why are research databases important

Library Research: Understanding Library Databases: Why are databases useful?

• Defining Databases
• How to Access Databases at the Library
• Accessing Databases On/Off Campus
• Why are databases useful?
• Facts about databases
• Types of databases
• Strategies for finding databases
• Understanding What's in a database
• Define your topic
• Choose keywords
• Boolean Operators
• Examples of using AND, OR, NOT
• Wildcards and Truncation
• Subject Headings
• Video: Choosing a Database
• Tutorial: Choosing & Using Keywords
• Quiz: Choosing and Using Keywords
• Quiz: Choosing a Database
• Tutorial: Search Techniques, Part 1
• Tutorial: Search Techniques, Part 2
• Quiz: Search Techniques
• Video: Refining Search Results

John B. Cade Library

Why is it a good choice to use library databases to conduct research for your research paper?

Library Databases are useful for Authority, Accuracy, and Access.

• Authority - Library databases contain works from professionally published sources and information are more likely to come from an expert on a particular topic. Unlike a website where it may be hard to tell who is responsible for the content, a library database clearly indicates the author and source.
• Accuracy and currency-Information in library databases are checked for accuracy and library databases always include the date of publication.
• Access - Library databases offer options like related terms, search options to broaden or narrow the search, and other organizational tools that support your research.
• << Previous: Accessing Databases On/Off Campus
• Next: Facts about databases >>
• Last Updated: Feb 28, 2024 2:03 PM
• URL: https://subr.libguides.com/ULD

Introduction to Library Research

• Find Articles by Subject
• Tips for Finding Articles
• How to Read a Scholarly Article
• Citation Help
• Helpful Videos

What is a Library Database?

A library database  is an electronic collection of information, organized to allow users to get that information by searching in various ways.

Examples of Database information

Articles from magazines, newspapers, peer-reviewed journals and more.  More unusual information such as medical images, audio recitation of a poem, radio interview transcripts, and instruction video can be found in databases as well.

General reference information such as that found in an encyclopedia.  Both very broad topic information is available as well as very specific.

Books.  Online versions, eBooks, are the same as print versions with some enhancements at times, such as an online glossary.  

Why not just use Google?

What’s the difference?

Information in a database has been tagged with all sorts of data, allowing you to search much more effectively and efficiently.  You can search by author, title, keyword, topic, publication date, type of source (magazine, newspaper, etc.) and more.

Database information has been evaluated in some way, ranging from a very rigorous peer-review publishing process to an editor of a popular magazine making a decision to publish an article. 

Databases are purchased, and most of the information is not available for free on the internet. The databases are continually updated as new information is produced.

Citation information.  Databases include the information you need to properly cite your sources and create your bibliography.  Information you retrieve using Google may or may not have this information.

My professor says I can’t use the Internet.  Can I still use these databases?

Yes!  The internet is only the delivery system for the databases.  The information in the databases is not found on the free web.

• << Previous: Home
• Next: Find Articles by Subject >>
• Last Updated: Mar 1, 2024 12:41 PM
• URL: https://libguides.regiscollege.edu/researchintro

A Question of Balance: Private Rights and the Public Interest in Scientific and Technical Databases (1999)

Chapter: 1 importance and use of scientific and technical databases, 1 importance and use of scientific and technical databases.

Modern technology has propelled us into the information age, making it possible to generate and record vast quantities of new data. 1 Advances in computing and communications technologies and the development of digital networks have revolutionized the manner in which data are stored, communicated, and manipulated. Databases, and uses to which they can be put, have become increasingly valuable commodities.

The now-common practice of downloading material from online databases has made it easy for researchers and other users to acquire data, which frequently have been produced with considerable investments of time, money, and other resources. Government agencies and most government contractors or grantees in the United States (though not in many other countries) usually make their data, produced at taxpayer expense, available at no cost or for the cost of reproduction and dissemination. For-profit and not-for-profit database producers (other than most government contractors and grantees) typically charge for access to and use of their data through subscriptions, licensing agreements, and individual sales.

Currently many for-profit and not-for-profit database producers are concerned about the possibility that significant portions of their databases will be copied or used in substantial part by others to create "new" derivative databases. If an identical or substantially similar database is then either redisseminated broadly or sold and used in direct competition with the original rights holder's database, the rights holder's revenues will be undermined, or in extreme cases,

the rights holder will be put out of business. Besides being unfair to the rights holder, this actual or potential loss of revenue may create a disincentive to produce and then maintain databases, thus reducing the number of databases available to others. However, preventing database uses by others, or making access and subsequent use more expensive or difficult, may discourage socially useful applications of databases. The question is how to protect rights in databases while ensuring that factual data remain accessible for public-interest and other uses.

This report explores issues in the conundrum posed by the need to properly balance the rights of original database producers or rights holders and the rights of all the downstream users and competitors—with the principal focus on the balance of rights between the database rights holders and public-interest users such as researchers, educators, and librarians. In particular, the Committee for a Study on Promoting Access to Scientific and Technical Data for the Public Interest focuses on scientific and technical (S&T) data (with examples drawn primarily from the physical and biological sciences) as an essential consideration in reasoned attempts to balance competing interests in databases.

To broaden the perspective of and enhance cooperation among the various competing interests, and to help ensure an efficient and effective outcome for all, the committee examines the following basic elements in the larger issue at hand:

Salient characteristics and the importance of S&T databases produced and used in research;

Impacts of computer technology on the production, distribution, and use of S&T databases;

Motivations of the various sectors involved in S&T research and the dissemination and use of research results;

Economic issues and incentives that influence the production, distribution, and use of S&T databases, and how these activities are interrelated;

Mechanisms currently in place for protecting these economic incentives; and

New legislation currently under consideration that would affect the production, dissemination, and use of S&T databases in a variety of ways.

To ensure the most successful outcome in the current debate over rights in databases, any new action must take account of and balance the legitimate interests of the various stakeholders, and must reflect awareness of how the broad public interest can best be served.

SCIENTIFIC AND TECHNICAL DATA AND THE CREATION OF NEW KNOWLEDGE

Factual data are both an essential resource for and a valuable output from scientific research. It is through the formation, communication, and use of facts and ideas that scientists conduct research. Throughout the history of science, new findings and ideas have been recorded and used as the basis for further scientific advances and for educating students.

Now, as a result of the near-complete digitization of data collection, manipulation, and dissemination over the past 30 years, almost every aspect of the natural world, human activity, and indeed every life form can be observed and captured in an electronic database. 2 There is barely a sector of the economy that is not significantly engaged in the creation and exploitation of digital databases, and there are many—such as insurance, banking, or direct marketing—that are completely database dependent.

Certainly scientific and engineering research is no exception in its growing reliance on the creation and exploitation of electronic databases. The genetic sequence of each living organism is a natural database, transforming biological

research and applications over the past decade into a data-dependent enterprise and giving rise to the rapidly growing field of bioinformatics. Myriad data collection platforms, recording and storing information about our physical universe at an ever-increasing rate, are now integral to the study and understanding of the natural environment, from small ecological subsystems to planet-scale geophysical processes and beyond. Similarly, the engineering disciplines continually create databases about our constructed environment and new technical processes, which are endlessly updated and refined to fuel our technological progress and innovation system.

Basic scientific research drives most of the world's progress in the natural and social sciences. Basic, or fundamental, research may be defined as research that leads to new understanding of how nature works and how its many facets are interconnected. 3 Society uses the fruits of such research to expand the world's base of knowledge and applies that knowledge in myriad ways to create wealth and to enhance the public welfare.

New scientific understanding and its applications are yielding benefits such as the following:

Improved diagnosis, pharmaceuticals, and treatments in medicine;

Better and higher-yield food production in agriculture;

New and improved materials for fabrication of manufactured objects, building materials, packaging, and special applications such as microelectronics;

Faster, cheaper, and safer transportation and communication;

Better means for energy production;

Improved ability to forecast environmental conditions and to manage natural resources; and

More powerful ways to explore all aspects of our universe, ranging from the finest subnuclear scale to the boundaries of the universe, and encompassing living organisms in all their variety. 4

SCIENTIFIC AND TECHNICAL DATABASES AS A RESOURCE-THE CURRENT CONTEXT

The committee's January 1999 Workshop on Promoting Access to Scientific and Technical Data for the Public Interest: An Assessment of Policy Options, 5

included presentations on and discussions of data activities in twelve selected organizations representing three broad sectors (government, not-for-profit, and commercial). The sample activities illustrated some of the depth and range of uses for S&T databases today ( Table 1.1 provides a summary) and indicated also the complexity of the often overlapping relationships and interests of database users and producers.

The discussion below outlines basic aspects of current data activities, including collection and production of S&T data and databases, dissemination, and use, and it describes the roles that the three sectors play in the overall process. In contrasting past and current practices, it indicates how ongoing technological advances have contributed to increased capabilities for obtaining and using S&T data. This description, which provides essential background for the remainder of this report, draws on examples from the four general discipline areas—geographic and environmental, genomic, chemical and chemical engineering, and meteorological research and applications—focused on in the workshop.

Collection of Original Data and Production of New Databases

Sources of primary data and uses.

The process of scientific inquiry typically has begun with the formulation of a working hypothesis, based usually on limited observation and data, followed by experimentation designed to test the hypothesis. The experimentation results in the accumulation of new data used to confirm or refute the original hypothesis. Understanding of the natural and physical world has been advanced by researchers building on a growing base of knowledge that is continually being refined, tested, and augmented in the long-established approach to scientific inquiry known as the scientific method.

With the advent of digital technologies has come a dramatic increase in the pace and volume of data acquisition. Ongoing rapid advances in electronic technologies for computing and communications, experimentation, and observation ranging from high-frequency direct sampling to multispectral remote sensing have enabled dramatic increases in the quantities of data generated about the natural world at scales from the microcosm to the macrocosm. For instance, the volume of data on weather and climate stored in the National Climatic Data Center has increased 750-fold in the past two decades ( Box 1.2 ). A pharmaceutical company that 5 years ago could characterize 100,000 compounds per year can now handle a million compounds in a week.

Although some of these data represent actual measurements, large quantities of data also are being generated through numerical simulations performed on supercomputers. Collection of new data is becoming increasingly automated as recording devices and instrumentation become more sophisticated and rapid. Moreover, many older paper-based data sets, such as historical U.S. Weather

TABLE 1.1 Examples of Different Types of S&T Database Activities Discussed in the January 1999 Workshop

Bureau observational records or U.S. census data, are being digitized and organized into electronically accessible databases. This shift from a data-poor to a data-rich research and education environment is occurring through the activities of a host of government agencies, universities, and other research establishments, both public and private, nationally and internationally, in diverse research disciplines.

In many cases data are being collected not to answer specific scientific questions, but rather to describe various physical and biological phenomena in ever-increasing detail. This broad-based acquisition of data, coupled with data mining and knowledge discovery 6 and the broad review and analysis of information stored in large databases, is anticipated to reveal trends or patterns or to lead

to discoveries that will serve as a source of new hypotheses. The increasing use of databases as a research tool, whether in pursuit of new information or clues to unexpected relationships as starting points for conducting fundamental research, or for developing new commercial applications, 7 relies on the production and availability of such databases as an initial step in the process.

In recent decades, and in most disciplines today, the federal government and federally funded research have played the major role in generating primary S&T data. Substantial amounts and varieties of data are created by thousands of federal government grantees doing basic research, either individually or in teams, and most often at universities and other not-for-profit research institutions. The National Science Foundation and the National Institutes of Health, which in FY 1999 funded over $2.6 billion 8 and $11.8 billion 9 in extramural grants, respectively, provide the bulk of support for these efforts. However, other federal departments and independent agencies also have significant research grant programs that involve the collection of research data and the production of associated databases outside the direct control of the government.

In FY 1998, the federal government spent approximately $19.5 billion on intramural and extramural basic research and almost $50 billion on applied research. 10 A substantial fraction of that funding was devoted to the creation of primary data used for fundamental research, education, and other public-interest purposes. Among the current major observational data research programs are NASA's Earth Observing System and numerous space science missions. 11 The Human Genome Project of the National Institutes of Health is another large-scale, data-intensive research effort. 12 Large experimental facilities dedicated to

enabling advances in fundamental physics are operated by the Department of Energy 13 or by universities or not-for-profit organizations under contract to one or more federal government agencies.

The government also collects large amounts of data for operational, non-research applications, such as daily weather forecasting, public health and safety, and other public-interest government functions. Many of the resulting databases—such as those developed from observations made by meteorological satellites and ground-based NEXRAD radars operated by the National Oceanic and Atmospheric Administration, or the geological, hydrological, and ecological data collected by the U.S. Geological Survey in response to Department of the Interior mandates 14 have multiple uses, as well as value for both immediate and long-term research.

Additional extensive data are collected continuously at the state and local government levels, principally in support of public government functions, such as the provision of local health, education, and welfare services, or the regulation of various economic activities. These databases also provide a wealth of factual and statistical information for social science researchers, as well as for historians.

While original data collection activities in the United States, especially for research and educational purposes, are carried out largely under government auspices, a significant amount of basic research is also funded outside government by both not-for-profit and commercial institutions. In 1998, nongovernmental sources spent approximately $15 billion on basic research, 15 some of which was used to produce and analyze new S&T databases. In addition, most large federal government research projects and programs involve one or more foreign government agencies, often with significant international participation of researchers. 16 Large-scale research in areas such as climate trends, marine biology, and space science requires international cooperation in the collection, production, and dissemination of observational data. The effectiveness of such cooperation is dependent on, among other things, agreement on laws and policies for sharing and using those data in different countries.

Significant Aspects of Database Production

The rate of scientific progress depends not only on the collection of new data, but also on the quality of the data collected, their ease of use, and the dissemination of information about the database. Considerable attention must be

given to all those activities necessary to organize raw or disparate data into databases for broader use. These functions and methods typically include digitally processing the data into successively more highly refined and usable products; organizing the data into a database with appropriate structure, format, presentation, and documentation; creating the necessary accompanying analytical support software; providing adequate quality assurance and quality control; announcing the availability of the database; and arranging for secure near-term storage and eventual deposit in an archive that preserves the database and enables continued access. 17 As databases become ever larger and more complex, effective database production methods become increasingly important and constitute a significant component of the overall cost of the database.

The production of S&T databases requires at least some involvement by those responsible for collecting the original data. Typically, those closest to the collection of the data have the greatest expertise and interest in organizing them into a database whose contents are both available to and readily usable by others. Furthermore, the highly technical and frequently esoteric nature of S&T databases is likely to require that the original data collectors (or project scientists) participate in at least the initial stages of organizing, documenting, and reviewing the quality of data in the database. Involvement by the original data collectors in managing that part of the database production process decreases the probability that unusable or inaccurate databases will result, reduces the need for subsequent attempts to rescue or complete such data sets, and saves time and expense overall.

The level of processing and related database production activities is a significant factor in defining the ultimate utility (and legal protection) of a digital data collection. It is the original unprocessed, or minimally processed, data that are usually the most difficult to understand or use by anyone other than the originator of those data, or an expert in that particular area. With every successive level of processing, organization, and documentation, the data tend to become more comprehensible and easier to use by the nonexpert. As a database is prepared for more widespread use with the addition of more creative elements, it also tends to become more copyrightable as well as more generally marketable. In the case of observational sciences, it is the raw, noncopyrightable data that are typically of greatest long-term value to basic research (see "The Uniqueness of Many S&T Databases," below). Increased or new protection for noncopyrightable databases previously in the public domain could therefore have a disproportionate impact on the heretofore unrestricted access to and use of raw data sets for basic research and education.

Although the production of many S&T databases is performed by, or with

the active participation of, the originating researchers, it also is common for third parties to be involved in an aspect of database production referred to as "value adding." Because the comprehensive production of very large or complex databases can be quite expensive, organizations that collect data, especially in government, are increasingly "outsourcing" database production and subsequent distribution to third parties in an effort to contain costs. In such instances, the raw, or minimally processed, data are provided to a private-sector vendor expressly contracted with by government to add value to the data and produce a database in a commercially marketable format to meet broad user requirements. However, since most federal government databases are openly available and in the public domain, adding value to them may be undertaken as an initiative by entrepreneurs that see a business opportunity in such activities, without any formal contractual arrangement with the government data source. (For examples of such third-party providers, see the summary in Table 1.1 and the committee's online workshop Proceedings. )

In the context of this report, the most significant aspect of these third-party, value-adding arrangements is that they almost always involve the transfer of public or publicly funded data and databases to private-sector proprietary database producers and vendors. To the extent that these transfers are done on an exclusive basis and the original government databases are not maintained or otherwise made publicly available, the result is a concomitant decrease in the public availability of S&T data.

Perspective on Number of Databases Produced—Some Statistics

According to one set of recently compiled statistics, 18 over the period from 1975 through 1998 the number of all databases grew by a factor of 38 (from 301

to 11,339), the number of database producers increased by a factor of 18 (from 200 to 3,686), and the number of vendors grew by a factor of 23 (from 105 to 2,459). In 1975 the 301 identified databases contained about 52 million records, whereas in 1998 the 11,339 tallied databases held nearly 12.05 billion records, a 231-fold increase in the number of records.

Although in today's digitized information world databases are produced on all continents, the percentage of all types of databases produced in the United States continues to represent the lion's share of the global output. In 1998, of the 11,339 databases that were identified, 63% were produced in the United States. In 1975, of the 301 publicly available, computer-readable databases worldwide, 59% were U.S. databases. From 1985 to 1993, the ratio of U.S. to non-U.S. databases remained at about 2:1. From 1994 on, production of non-U.S. databases has accelerated somewhat, so that in 1998 the ratio of the number of U.S. to non-U.S. databases was about 3:2. The average size of U.S. databases in terms of the number of records they contained was larger than that of the non-U.S. databases. As noted above, however, most U.S. government and academic databases are not represented in these figures.

In the source quoted here, database statistics were compiled in eight major subject categories—business, health/life/medical sciences, humanities, law, multi-disciplinary, news/general, science/technology/engineering, and social sciences. If the health/life/medical sciences category is combined with science/technology/engineering, that general scientific and technical category had the largest number of databases (28%) in 1998, followed by business (26%), news/general (15%), and law (11%), with the remaining three categories accounting for the other 20%. 19

The Uniqueness of Many S&T Databases

A key characteristic of original S&T databases is that many of them are the only one of their particular kind, available only from a single-source, which has significant economic and legal implications, as discussed in subsequent chapters of this report. For example, many S&T databases describe physical phenomena or transitory events that have been rendered unique by the passage of time. Measurements of a snowstorm obtained with a single radar observation, or a statistical compilation of some key socioeconomic characteristics such as income levels collected by a state agency, cannot be recaptured after the original event. The vast majority of observational data sets of the natural world, as well as all unique historical records, can never again be recreated independently and are thus available only as originally obtained, frequently from a single-source. Other S&T databases are de facto unique because the cost of obtaining the data was

extremely high. This is the case with very large facilities for physical experiments or space-based observatories.

Even when data similar but not identical to original research results or observations are available for use in non-technical applications, scientists and engineers will likely not find an inexact replica of a database a suitable substitute if it does not meet certain specifications for a particular experiment or analysis. For example, two infrared sensors with similar spatial and spectral characteristics on different satellites collecting observations of Earth may provide relatively interchangeable data products for the non-expert consumer, but for a researcher, the absence of one spectral band can make all the difference in whether a certain type of research can be performed. Thus a database generally deemed adequate as a substitute in the mass consumer market very likely will not be usable for many research or education purposes.

Dissemination of Scientific and Technical Data and the Issue of Access

S&T data traditionally were disseminated in paper form in journal articles, textbooks, reference books, and abstracting and indexing publications. As data have become available in electronic form, they have been distributed via magnetic tape and, more recently, optical media such as CD-ROM or DVD. The growing use of the Internet has revolutionized dissemination by allowing most databases to be made available globally in electronic form. Digitization and the potential for instant, low-cost global communication have opened tremendous new opportunities for the dissemination and utilization of S&T databases and other forms of information, but also have led to a blurring of the traditional roles and relationships of database producers, vendors, and users of those databases in the government, not-for-profit, and commercial-sectors. In fact, virtually anyone who obtains access to a digital database can instantly become a worldwide disseminator, whether legally or illegally. 20

Two of the most important mechanisms for the dissemination of public and publicly funded databases have been government data centers and public libraries. Government, or government-funded, data centers have been created in recent decades for dissemination of data obtained in certain programs or research disciplines. Examples of such data centers include the National Center for Biotech

nology Information and the National Climatic Data Center ( Table 1.1 ), but many others have been established for almost every field of research. 21

Public libraries, whether part of the federal depository library program, university research libraries, or other public libraries or foundations specializing in various S&T or other academic subjects, not only preserve and publicly disseminate government data, but provide general public access for many proprietary S&T databases as well. With ever-increasing costs, however, the libraries' ability to provide this public "safety net" for all published products is diminishing. 22

Historically, most federal government S&T data and government-funded research data in the United States have been fully and openly available to the public. 23 This has meant that such data are available free or at low cost for academic and commercial research—and indeed any other use—without restrictions and can be incorporated into derivative databases, which can, themselves, be redistributed and incorporated into additional databases. In some instances in which the government contracts for the dissemination of data, however, the rights assigned to the database vendor may place restrictions on the ability of the research and education communities to fully utilize the data. Increasingly, both government and not-for-profit organizations are exploring means to recover database production and distribution costs, or to generate revenue streams in order to support their expensive data activities, thereby making them function in a manner similar to commercial organizations.

The ability to access existing data and to extract and recombine selected portions of them for research or for incorporation into new databases for further distribution and use has become a key part of the scientific process by which new insights are gained and knowledge is advanced. When the ability to access or distribute data on an international basis is required, various intergovernmental agreements are depended on to facilitate such exchanges in the public sector. In contrast, to achieve a suitable return on their investment, private-sector vendors of proprietary databases typically seek to control unauthorized access to and use of their databases. It is at the intersection of public and private interests in data

where the greatest challenges emerge. As an example, Box 1.3 sketches some of the issues and approaches currently being tried.

Use of Scientific and Technical Databases

Prior to its public dissemination, the use of a database is limited to those involved in the collection of data or production, and therefore does not provide the opportunity to contribute broadly to the advancement of scientific knowledge, technical progress, economic growth, or other applications beyond those of the immediate group. It is only upon the distribution of a database that its far-reaching research, educational, and other socioeconomic values are realized. One or more researchers applying varying hypotheses, manipulating the data in different ways, or combining elements from disparate databases may produce a diversity of data and information products. The contribution of any of these products to scientific and technical knowledge might well assume a value far greater than the costs of database production and dissemination. The results of a thorough

database analysis may reveal a value of the data not apparent in even a detailed examination of the individual elements of the database itself. With the widespread availability of information on the Internet have come abundant opportunities to search for scientific and technical gold in this ore of factual elements. The possibilities for discovery of new insights about the natural word—with both commercial and public-interest value—are extraordinary.

In considering how databases are used, it is important to distinguish between end use and derivative use. End use—accessing a database to verify some fact or perform some job-related or personal task, such as obtaining an example for a work memo—is most typical of public consumer uses. End use does not involve the physical integration of one or more portions of the database into another database in order to create a new information product. A derivative (value-adding or transformative) use (see Box 1.1 ) builds on a preexisting database and includes at least one, and frequently many more, extractions from one or more databases to create a new database, which can be used for the same, a similar, or an entirely different purpose than the original component database(s).

Integration of Distributed Data to Broaden Access and Potential for Discovery

In seeking new knowledge, researchers may gather data from widely disparate sources. A significant advantage arising from the abundance of digitized data now accessible through both private and public networks is the potential for linking data in multiple (even thousands of) databases. The ability to link sites on the World Wide Web is one type of integration that could result in more data being available overall to users. Another is the merging of databases of the same or complementary content. It is now possible to maintain a site with continuously verified links to related information sites for use by subscribers or members of a specific group; an example is the Engineering Village of Engineering Information, Inc. 24 Yet another type of integration occurs in the connection of distributed databases such that different parts of a single large database may reside on different computers in geographically dispersed locations throughout the country or the world. With a common structure, data can be located in a physically distributed network and accessed as if they were in one database in one computer in one location. The cost can thus be distributed and the value of each contributory database increased. Still other databases are automatically created from other databases. For example, data are routinely mined and collected by ''knowbots" and "web crawlers" (software employing artificial intelligence and rule-based selection techniques) on the Internet throughout the world and retrieved for pro

cessing and further use. One such data mining activity in the area of biotechnology was described and discussed at the committee's January 1999 workshop (see the Molecular Applications Group's activities summarized in Table 1.1 ).

With a capability to integrate information in multiple databases comes the potential for exploiting relationships identified in the information and developing new knowledge. In many scientific fields, the initial investment by the database rights holder may not produce the greatest value until it is integrated with the investments of others. For example, while protein sequence data are valuable in their own right, their value is greatly enhanced if associated x-ray crystallographic data are also concurrently available. It is possible to use the combined data to understand the way in which protein chains are folded and, in the case of an enzyme, the way in which various nonsequential residues, or even residues on separate protein chains, combine to form an active site.

Derivative Databases and New Data-Driven Research and Capabilities

The ethos in research is that science builds on science. The creation of derivative databases not only enables incremental advances in the knowledge base, but also can contribute to major new findings, particularly when existing data are combined with new or entirely different data. The importance for research and related educational activities of producing new derivative databases cannot be overemphasized. 25 The vast increase in the creation of digital databases in recent decades, together with the ability to make them broadly and instantaneously available, has resulted in entire new fields of data-driven research.

For example, the study of biological systems has been transformed radically in the past 20 years from an experimental research endeavor conducted in laboratories to one that relies heavily on computing and on access to and further refine

ment of globally linked databases. 26 Indeed, one of the fastest growing disciplines is bioinformatics, a computer-based approach to biological research. New technologies, such as DNA microarrays and high-throughput sequencing machines, are producing a deluge of data. A challenge to biology in the coming decades will be to convert these data into knowledge. 27

The availability of global remote-sensing satellite observations, coupled with other airborne and in situ observational capabilities, has given rise to a new field of environmental research, Earth system science, which integrates the study of the physical and biological processes of our planet at various scales. The large meteorological databases obtained from government satellites, ground-based radar, and other data collection systems pose a challenge similar to that mentioned above for biology, but also already have yielded a remarkable range of commercial and non-commercial value. Dissemination of the atmospheric observations in real-time or near-real time for "nowcasts" and daily weather forecasts has very high commercial value, which is captured by third-party distributors. Use of these atmospheric observations to develop numerical models that predict the weather accurately, hours or days in advance, adds value in terms of safety and economic benefits to society that are not readily quantifiable. While the economic value of these data can be gauged by the profits of private-sector distributors, how does one measure the value of the lives and property saved by timely and accurate hurricane forecasts and tornado warnings? Once the immediate and most lucrative commercial value is exploited, the resulting data continue to have significant commercial and public-interest uses indefinitely. For instance, these data enable basic research on severe weather and long-term climate trends and provide various retrospective applications for industry. The original databases are archived and made available by the National Climatic Data Center (see Box 1.2 ). Derivative databases and data products are distributed under various arrangements by both commercial and not-for-profit entities like the Unidata Program of the University Corporation for Atmospheric Research (see Table 1.1 and the online workshop Proceedings ).

Geographic information systems that integrate myriad sources of data provide an opportunity for new insights about the natural and constructed environment, greatly enhancing our knowledge of where we live and how we affect our physical environment. Important applications include environmental management, urban planning, route planning and navigation, emergency preparedness

and response, land-use regulation, and enhancement of agricultural productivity, among many others. 28

Finally, databases used by researchers and educators also frequently are produced and disseminated primarily for other purposes. For example, a physical scientist studying the complex relationships among geology, hydrology, and biology as they relate to the preservation of species diversity likely would draw on numerous digital and hard copy databases originally gathered for other purposes. A social scientist studying the characteristics and patterns of urban crime or the spread of communicable diseases likely would do the same. For many scientists, the ability to supplement existing databases with further data collection in a seamless web of old and new data is basic to meeting the needs of their specific investigations.

Text Databases and Online Publication

Another type of S&T database not yet discussed, but that is used extensively by the research community, consists primarily of text with data summarized or added as examples. These databases may consist of primary literature (as in the case of full text databases of journal articles) or secondary literature (as in the case of bibliographic reference databases). Traditionally, this text has been available in print form, with publishers providing peer review, professional editing, indexing and formatting, and other services, including marketing and distribution. Increasingly this information is being provided as text databases with the publishers also providing the systems that allow access to these databases. These value-adding or information repackaging functions are performed by both not-for-profit and for-profit organizations. For example, the not-for-profit American Association for the Advancement of Science, a scientific society, produces a database containing the full text of articles from Science magazine, including enhancements to the content that do not appear in the print version. 29 Similarly, the for-profit publisher Elsevier Science produces Science Direct, a database containing the full text of its journal articles. Bibliographic reference databases are also produced by government, not-for-profit, and for-profit organizations, such as the National Library of Medicine, Chemical Abstracts Service, and the Institute for Scientific Information, respectively (see Table 1.1 and the online workshop Proceedings 30 ). Where full text databases include associated data collec

tions, physical and legal possession of the data collections may be retained by the originator or may pass to the publisher.

As S&T data and results are increasingly digitized and made available online, publishers are seeking access to and inclusion of the underlying data collections on which published articles are based. The intent is not only to provide greater validity and support for published research articles, but also to make their online publications more interesting and useful to the S&T customer base. The ability to link to the underlying databases instantaneously and at different levels of detail adds an entirely new and exciting dimension to scientific publishing and to the potential for new research, but also raises the question of who will have the rights to exploiting those data.

THE CHALLENGE OF EFFECTIVELY BALANCING PRIVATE RIGHTS AND THE PUBLIC INTEREST IN SCIENTIFIC AND TECHNICAL DATABASES

The general advancement of knowledge independent of its eventual societal benefits is a goal of basic research. Nevertheless, an endless array of examples demonstrates how the creation of new knowledge, building on the existing base of understanding and information developed by researchers, has enabled broad and important socioeconomic benefits for the nation as a whole. Our society appreciates that knowledge itself is intrinsically valuable and important, and our success in the world market for advanced technology products and services attests to the direct economic benefits of the resulting applications. It is for these reasons that government funds basic research and related data activities as a public good. 31 , 32 Yet it is precisely these activities that are at risk of being hindered, if not in some instances stopped, by proposed major changes to the legal protections of factual databases.

Legislative efforts are currently under way in the United States, the European Union, and the World Intellectual Property Organization to greatly enhance the legal protection of proprietary databases. These new legal approaches threaten to compromise traditional and customary access to and use of S&T data for public-interest endeavors, including not-for-profit research, education, and general library uses. At the same time, there are legitimate concerns by the rights holders in databases regarding unauthorized and uncompensated uses of their data products, including at times the wholesale commercial misappropriation of proprietary databases.

Because of the complex web of interdependent relationships among public-sector and private-sector database producers, disseminators, and users, any action to increase the rights of persons in one category likely will compromise the rights of the persons in the other categories, with far-reaching and potentially negative consequences. Of course, it is in the common interest of both database rights holders and users—and of society in general—to achieve a workable balance among the respective interests so that all legitimate rights remain reasonably protected.

New legal approaches, such as the European Union's 1996 Directive on the Legal Protection of Databases, and other legal initiatives now being considered in the United States at the federal and state level, are threatening to compromise public access to scientific and technical data available through computerized databases. Lawmakers are struggling to strike an appropriate balance between the rights of database rights holders, who are concerned about possible commercial misappropriation of their products, and public-interest users of the data such as researchers, educators, and libraries.

A Question of Balance examines this balancing act. The committee concludes that because database rights holders already enjoy significant legal, technical, and market-based protections, the need for statutory protection has not been sufficiently substantiated. Nevertheless, although the committee opposes the creation of any strong new protective measures, it recognizes that some additional limits against wholesale misappropriation of databases may be necessary. In particular, a new, properly scoped and focused U.S. statute might provide a reasonable alternative to the European Union's highly protectionistic database directive. Such legislation could then serve as a legal model for an international treaty in this area. The book recommends a number of guiding principles for such possible legislation, as well as related policy actions for the administration.

READ FREE ONLINE

Welcome to OpenBook!

You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

Do you want to take a quick tour of the OpenBook's features?

Show this book's table of contents , where you can jump to any chapter by name.

...or use these buttons to go back to the previous chapter or skip to the next one.

Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

Switch between the Original Pages , where you can read the report as it appeared in print, and Text Pages for the web version, where you can highlight and search the text.

To search the entire text of this book, type in your search term here and press Enter .

Share a link to this book page on your preferred social network or via email.

View our suggested citation for this chapter.

Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

Get Email Updates

Do you enjoy reading reports from the Academies online for free ? Sign up for email notifications and we'll let you know about new publications in your areas of interest when they're released.

• Open access
• Published: 06 December 2017

Optimal database combinations for literature searches in systematic reviews: a prospective exploratory study

• Wichor M. Bramer 1 ,
• Melissa L. Rethlefsen 2 ,
• Jos Kleijnen 3 , 4 &
• Oscar H. Franco 5  

Systematic Reviews volume  6 , Article number:  245 ( 2017 ) Cite this article

151k Accesses

860 Citations

88 Altmetric

Metrics details

Within systematic reviews, when searching for relevant references, it is advisable to use multiple databases. However, searching databases is laborious and time-consuming, as syntax of search strategies are database specific. We aimed to determine the optimal combination of databases needed to conduct efficient searches in systematic reviews and whether the current practice in published reviews is appropriate. While previous studies determined the coverage of databases, we analyzed the actual retrieval from the original searches for systematic reviews.

Since May 2013, the first author prospectively recorded results from systematic review searches that he performed at his institution. PubMed was used to identify systematic reviews published using our search strategy results. For each published systematic review, we extracted the references of the included studies. Using the prospectively recorded results and the studies included in the publications, we calculated recall, precision, and number needed to read for single databases and databases in combination. We assessed the frequency at which databases and combinations would achieve varying levels of recall (i.e., 95%). For a sample of 200 recently published systematic reviews, we calculated how many had used enough databases to ensure 95% recall.

A total of 58 published systematic reviews were included, totaling 1746 relevant references identified by our database searches, while 84 included references had been retrieved by other search methods. Sixteen percent of the included references (291 articles) were only found in a single database; Embase produced the most unique references ( n  = 132). The combination of Embase, MEDLINE, Web of Science Core Collection, and Google Scholar performed best, achieving an overall recall of 98.3 and 100% recall in 72% of systematic reviews. We estimate that 60% of published systematic reviews do not retrieve 95% of all available relevant references as many fail to search important databases. Other specialized databases, such as CINAHL or PsycINFO, add unique references to some reviews where the topic of the review is related to the focus of the database.

Conclusions

Optimal searches in systematic reviews should search at least Embase, MEDLINE, Web of Science, and Google Scholar as a minimum requirement to guarantee adequate and efficient coverage.

Peer Review reports

Investigators and information specialists searching for relevant references for a systematic review (SR) are generally advised to search multiple databases and to use additional methods to be able to adequately identify all literature related to the topic of interest [ 1 , 2 , 3 , 4 , 5 , 6 ]. The Cochrane Handbook, for example, recommends the use of at least MEDLINE and Cochrane Central and, when available, Embase for identifying reports of randomized controlled trials [ 7 ]. There are disadvantages to using multiple databases. It is laborious for searchers to translate a search strategy into multiple interfaces and search syntaxes, as field codes and proximity operators differ between interfaces. Differences in thesaurus terms between databases add another significant burden for translation. Furthermore, it is time-consuming for reviewers who have to screen more, and likely irrelevant, titles and abstracts. Lastly, access to databases is often limited and only available on subscription basis.

Previous studies have investigated the added value of different databases on different topics [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. Some concluded that searching only one database can be sufficient as searching other databases has no effect on the outcome [ 16 , 17 ]. Nevertheless others have concluded that a single database is not sufficient to retrieve all references for systematic reviews [ 18 , 19 ]. Most articles on this topic draw their conclusions based on the coverage of databases [ 14 ]. A recent paper tried to find an acceptable number needed to read for adding an additional database; sadly, however, no true conclusion could be drawn [ 20 ]. However, whether an article is present in a database may not translate to being found by a search in that database. Because of this major limitation, the question of which databases are necessary to retrieve all relevant references for a systematic review remains unanswered. Therefore, we research the probability that single or various combinations of databases retrieve the most relevant references in a systematic review by studying actual retrieval in various databases.

The aim of our research is to determine the combination of databases needed for systematic review searches to provide efficient results (i.e., to minimize the burden for the investigators without reducing the validity of the research by missing relevant references). A secondary aim is to investigate the current practice of databases searched for published reviews. Are included references being missed because the review authors failed to search a certain database?

Development of search strategies

At Erasmus MC, search strategies for systematic reviews are often designed via a librarian-mediated search service. The information specialists of Erasmus MC developed an efficient method that helps them perform searches in many databases in a much shorter time than other methods. This method of literature searching and a pragmatic evaluation thereof are published in separate journal articles [ 21 , 22 ]. In short, the method consists of an efficient way to combine thesaurus terms and title/abstract terms into a single line search strategy. This search is then optimized. Articles that are indexed with a set of identified thesaurus terms, but do not contain the current search terms in title or abstract, are screened to discover potential new terms. New candidate terms are added to the basic search and evaluated. Once optimal recall is achieved, macros are used to translate the search syntaxes between databases, though manual adaptation of the thesaurus terms is still necessary.

Review projects at Erasmus MC cover a wide range of medical topics, from therapeutic effectiveness and diagnostic accuracy to ethics and public health. In general, searches are developed in MEDLINE in Ovid (Ovid MEDLINE® In-Process & Other Non-Indexed Citations, Ovid MEDLINE® Daily and Ovid MEDLINE®, from 1946); Embase.com (searching both Embase and MEDLINE records, with full coverage including Embase Classic); the Cochrane Central Register of Controlled Trials (CENTRAL) via the Wiley Interface; Web of Science Core Collection (hereafter called Web of Science); PubMed restricting to records in the subset “as supplied by publisher” to find references that not yet indexed in MEDLINE (using the syntax publisher [sb]); and Google Scholar. In general, we use the first 200 references as sorted in the relevance ranking of Google Scholar. When the number of references from other databases was low, we expected the total number of potential relevant references to be low. In this case, the number of hits from Google Scholar was limited to 100. When the overall number of hits was low, we additionally searched Scopus, and when appropriate for the topic, we included CINAHL (EBSCOhost), PsycINFO (Ovid), and SportDiscus (EBSCOhost) in our search.

Beginning in May 2013, the number of records retrieved from each search for each database was recorded at the moment of searching. The complete results from all databases used for each of the systematic reviews were imported into a unique EndNote library upon search completion and saved without deduplication for this research. The researchers that requested the search received a deduplicated EndNote file from which they selected the references relevant for inclusion in their systematic review. All searches in this study were developed and executed by W.M.B.

Determining relevant references of published reviews

We searched PubMed in July 2016 for all reviews published since 2014 where first authors were affiliated to Erasmus MC, Rotterdam, the Netherlands, and matched those with search registrations performed by the medical library of Erasmus MC. This search was used in earlier research [ 21 ]. Published reviews were included if the search strategies and results had been documented at the time of the last update and if, at minimum, the databases Embase, MEDLINE, Cochrane CENTRAL, Web of Science, and Google Scholar had been used in the review. From the published journal article, we extracted the list of final included references. We documented the department of the first author. To categorize the types of patient/population and intervention, we identified broad MeSH terms relating to the most important disease and intervention discussed in the article. We copied from the MeSH tree the top MeSH term directly below the disease category or, in to case of the intervention, directly below the therapeutics MeSH term. We selected the domain from a pre-defined set of broad domains, including therapy, etiology, epidemiology, diagnosis, management, and prognosis. Lastly, we checked whether the reviews described limiting their included references to a particular study design.

To identify whether our searches had found the included references, and if so, from which database(s) that citation was retrieved, each included reference was located in the original corresponding EndNote library using the first author name combined with the publication year as a search term for each specific relevant publication. If this resulted in extraneous results, the search was subsequently limited using a distinct part of the title or a second author name. Based on the record numbers of the search results in EndNote, we determined from which database these references came. If an included reference was not found in the EndNote file, we presumed the authors used an alternative method of identifying the reference (e.g., examining cited references, contacting prominent authors, or searching gray literature), and we did not include it in our analysis.

Data analysis

We determined the databases that contributed most to the reviews by the number of unique references retrieved by each database used in the reviews. Unique references were included articles that had been found by only one database search. Those databases that contributed the most unique included references were then considered candidate databases to determine the most optimal combination of databases in the further analyses.

In Excel, we calculated the performance of each individual database and various combinations. Performance was measured using recall, precision, and number needed to read. See Table  1 for definitions of these measures. These values were calculated both for all reviews combined and per individual review.

Performance of a search can be expressed in different ways. Depending on the goal of the search, different measures may be optimized. In the case of a clinical question, precision is most important, as a practicing clinician does not have a lot of time to read through many articles in a clinical setting. When searching for a systematic review, recall is the most important aspect, as the researcher does not want to miss any relevant references. As our research is performed on systematic reviews, the main performance measure is recall.

We identified all included references that were uniquely identified by a single database. For the databases that retrieved the most unique included references, we calculated the number of references retrieved (after deduplication) and the number of included references that had been retrieved by all possible combinations of these databases, in total and per review. For all individual reviews, we determined the median recall, the minimum recall, and the percentage of reviews for which each single database or combination retrieved 100% recall.

For each review that we investigated, we determined what the recall was for all possible different database combinations of the most important databases. Based on these, we determined the percentage of reviews where that database combination had achieved 100% recall, more than 95%, more than 90%, and more than 80%. Based on the number of results per database both before and after deduplication as recorded at the time of searching, we calculated the ratio between the total number of results and the number of results for each database and combination.

Improvement of precision was calculated as the ratio between the original precision from the searches in all databases and the precision for each database and combination.

To compare our practice of database usage in systematic reviews against current practice as evidenced in the literature, we analyzed a set of 200 recent systematic reviews from PubMed. On 5 January 2017, we searched PubMed for articles with the phrase “systematic review” in the title. Starting with the most recent articles, we determined the databases searched either from the abstract or from the full text until we had data for 200 reviews. For the individual databases and combinations that were used in those reviews, we multiplied the frequency of occurrence in that set of 200 with the probability that the database or combination would lead to an acceptable recall (which we defined at 95%) that we had measured in our own data.

Our earlier research had resulted in 206 systematic reviews published between 2014 and July 2016, in which the first author was affiliated with Erasmus MC [ 21 ]. In 73 of these, the searches and results had been documented by the first author of this article at the time of the last search. Of those, 15 could not be included in this research, since they had not searched all databases we investigated here. Therefore, for this research, a total of 58 systematic reviews were analyzed. The references to these reviews can be found in Additional file 1 . An overview of the broad topical categories covered in these reviews is given in Table  2 . Many of the reviews were initiated by members of the departments of surgery and epidemiology. The reviews covered a wide variety of disease, none of which was present in more than 12% of the reviews. The interventions were mostly from the chemicals and drugs category, or surgical procedures. Over a third of the reviews were therapeutic, while slightly under a quarter answered an etiological question. Most reviews did not limit to certain study designs, 9% limited to RCTs only, and another 9% limited to other study types.

Together, these reviews included a total of 1830 references. Of these, 84 references (4.6%) had not been retrieved by our database searches and were not included in our analysis, leaving in total 1746 references. In our analyses, we combined the results from MEDLINE in Ovid and PubMed (the subset as supplied by publisher) into one database labeled MEDLINE.

Unique references per database

A total of 292 (17%) references were found by only one database. Table  3 displays the number of unique results retrieved for each single database. Embase retrieved the most unique included references, followed by MEDLINE, Web of Science, and Google Scholar. Cochrane CENTRAL is absent from the table, as for the five reviews limited to randomized trials, it did not add any unique included references. Subject-specific databases such as CINAHL, PsycINFO, and SportDiscus only retrieved additional included references when the topic of the review was directly related to their special content, respectively nursing, psychiatry, and sports medicine.

Overall performance

The four databases that had retrieved the most unique references (Embase, MEDLINE, Web of Science, and Google Scholar) were investigated individually and in all possible combinations (see Table  4 ). Of the individual databases, Embase had the highest overall recall (85.9%). Of the combinations of two databases, Embase and MEDLINE had the best results (92.8%). Embase and MEDLINE combined with either Google Scholar or Web of Science scored similarly well on overall recall (95.9%). However, the combination with Google Scholar had a higher precision and higher median recall, a higher minimum recall, and a higher proportion of reviews that retrieved all included references. Using both Web of Science and Google Scholar in addition to MEDLINE and Embase increased the overall recall to 98.3%. The higher recall from adding extra databases came at a cost in number needed to read (NNR). Searching only Embase produced an NNR of 57 on average, whereas, for the optimal combination of four databases, the NNR was 73.

Probability of appropriate recall

We calculated the recall for individual databases and databases in all possible combination for all reviews included in the research. Figure  1 shows the percentages of reviews where a certain database combination led to a certain recall. For example, in 48% of all systematic reviews, the combination of Embase and MEDLINE (with or without Cochrane CENTRAL; Cochrane CENTRAL did not add unique relevant references) reaches a recall of at least 95%. In 72% of studied systematic reviews, the combination of Embase, MEDLINE, Web of Science, and Google Scholar retrieved all included references. In the top bar, we present the results of the complete database searches relative to the total number of included references. This shows that many database searches missed relevant references.

Percentage of systematic reviews for which a certain database combination reached a certain recall. The X -axis represents the percentage of reviews for which a specific combination of databases, as shown on the y -axis, reached a certain recall (represented with bar colors). Abbreviations: EM Embase, ML MEDLINE, WoS Web of Science, GS Google Scholar. Asterisk indicates that the recall of all databases has been calculated over all included references. The recall of the database combinations was calculated over all included references retrieved by any database

Differences between domains of reviews

We analyzed whether the added value of Web of Science and Google Scholar was dependent of the domain of the review. For 55 reviews, we determined the domain. See Fig.  2 for the comparison of the recall of Embase, MEDLINE, and Cochrane CENTRAL per review for all identified domains. For all but one domain, the traditional combination of Embase, MEDLINE, and Cochrane CENTRAL did not retrieve enough included references. For four out of five systematic reviews that limited to randomized controlled trials (RCTs) only, the traditional combination retrieved 100% of all included references. However, for one review of this domain, the recall was 82%. Of the 11 references included in this review, one was found only in Google Scholar and one only in Web of Science.

Percentage of systematic reviews of a certain domain for which the combination Embase, MEDLINE and Cochrane CENTRAL reached a certain recall

Reduction in number of results

We calculated the ratio between the number of results found when searching all databases, including databases not included in our analyses, such as Scopus, PsycINFO, and CINAHL, and the number of results found searching a selection of databases. See Fig.  3 for the legend of the plots in Figs.  4 and 5 . Figure  4 shows the distribution of this value for individual reviews. The database combinations with the highest recall did not reduce the total number of results by large margins. Moreover, in combinations where the number of results was greatly reduced, the recall of included references was lower.

Legend of Figs. 3 and 4

The ratio between number of results per database combination and the total number of results for all databases

The ratio between precision per database combination and the total precision for all databases

Improvement of precision

To determine how searching multiple databases affected precision, we calculated for each combination the ratio between the original precision, observed when all databases were searched, and the precision calculated for different database combinations. Figure  5 shows the improvement of precision for 15 databases and database combinations. Because precision is defined as the number of relevant references divided by the number of total results, we see a strong correlation with the total number of results.

Status of current practice of database selection

From a set of 200 recent SRs identified via PubMed, we analyzed the databases that had been searched. Almost all reviews (97%) reported a search in MEDLINE. Other databases that we identified as essential for good recall were searched much less frequently; Embase was searched in 61% and Web of Science in 35%, and Google Scholar was only used in 10% of all reviews. For all individual databases or combinations of the four important databases from our research (MEDLINE, Embase, Web of Science, and Google Scholar), we multiplied the frequency of occurrence of that combination in the random set, with the probability we found in our research that this combination would lead to an acceptable recall of 95%. The calculation is shown in Table  5 . For example, around a third of the reviews (37%) relied on the combination of MEDLINE and Embase. Based on our findings, this combination achieves acceptable recall about half the time (47%). This implies that 17% of the reviews in the PubMed sample would have achieved an acceptable recall of 95%. The sum of all these values is the total probability of acceptable recall in the random sample. Based on these calculations, we estimate that the probability that this random set of reviews retrieved more than 95% of all possible included references was 40%. Using similar calculations, also shown in Table  5 , we estimated the probability that 100% of relevant references were retrieved is 23%.

Our study shows that, to reach maximum recall, searches in systematic reviews ought to include a combination of databases. To ensure adequate performance in searches (i.e., recall, precision, and number needed to read), we find that literature searches for a systematic review should, at minimum, be performed in the combination of the following four databases: Embase, MEDLINE (including Epub ahead of print), Web of Science Core Collection, and Google Scholar. Using that combination, 93% of the systematic reviews in our study obtained levels of recall that could be considered acceptable (> 95%). Unique results from specialized databases that closely match systematic review topics, such as PsycINFO for reviews in the fields of behavioral sciences and mental health or CINAHL for reviews on the topics of nursing or allied health, indicate that specialized databases should be used additionally when appropriate.

We find that Embase is critical for acceptable recall in a review and should always be searched for medically oriented systematic reviews. However, Embase is only accessible via a paid subscription, which generally makes it challenging for review teams not affiliated with academic medical centers to access. The highest scoring database combination without Embase is a combination of MEDLINE, Web of Science, and Google Scholar, but that reaches satisfactory recall for only 39% of all investigated systematic reviews, while still requiring a paid subscription to Web of Science. Of the five reviews that included only RCTs, four reached 100% recall if MEDLINE, Web of Science, and Google Scholar combined were complemented with Cochrane CENTRAL.

The Cochrane Handbook recommends searching MEDLINE, Cochrane CENTRAL, and Embase for systematic reviews of RCTs. For reviews in our study that included RCTs only, indeed, this recommendation was sufficient for four (80%) of the reviews. The one review where it was insufficient was about alternative medicine, specifically meditation and relaxation therapy, where one of the missed studies was published in the Indian Journal of Positive Psychology . The other study from the Journal of Advanced Nursing is indexed in MEDLINE and Embase but was only retrieved because of the addition of KeyWords Plus in Web of Science. We estimate more than 50% of reviews that include more study types than RCTs would miss more than 5% of included references if only traditional combination of MEDLINE, Embase, and Cochrane CENTAL is searched.

We are aware that the Cochrane Handbook [ 7 ] recommends more than only these databases, but further recommendations focus on regional and specialized databases. Though we occasionally used the regional databases LILACS and SciELO in our reviews, they did not provide unique references in our study. Subject-specific databases like PsycINFO only added unique references to a small percentage of systematic reviews when they had been used for the search. The third key database we identified in this research, Web of Science, is only mentioned as a citation index in the Cochrane Handbook, not as a bibliographic database. To our surprise, Cochrane CENTRAL did not identify any unique included studies that had not been retrieved by the other databases, not even for the five reviews focusing entirely on RCTs. If Erasmus MC authors had conducted more reviews that included only RCTs, Cochrane CENTRAL might have added more unique references.

MEDLINE did find unique references that had not been found in Embase, although our searches in Embase included all MEDLINE records. It is likely caused by difference in thesaurus terms that were added, but further analysis would be required to determine reasons for not finding the MEDLINE records in Embase. Although Embase covers MEDLINE, it apparently does not index every article from MEDLINE. Thirty-seven references were found in MEDLINE (Ovid) but were not available in Embase.com . These are mostly unique PubMed references, which are not assigned MeSH terms, and are often freely available via PubMed Central.

Google Scholar adds relevant articles not found in the other databases, possibly because it indexes the full text of all articles. It therefore finds articles in which the topic of research is not mentioned in title, abstract, or thesaurus terms, but where the concepts are only discussed in the full text. Searching Google Scholar is challenging as it lacks basic functionality of traditional bibliographic databases, such as truncation (word stemming), proximity operators, the use of parentheses, and a search history. Additionally, search strategies are limited to a maximum of 256 characters, which means that creating a thorough search strategy can be laborious.

Whether Embase and Web of Science can be replaced by Scopus remains uncertain. We have not yet gathered enough data to be able to make a full comparison between Embase and Scopus. In 23 reviews included in this research, Scopus was searched. In 12 reviews (52%), Scopus retrieved 100% of all included references retrieved by Embase or Web of Science. In the other 48%, the recall by Scopus was suboptimal, in one occasion as low as 38%.

Of all reviews in which we searched CINAHL and PsycINFO, respectively, for 6 and 9% of the reviews, unique references were found. For CINAHL and PsycINFO, in one case each, unique relevant references were found. In both these reviews, the topic was highly related to the topic of the database. Although we did not use these special topic databases in all of our reviews, given the low number of reviews where these databases added relevant references, and observing the special topics of those reviews, we suggest that these subject databases will only add value if the topic is related to the topic of the database.

Many articles written on this topic have calculated overall recall of several reviews, instead of the effects on all individual reviews. Researchers planning a systematic review generally perform one review, and they need to estimate the probability that they may miss relevant articles in their search. When looking at the overall recall, the combination of Embase and MEDLINE and either Google Scholar or Web of Science could be regarded sufficient with 96% recall. This number however is not an answer to the question of a researcher performing a systematic review, regarding which databases should be searched. A researcher wants to be able to estimate the chances that his or her current project will miss a relevant reference. However, when looking at individual reviews, the probability of missing more than 5% of included references found through database searching is 33% when Google Scholar is used together with Embase and MEDLINE and 30% for the Web of Science, Embase, and MEDLINE combination. What is considered acceptable recall for systematic review searches is open for debate and can differ between individuals and groups. Some reviewers might accept a potential loss of 5% of relevant references; others would want to pursue 100% recall, no matter what cost. Using the results in this research, review teams can decide, based on their idea of acceptable recall and the desired probability which databases to include in their searches.

Strengths and limitations

We did not investigate whether the loss of certain references had resulted in changes to the conclusion of the reviews. Of course, the loss of a minor non-randomized included study that follows the systematic review’s conclusions would not be as problematic as losing a major included randomized controlled trial with contradictory results. However, the wide range of scope, topic, and criteria between systematic reviews and their related review types make it very hard to answer this question.

We found that two databases previously not recommended as essential for systematic review searching, Web of Science and Google Scholar, were key to improving recall in the reviews we investigated. Because this is a novel finding, we cannot conclude whether it is due to our dataset or to a generalizable principle. It is likely that topical differences in systematic reviews may impact whether databases such as Web of Science and Google Scholar add value to the review. One explanation for our finding may be that if the research question is very specific, the topic of research might not always be mentioned in the title and/or abstract. In that case, Google Scholar might add value by searching the full text of articles. If the research question is more interdisciplinary, a broader science database such as Web of Science is likely to add value. The topics of the reviews studied here may simply have fallen into those categories, though the diversity of the included reviews may point to a more universal applicability.

Although we searched PubMed as supplied by publisher separately from MEDLINE in Ovid, we combined the included references of these databases into one measurement in our analysis. Until 2016, the most complete MEDLINE selection in Ovid still lacked the electronic publications that were already available in PubMed. These could be retrieved by searching PubMed with the subset as supplied by publisher. Since the introduction of the more complete MEDLINE collection Epub Ahead of Print , In-Process & Other Non-Indexed Citations , and Ovid MEDLINE® , the need to separately search PubMed as supplied by publisher has disappeared. According to our data, PubMed’s “as supplied by publisher” subset retrieved 12 unique included references, and it was the most important addition in terms of relevant references to the four major databases. It is therefore important to search MEDLINE including the “Epub Ahead of Print, In-Process, and Other Non-Indexed Citations” references.

These results may not be generalizable to other studies for other reasons. The skills and experience of the searcher are one of the most important aspects in the effectiveness of systematic review search strategies [ 23 , 24 , 25 ]. The searcher in the case of all 58 systematic reviews is an experienced biomedical information specialist. Though we suspect that searchers who are not information specialists or librarians would have a higher possibility of less well-constructed searches and searches with lower recall, even highly trained searchers differ in their approaches to searching. For this study, we searched to achieve as high a recall as possible, though our search strategies, like any other search strategy, still missed some relevant references because relevant terms had not been used in the search. We are not implying that a combined search of the four recommended databases will never result in relevant references being missed, rather that failure to search any one of these four databases will likely lead to relevant references being missed. Our experience in this study shows that additional efforts, such as hand searching, reference checking, and contacting key players, should be made to retrieve extra possible includes.

Based on our calculations made by looking at random systematic reviews in PubMed, we estimate that 60% of these reviews are likely to have missed more than 5% of relevant references only because of the combinations of databases that were used. That is with the generous assumption that the searches in those databases had been designed sensitively enough. Even when taking into account that many searchers consider the use of Scopus as a replacement of Embase, plus taking into account the large overlap of Scopus and Web of Science, this estimate remains similar. Also, while the Scopus and Web of Science assumptions we made might be true for coverage, they are likely very different when looking at recall, as Scopus does not allow the use of the full features of a thesaurus. We see that reviewers rarely use Web of Science and especially Google Scholar in their searches, though they retrieve a great deal of unique references in our reviews. Systematic review searchers should consider using these databases if they are available to them, and if their institution lacks availability, they should ask other institutes to cooperate on their systematic review searches.

The major strength of our paper is that it is the first large-scale study we know of to assess database performance for systematic reviews using prospectively collected data. Prior research on database importance for systematic reviews has looked primarily at whether included references could have theoretically been found in a certain database, but most have been unable to ascertain whether the researchers actually found the articles in those databases [ 10 , 12 , 16 , 17 , 26 ]. Whether a reference is available in a database is important, but whether the article can be found in a precise search with reasonable recall is not only impacted by the database’s coverage. Our experience has shown us that it is also impacted by the ability of the searcher, the accuracy of indexing of the database, and the complexity of terminology in a particular field. Because these studies based on retrospective analysis of database coverage do not account for the searchers’ abilities, the actual findings from the searches performed, and the indexing for particular articles, their conclusions lack immediate translatability into practice. This research goes beyond retrospectively assessed coverage to investigate real search performance in databases. Many of the articles reporting on previous research concluded that one database was able to retrieve most included references. Halladay et al. [ 10 ] and van Enst et al. [ 16 ] concluded that databases other than MEDLINE/PubMed did not change the outcomes of the review, while Rice et al. [ 17 ] found the added value of other databases only for newer, non-indexed references. In addition, Michaleff et al. [ 26 ] found that Cochrane CENTRAL included 95% of all RCTs included in the reviews investigated. Our conclusion that Web of Science and Google Scholar are needed for completeness has not been shared by previous research. Most of the previous studies did not include these two databases in their research.

We recommend that, regardless of their topic, searches for biomedical systematic reviews should combine Embase, MEDLINE (including electronic publications ahead of print), Web of Science (Core Collection), and Google Scholar (the 200 first relevant references) at minimum. Special topics databases such as CINAHL and PsycINFO should be added if the topic of the review directly touches the primary focus of a specialized subject database, like CINAHL for focus on nursing and allied health or PsycINFO for behavioral sciences and mental health. For reviews where RCTs are the desired study design, Cochrane CENTRAL may be similarly useful. Ignoring one or more of the databases that we identified as the four key databases will result in more precise searches with a lower number of results, but the researchers should decide whether that is worth the >increased probability of losing relevant references. This study also highlights once more that searching databases alone is, nevertheless, not enough to retrieve all relevant references.

Future research should continue to investigate recall of actual searches beyond coverage of databases and should consider focusing on the most optimal database combinations, not on single databases.

Levay P, Raynor M, Tuvey D. The contributions of MEDLINE, other bibliographic databases and various search techniques to NICE public health guidance. Evid Based Libr Inf Pract. 2015;10:50–68.

Article   Google Scholar  

Stevinson C, Lawlor DA. Searching multiple databases for systematic reviews: added value or diminishing returns? Complement Ther Med. 2004;12:228–32.

Article   CAS   PubMed   Google Scholar  

Lawrence DW. What is lost when searching only one literature database for articles relevant to injury prevention and safety promotion? Inj Prev. 2008;14:401–4.

Lemeshow AR, Blum RE, Berlin JA, Stoto MA, Colditz GA. Searching one or two databases was insufficient for meta-analysis of observational studies. J Clin Epidemiol. 2005;58:867–73.

Article   PubMed   Google Scholar  

Zheng MH, Zhang X, Ye Q, Chen YP. Searching additional databases except PubMed are necessary for a systematic review. Stroke. 2008;39:e139. author reply e140

Beyer FR, Wright K. Can we prioritise which databases to search? A case study using a systematic review of frozen shoulder management. Health Inf Libr J. 2013;30:49–58.

Higgins JPT, Green S. Cochrane handbook for systematic reviews of interventions: The Cochrane Collaboration, London, United Kingdom. 2011.

Wright K, Golder S, Lewis-Light K. What value is the CINAHL database when searching for systematic reviews of qualitative studies? Syst Rev. 2015;4:104.

Article   PubMed   PubMed Central   Google Scholar  

Wilkins T, Gillies RA, Davies K. EMBASE versus MEDLINE for family medicine searches: can MEDLINE searches find the forest or a tree? Can Fam Physician. 2005;51:848–9.

PubMed   Google Scholar  

Halladay CW, Trikalinos TA, Schmid IT, Schmid CH, Dahabreh IJ. Using data sources beyond PubMed has a modest impact on the results of systematic reviews of therapeutic interventions. J Clin Epidemiol. 2015;68:1076–84.

Ahmadi M, Ershad-Sarabi R, Jamshidiorak R, Bahaodini K. Comparison of bibliographic databases in retrieving information on telemedicine. J Kerman Univ Med Sci. 2014;21:343–54.

Google Scholar  

Lorenzetti DL, Topfer L-A, Dennett L, Clement F. Value of databases other than MEDLINE for rapid health technology assessments. Int J Technol Assess Health Care. 2014;30:173–8.

Beckles Z, Glover S, Ashe J, Stockton S, Boynton J, Lai R, Alderson P. Searching CINAHL did not add value to clinical questions posed in NICE guidelines. J Clin Epidemiol. 2013;66:1051–7.

Hartling L, Featherstone R, Nuspl M, Shave K, Dryden DM, Vandermeer B. The contribution of databases to the results of systematic reviews: a cross-sectional study. BMC Med Res Methodol. 2016;16:1–13.

Aagaard T, Lund H, Juhl C. Optimizing literature search in systematic reviews—are MEDLINE, EMBASE and CENTRAL enough for identifying effect studies within the area of musculoskeletal disorders? BMC Med Res Methodol. 2016;16:161.

van Enst WA, Scholten RJ, Whiting P, Zwinderman AH, Hooft L. Meta-epidemiologic analysis indicates that MEDLINE searches are sufficient for diagnostic test accuracy systematic reviews. J Clin Epidemiol. 2014;67:1192–9.

Rice DB, Kloda LA, Levis B, Qi B, Kingsland E, Thombs BD. Are MEDLINE searches sufficient for systematic reviews and meta-analyses of the diagnostic accuracy of depression screening tools? A review of meta-analyses. J Psychosom Res. 2016;87:7–13.

Bramer WM, Giustini D, Kramer BM, Anderson PF. The comparative recall of Google Scholar versus PubMed in identical searches for biomedical systematic reviews: a review of searches used in systematic reviews. Syst Rev. 2013;2:115.

Bramer WM, Giustini D, Kramer BMR. Comparing the coverage, recall, and precision of searches for 120 systematic reviews in Embase, MEDLINE, and Google Scholar: a prospective study. Syst Rev. 2016;5:39.

Ross-White A, Godfrey C. Is there an optimum number needed to retrieve to justify inclusion of a database in a systematic review search? Health Inf Libr J. 2017;33:217–24.

Bramer WM, Rethlefsen ML, Mast F, Kleijnen J. A pragmatic evaluation of a new method for librarian-mediated literature searches for systematic reviews. Res Synth Methods. 2017. doi: 10.1002/jrsm.1279 .

Bramer WM, de Jonge GB, Rethlefsen ML, Mast F, Kleijnen J. A systematic approach to searching: how to perform high quality literature searches more efficiently. J Med Libr Assoc. 2018.

Rethlefsen ML, Farrell AM, Osterhaus Trzasko LC, Brigham TJ. Librarian co-authors correlated with higher quality reported search strategies in general internal medicine systematic reviews. J Clin Epidemiol. 2015;68:617–26.

McGowan J, Sampson M. Systematic reviews need systematic searchers. J Med Libr Assoc. 2005;93:74–80.

PubMed   PubMed Central   Google Scholar  

McKibbon KA, Haynes RB, Dilks CJW, Ramsden MF, Ryan NC, Baker L, Flemming T, Fitzgerald D. How good are clinical MEDLINE searches? A comparative study of clinical end-user and librarian searches. Comput Biomed Res. 1990;23:583–93.

Michaleff ZA, Costa LO, Moseley AM, Maher CG, Elkins MR, Herbert RD, Sherrington C. CENTRAL, PEDro, PubMed, and EMBASE are the most comprehensive databases indexing randomized controlled trials of physical therapy interventions. Phys Ther. 2011;91:190–7.

Download references

Acknowledgements

Not applicable

Melissa Rethlefsen receives funding in part from the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UL1TR001067. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available from the corresponding author on a reasonable request.

Author information

Authors and affiliations.

Medical Library, Erasmus MC, Erasmus University Medical Centre Rotterdam, 3000 CS, Rotterdam, the Netherlands

Wichor M. Bramer

Spencer S. Eccles Health Sciences Library, University of Utah, Salt Lake City, Utah, USA

Melissa L. Rethlefsen

Kleijnen Systematic Reviews Ltd., York, UK

Jos Kleijnen

School for Public Health and Primary Care (CAPHRI), Maastricht University, Maastricht, the Netherlands

Department of Epidemiology, Erasmus MC, Erasmus University Medical Centre Rotterdam, Rotterdam, the Netherlands

Oscar H. Franco

You can also search for this author in PubMed   Google Scholar

Contributions

WB, JK, and OF designed the study. WB designed the searches used in this study and gathered the data. WB and ML analyzed the data. WB drafted the first manuscript, which was revised critically by the other authors. All authors have approved the final manuscript.

Corresponding author

Correspondence to Wichor M. Bramer .

Ethics declarations

Ethics approval and consent to participate, consent for publication, competing interests.

WB has received travel allowance from Embase for giving a presentation at a conference. The other authors declare no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Additional files

Additional file 1:.

Reviews included in the research . References to the systematic reviews published by Erasmus MC authors that were included in the research. (DOCX 19 kb)

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Cite this article.

Bramer, W.M., Rethlefsen, M.L., Kleijnen, J. et al. Optimal database combinations for literature searches in systematic reviews: a prospective exploratory study. Syst Rev 6 , 245 (2017). https://doi.org/10.1186/s13643-017-0644-y

Download citation

Received : 21 August 2017

Accepted : 24 November 2017

Published : 06 December 2017

DOI : https://doi.org/10.1186/s13643-017-0644-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Databases, bibliographic
• Review literature as topic
• Sensitivity and specificity
• Information storage and retrieval

Systematic Reviews

ISSN: 2046-4053

• Submission enquiries: Access here and click Contact Us
• General enquiries: [email protected]

Librarians/Admins

• EBSCOhost Collection Manager
• EBSCO Experience Manager
• EBSCO Connect
• Start your research
• EBSCO Mobile App

Clinical Decisions Users

• DynaMed Decisions
• Dynamic Health
• Waiting Rooms
• NoveList Blog

Why You Need Library Databases for Research

Yavapai College Libraries in Arizona created a short video promoting the importance of using databases instead of commercial search engines when conducting research. The narrator, “Bud,” asks viewers to think critically about what they are searching when they use the Web to find information. The Web, he says, provides free access to what companies and people have made available to the public. He reminds viewers that anyone can create a web page, whether they are a subject expert or not, and no one is policing the Internet. In addition, he says, search engines offer few options for narrowing results.

On the other hand, research databases offer users access to thousands of books, magazine articles, images, charts and primary sources. These databases contain scholarly and peer-reviewed articles written by credible authors, such as journalists, researchers and experts in their field. Since databases provide powerful search tools for narrowing results, users are able to more quickly find the information they need.

Related Posts

What is a Research Databases?

In the ever-evolving world of academia and research, staying ahead of the curve requires unfettered access to a vast wealth of knowledge.

As researchers, students, and knowledge-seekers, we strive to uncover groundbreaking insights, delve into the depths of human understanding, and contribute to the expanding boundaries of human intellect.

Amid this pursuit of knowledge, research databases stand as the unsung heroes, providing us with the key to unlocking the gates of an information goldmine.

In this digital age, the internet has transformed the way we access information, and research databases have emerged as the foundational pillars of academic exploration.

Offering a treasure trove of scholarly resources, these virtual repositories are meticulously curated to cater to the unique needs of researchers from diverse disciplines.

From peer-reviewed articles and conference proceedings to patents and historical archives, research databases are the beacons guiding us through the labyrinth of academic literature.

Join us as we embark on an illuminating journey to unravel the power of research databases. In this blog post, we will explore what research databases are, their vital role in supporting academic endeavors, and the remarkable advantages they present to the enquiring minds of the scholarly community.

Whether you are a seasoned researcher seeking a more efficient way to navigate through the sea of publications or a student eager to hone your skills in literature review, this blog will serve as your compass, pointing you towards the invaluable resources that lie just a few clicks away.

Step into the realm of research databases, where knowledge knows no bounds, and discoveries await those with the curiosity to seek them.

Let us dive into this digital realm of information and harness the potential that research databases hold in reshaping the future of knowledge acquisition and creation.

What is a research database?

A research database is a structured collection of digital information and resources that are specifically designed to support academic and scholarly research. These databases gather and organize a wide range of materials, such as academic journals, research papers, conference proceedings, books, theses, patents, and more, making it easier for researchers to access and retrieve relevant information on a particular topic.

Research databases play a crucial role in the academic community, as they provide a centralized and organized repository of high-quality, peer-reviewed, and reliable sources that researchers can use to find literature related to their research interests. These databases are typically accessible through online platforms and are searchable using various criteria, including keywords, author names, publication dates, and more.

What are the benefits of using research databases?

The benefits of using research databases include:

1. Comprehensive Coverage

Databases often cover a broad range of disciplines, making it easier to find information across different fields.

2. Peer-reviewed Content

Many databases only include content that has undergone rigorous peer review, ensuring the reliability and quality of the sources.

3. Reliable resources

4. searchability.

Databases offer advanced search features that allow researchers to narrow down their search and find highly relevant materials quickly.

5. Citation Information

Databases often provide citation details for each source, making it easier for researchers to properly cite and reference the works they use.

6. Access to Full Text

Many databases provide direct access to full-text articles, reducing the need to go through multiple websites or paywalls.

Some examples of well-known research databases include PubMed, Scopus, Web of Science, IEEE Xplore Digital Library, JSTOR, and Google Scholar.

Researchers, students, and academics often rely on research databases to stay up-to-date with the latest advancements in their fields, conduct literature reviews, and gather evidence for their research projects.

Related Guides

• A Comprehensive Review of SAGE Journals Database
• RePEc (Research Papers in Economics) Database Review
• Scopus : Navigating the Vast Scholarly Landscape
• DOAJ (Directory of Open Access Journals) : All You Need to Know
• EBSCO Databases

• TutorHome |
• IntranetHome |
• Contact the OU Contact the OU Contact the OU |
• Accessibility Accessibility
• StudentHome
• Help Centre

You are here

Help and support.

• Getting started with the online library
• Understanding databases
• Site Accessibility: Library Services

A database is a bit like an online catalogue where information is stored in a structured way.

The OU library has a collection of over five hundred different databases. They more than just journal articles and books. Some databases also house resources like images, newspapers and music.

While certain databases like Academic Search Complete cover a broad range of topics, others are specifically tailored to particular subjects.

The  Databases  page of the library website contains the complete list of databases provided by the OU Library.

The  Selected resources for your study  page lists the recommended ones for each subject area.

Reasons for using library databases

• Comprehensive search : databases allow you to search for information from a variety of sources, enabling you to access a wide range of materials.
• Full text access : many databases provide access to the complete text of books and journal articles, giving you an opportunity to delve deeper into your research.
• Academic standard:  the information you find in databases meets high academic standards, ensuring its reliability and relevance to your studies.

Searching for information in library databases

You can use  Library Search  to search across most of our main databases all at once. Making it a convenient starting point for your research. 

Alternatively you can search within each subject database separately. In general, searching within a subject database will retrieve fewer but more relevant results.

Most databases offer advanced search tools that enable you to refine your search criteria and obtain precise results.  Learning these advanced search techniques is an academic skill that takes time to develop. The Finding resources for your assignment page provides useful activities to help you learn these skills.

Try it for yourself

• Think of a subject that interests you.
• Search for that subject on  Library Search  to find information from a range of different databases.
• Now search for the same topic within  Academic Search Complete , which is a large, multi-disciplinary database. 
• Frequently Asked Questions
• Understanding ebooks
• Understanding ejournals
• Understanding articles
• Disabled user support
• Finding resources for your assignment
• Finding ejournals and articles
• Access eresources using Google Scholar
• Help with online resources
• Finding and using books and theses
• Finding information on your research topic
• Referencing and plagiarism
• Training and skills
• Study materials
• Using other libraries and SCONUL Access
• Borrowing at the Walton Hall Library
• OU Glossary
• Contacting the helpdesk

Smarter searching with library databases

Thursday, 9 May, 2024 - 20:30

Learn how to access library databases, take advantage of the functionality they offer, and devise a proper search technique.

Library Helpdesk

Chat to a Librarian  - Available 24/7

Other ways to contact the Library Helpdesk

The Open University

• Study with us
• Supported distance learning
• Funding your studies
• International students
• Global reputation
• Apprenticeships
• Develop your workforce
• News & media
• Contact the OU

Undergraduate

• Arts and Humanities
• Art History
• Business and Management
• Combined Studies
• Computing and IT
• Counselling
• Creative Writing
• Criminology
• Early Years
• Electronic Engineering
• Engineering
• Environment
• Film and Media
• Health and Social Care
• Health and Wellbeing
• Health Sciences
• International Studies
• Mathematics
• Mental Health
• Nursing and Healthcare
• Religious Studies
• Social Sciences
• Social Work
• Software Engineering
• Sport and Fitness

Postgraduate

• Postgraduate study
• Research degrees
• Masters in Art History (MA)
• Masters in Computing (MSc)
• Masters in Creative Writing (MA)
• Masters degree in Education
• Masters in Engineering (MSc)
• Masters in English Literature (MA)
• Masters in History (MA)
• Master of Laws (LLM)
• Masters in Mathematics (MSc)
• Masters in Psychology (MSc)
• A to Z of Masters degrees
• Accessibility statement
• Conditions of use
• Privacy policy
• Cookie policy
• Manage cookie preferences
• Modern slavery act (pdf 149kb)

Follow us on Social media

• Student Policies and Regulations
• Student Charter
• System Status
• Contact the OU Contact the OU
• Modern Slavery Act (pdf 149kb)

© . . .

Research Tutorial

• Introduction
• Understanding Your Assignment
• Developing Key Term from Your Topic
• Creating Searches
• Searching the Library Catalog
• Finding Books on the Shelf
• The Call Number System

What Are Databases?

• Accessing Databases
• Off Campus Access
• Choosing a Database
• The Mechanics of Searching
• Finding Websites
• Evaluating Websites
• What Every Citation Needs
• Citation Formats
• Making the Databases Work for You
• Resources for Citation Formats

In the context of libraries and doing research, the generally accepted definition of a database is "an electronic collection of searchable information on one or more topics."

Right. So we ask again, what are databases?

Think of databases as penned up corners of the Internet, sections that have been fenced off and locked, so that a regular Internet search (say, searching Google) won't find what's inside. And of course, it's behind this fence that most of the good information for doing academic research sits.

Why do they make this stuff hard to get to?

Unfortunately, like many things, it comes down to money. The companies who publish academic journals, magazines, and newspapers (all types of material you will find in these databases) need to make money. The people who digitize the content and create the search platforms need to make money. So they restrict access to the database by making them available through subscriptions.

So where does that leave you, the researcher?

With the library, of course!

One of the biggest roles that an academic library plays (and, not inconsequentially, where a large portion of the library's budget goes!) is in providing access to these databases. The library is your key through those locked gates. So rather than going to Google to try to find an academic journal article, come to the library's web page. We know the secret codes to get you in.

• << Previous: Databases: An Introduction
• Next: Accessing Databases >>
• Last Updated: Dec 19, 2023 2:36 PM
• URL: https://libguides.hartford.edu/ResearchTutorial

A-Z Site Index | Contact Us | Directions | Hours | Get Help

University of Hartford | 200 Bloomfield Avenue, West Hartford, CT 06117 Harrison Libraries © 2020 | 860.768.4264

Use of databases for clinical research

• PMID: 24489362
• DOI: 10.1136/archdischild-2013-304466

Databases are electronic filing systems that have been set up to capture patient data in a variety of clinical and administrative settings. While randomised controlled trials are the gold standard for the evaluation of healthcare interventions, electronic databases are valuable research options for studies of aetiology and prognosis, or where trials are too expensive/not logistically feasible. However, databases exist in many different settings and formats (often developed for administrative or financial reimbursement purposes rather than clinical research), and researchers need to put careful thought into identifying and acquiring relevant data sets. Accuracy of records and validation of diagnoses are key issues when planning a database study. High-quality databases can readily capture outcome data (as part of routine clinical care) without the costs and burden of additional trial-related follow-up, and there are promising hybrid models which combine the benefits of randomisation with the efficiency of outcome ascertainment using existing databases.

Keywords: Evidence Based Medicine; Health Service; Information Technology; Outcomes Research.

Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Publication types

• Biomedical Research / methods*
• Databases, Factual*

• ELEMENTARY SCHOOLS
• Alice West Fleet
• Arlington Science Focus
• Arlington Traditional
• Carlin Springs
• Hoffman-Boston
• Integration Station
• Long Branch
• MIDDLE SCHOOLS
• Dorothy Hamm
• Williamsburg
• HIGH SCHOOLS & PROGRAMS
• Arlington Career Center
• Arlington Tech
• Arlington Community High School

H-B Woodlawn

• Washington-Liberty
• DISTRICT SITE

Home » Library Home » Research » Why Use Databases?

Why Use Databases?

How to Access H-B’s Databases

Databases contain many professionally researched, copyrighted resources that were originally published in print.

Like most databases, the Gale databases provide a citation you can use in your bibliography as well as a link (a stable URL) that is useful to providing a location for the source.  You can select an MLA or APA citation to paste into your bibliography.

Librarians recommend trying library databases for most topics of research rather than searching the wide open internet.  Skillful database use is extremely important for anyone who wishes to advance their research skills beyond “Elementary School” level.  Let’s face it– by middle school, students have been conducting Google searches for years.  They end up with results that may include advertisements, inappropriate materials, and fake news– all of which can misinform, waste time, and even potentially endanger students who are not always internet-savvy or cyber-safe.

Using the library’s databases…

• speeds scholarly research
• elevates the quality of the information and detail being gathered for almost all scholarly topics
• provides access to professionally written articles, books, video content, images, primary sources, literature, and timelines that have already been curated, edited and organized by scholarly professionals.  Several databases such as Gale even recommend free, web-based resources that have been carefully selected for usefulness (for example, radio programming, podcasts and videos.)  Databases are expensive, information “gold mines” where students can spend less time worrying about whether the sources are credible/authoritative or not . . . and get straight to their information.
• develops in students the habit of seeking and respecting information expertise rather than relying on wide open internet where anyone’s ideas, whether fact-based or not can be distributed.
• provides citations for the resources they house… often in MLA and APA styles.  Those citations can be easily exported into NoodleTools or copied and pasted into Google Docs. Their ease of use saves students time and encourages the development of academic integrity.
• provides habit-building practice necessary for college preparation. University professors expect their students to arrive with experience in using scholarly databases for research as well as respect for information expertise.
• enable “advanced searches” that further students’ understanding of how information is searched and tagged in scholarly environments.  Advanced searching allows the student to combine terms and filter out resources that get in the way of their progress.  In the Information Age, the research challenge is often related to “Info-Whelm.”  The tidal wave of resource “hits” that result from Google searches overwhelms most young researchers who (research shows) often peruse only the first couple resources in the search results.  They do not know that these are often biased, sponsored sites or even popular “hoax” sites listed up top only because they get frequent hits. A skilled search in a database can result in a much more manageable set of search results. Databases are an important means that schools use to guard against cyber-predators motivated by commercial interests and political agendas.
• provide resources to multiple users at the same time, 24/7.   So collaborative project work is easier than when you have to share print resources that might not get returned quickly to the library.  Teachers can assign reading an article to the whole class and they need not print out copies.
• provides access to copyrighted materials, most of which may not be freely available on the Internet. Being aware of which database to explore first helps, and librarians facilitate a developing awareness of resources with use of Research Guides that they publish… often at their web sites, just as college libraries provide.   (Exceptions may apply for students researching technology, sports, celebrity news, entertainment, and breaking news.  Read on…)

Are there times when searching the wide open internet is recommended instead of databases? Absolutely!   Librarians want students to be critically thoughtful about the TYPE of information that they need.  Doing a Google Search is usually the fastest method to obtaining…

• breaking news
• maps/directions or an organization’s membership info and forms
• utilizing publicly provided databases (for example, library catalogs and publications of the National Institutes of Health, Council on Foreign Relations (a think tank) or the Library of Congress.  We often recommend specific sites at our Research Guides .)
• ticketing information for public events
• contact information or press releases (for example: HBW’s homepage, governmental agencies such as the DMV)
• celebrity gossip
• sports updates
• social media (such as Facebook) for communication, advocacy and entertainment where amateurs help author materials
• blogs for opinion pieces and insight on personal experiences
• YouTube and broadcasting web pages for entertainment and “how to” tutorials
• Twitter for alerts and rants.

For long term scholarly research projects, it’s quite possible that the information savvy student might make use of any of the above for detailed support for her work.

Teacher Tip: How to share database resources with students and collaborators .)

Dr. Casey Robinson, Principal

1601 Wilson Blvd.

Arlington, VA 22209

Phone: 703-228-6363

Fax: 703-528-5073

• Galvin Library

Biomedical Engineering

• Why Use a Research Database?
• Research Papers and Journal Articles
• Data & Properties
• Codes & Standards
• Product Information
• Resources for Alumni & Others

Why Use a Research Database Instead of Google or Google Scholar?

Why use a research database instead of library search, research tools at galvin library.

• Search Tips and Tricks for Reserch Databases
• Avoid Research Misconduct

Despite their learning curve, there are a number of compelling reasons for using a research database rather than Google or Google Scholar.

• This allows you to zero in on exactly those research papers you need without having to wade through countless irrelevant results or miss essential papers because you didn't choose the right keywords.
• This helps by removing a large number of irrelevant, off-topic results and focusing your search only in the areas of study that you're interested in.
• For example, in a psychology or medical database, you can specifically limit your search to studies or clinical trials concerning a particular population group or age group.
• Research databases carefully evaluate the resources they index to ensure that they are of the highest quality.

Library Search is best for finding general background information on topics--especially books--or for undergraduate students seeking resources for their 100 and 200 level classes. While it provides many benefits over searching Google or Google Scholar, it cannot compete with using a specialized research database for upper level undergraduate, graduate, or post-graduate level research. The reasons are similar to those for choosing research databases over Google.

• Research databases use controlled vocabulary. Library Search does not, so it suffers from the same limits to precision and recall as web search engines.
• Because of the subject specialization, the controlled vocabulary in the specialized databases is usually highly specialized to reflect the needs of that particular area of study.
• Library Search does NOT search all materials to which you have access as a member of the Illinois Tech community. The most useful or important papers for your topic may not be findable using Library Search. This is more often true of highly specialized papers in the sciences and engineering than for other areas of research or study.
• Artificial Intelligence (AI) by IIT Galvin Library Last Updated Mar 6, 2024 544 views this year
• Citation Management by IIT Galvin Library Last Updated Dec 21, 2023 38 views this year
• Citing Sources by IIT Galvin Library Last Updated Jan 29, 2024 143 views this year
• Finding and Using Books from Galvin Library by IIT Galvin Library Last Updated Mar 21, 2024 114 views this year
• Finding Media by IIT Galvin Library Last Updated Dec 15, 2023 142 views this year
• Going Beyond Google by IIT Galvin Library Last Updated Dec 21, 2023 159 views this year
• How To Do Secondary Research or a Literature Review by IIT Galvin Library Last Updated Dec 21, 2023 2705 views this year
• Introduction to Responsible Conduct of Research or RCR by IIT Galvin Library Last Updated Jan 16, 2024 67 views this year
• Library Search User Guide by Charles W. Uth Last Updated Jan 16, 2024 194 views this year
• Predatory Publishing by IIT Galvin Library Last Updated Jan 26, 2024 12 views this year
• Research Basics by IIT Galvin Library Last Updated Dec 21, 2023 1759 views this year
• Zotero by IIT Galvin Library Last Updated Dec 21, 2023 1943 views this year
• << Previous: Resources for Alumni & Others
• Next: Search Tips and Tricks for Reserch Databases >>
• Last Updated: Mar 25, 2024 9:39 AM
• URL: https://guides.library.iit.edu/biomedicalengineering

clock This article was published more than  1 year ago

What research shows on the effectiveness of gun-control laws

“When we passed the assault weapons ban, mass shootings went down. When the law expired, mass shootings tripled.”

— President Biden, addressing the mass shooting in Uvalde, Tex. , May 24

“There are, quote, ‘real’ gun laws in New York. There are ‘real’ gun laws in California. I hate to say this, but there are more people who were shot every weekend in Chicago than there are in schools in Texas.”

— Tex. Gov. Greg Abbott (R), on the mass shooting , May 25

Democrats and Republicans will forever argue about the effectiveness of gun laws to prevent mass shootings. But what does the latest academic research show?

The short answer is that many proposed laws probably would not have much impact on curbing the mass shootings that dominate the news. But they could lessen their severity, and might also bring down overall gun violence.

Despite their notoriety, mass shootings — as defined by criminologists — generally do not happen often enough for detailed data analysis. Moreover, there are at least eight databases of mass shootings , including one maintained by The Washington Post , with different definitions and parameters. An upcoming paper for the Justice Department, written by a team led by James Alan Fox of Northeastern University , Grant Duwe of the Minnesota Department of Corrections and Michael Rocque of Bates College , attempts to craft a common definition: A mass public shooting is any event in which four or more individuals, not including the assailant(s), were killed by gunfire in a public setting within a 24-hour period. Mass shootings associated with criminal activity are excluded.

Under this definition, there were three or four mass shootings a year through most of the 2010s, but then the number spiked to seven in 2017, 10 in 2018 and eight in 2019, according to the database, provided to the Fact Checker by Duwe.

The team, drawing on the existing databases and supplemental research, found that “the number of mass public shootings has indeed increased over the past four and one-half years, particularly over the past decade. However, even at its peak in 2018, the number of such incidents has not surpassed ten in any year, and often has been much lower.” Moreover, some of the increase can be linked to growth in population. The incident count tripled since the mid-1970s but the rate per 100 million of population increased by a factor of two.

Fox told the Fact Checker that most mass shooters are very determined individuals and that even with an average of seven or eight mass shootings a year, new laws might only reduce the number by one a year. But he said stricter gun control laws would be “the right thing to do for a different reason” — they might help reduce overall gun violence.

While it is generally correct that states with tougher gun laws tend to have lower gun fatality rates, those rankings change when suicides — which make up about 60 percent of gun deaths — are excluded. Rural areas, which may have less restrictive gun laws, have a lot of suicides of older single men who become lonely. Access to guns is believed to triple the risk of suicide, according to a 2014 study. But Fox said he would exclude suicides from such calculations. “There is a big difference between homicide and suicide,” he said. “The victim of a homicide does not choose to be killed.”

Here’s a summary of key research on the effectiveness of various laws, either at the federal or state level.

Assault weapons ban

In 1994, President Bill Clinton signed into law a ban on assault weapons and large-capacity magazines (LCMs), defined as those that could hold more than 10 rounds. The law — which grandfathered in an estimated 1.5 million assault weapons and 25 million LCMs already owned by Americans — was in place for 10 years until Congress let it lapse.

Even supporters of the law have acknowledged that it was riddled with loopholes, such as allowing copycat weapons to be sold, that limited its effectiveness. Some research, however, suggests the ban became more effective toward the end of the 10-year period because it helped cap and then reduce the supply of assault weapons and LCMs.

Biden claimed that mass shooting deaths tripled after the law expired. He appears to be relying on a study of mass shooting data from 1981 to 2017, published in 2019 in the Journal of Trauma and Acute Care Surgery by a team led by Charles DiMaggio , a professor of surgery at New York University’s Langone Medical Center. That group found that an assault weapons ban would have prevented 314 out of 448, or 70 percent, of the mass shooting deaths during the years when the ban was not in effect. But the data used in that study has come under attack by some analysts.

Meanwhile, Louis Klarevas , a research professor at Teachers College at Columbia University, studied high-fatality mass shootings (involving six or more people) for his 2016 book “ Rampage Nation .” He said that compared with the 10-year period before the ban, the number of gun massacres during the ban period fell by 37 percent and that the number of people dying because of mass shootings fell by 43 percent. But after the ban lapsed in 2004, the numbers in the next 10-year period rose sharply — a 183 percent increase in mass shootings and a 239 percent increase in deaths. His analysis, however, has been criticized by some experts for being heavily impacted by the final year of his data series.

Correlation does not necessarily equal causation, moreover. Fox, in a 2016 study co-written with Emma Fridel of Northeastern University, noted that “rather than assault weapons, semiautomatic handguns are the weapons of choice for most mass shooters.” (About 70 percent of mass public shootings after 1992 relied exclusively or primarily on semiautomatic handguns.) They wrote that “the frequency of incidents was virtually unchanged during the decade when the ban was in effect” and that “not only were there countless assault weapons already on the street, but also assailants had a variety of other powerful firearms at their disposal.”

The new mass-shooting database shows that there were 31 mass shootings in the decade before the 1994 law, 31 in the 10 years the law was in force (Sept. 13, 1994 to Sept. 12, 2004) and 47 in the 10 years after it expired. As noted, some of that increase stems from population growth.

Large-capacity magazines

While the assault weapons ban may not have reduced the number of mass shootings, there is some evidence that the 1994 law’s restrictions on LCMs may have been effective in reducing the death toll.

Christopher S. Koper , an associate professor of criminology at George Mason University, said in a 2020 study that LCMs enable rapid spray fire that gives shooters the ability to wound higher numbers of victims in public settings. So restrictions on LCMs can have an effect.

“Data on mass shooting incidents suggest these magazine restrictions can potentially reduce mass shooting deaths by 11 percent to 15 percent and total victims shot in these incidents by one quarter, likely as upper bounds,” Koper wrote, adding, “It is reasonable to argue that the federal ban could have prevented some of the recent increase in persons killed and injured in mass shootings had it remained in place.”

Moreover, a number of studies of state-level bans on LCMs, such as by Mark Gius of Quinnipiac University and by Klarevas , indicate that such laws are associated with a significantly lower number of fatalities in mass shootings. Fox co-wrote a 2020 study of state gun laws that concluded that bans on LCMs are associated with 38 percent fewer fatalities and 77 percent fewer nonfatal injuries when a mass shooting occurred.

But even states such as California, which outlaws LCMs that hold more than 10 bullets, have suffered from mass shootings that involved LCMs. When Syed Farook and Tashfeen Malik killed 14 people in San Bernardino, Calif., in 2015 with legally purchased guns and rifles, four high-capacity magazines were found, perhaps holding as many as 30 rounds. Many mass shooters also acquire a large inventory of weapons, making reloading less necessary.

Universal background checks

There is evidence that universal background checks — including between private parties — could have an impact on mass shootings. State laws requiring a permit to purchase a firearm, which includes a background check on all purchases, are associated with 60 percent lower odds of a mass public shooting occurring, Fox’s 2020 study found.

But most mass murderers legally purchase the firearms they use in their killing sprees. Salvador Ramos, identified by police as the gunman who killed 19 children and two teachers in Uvalde, purchased two AR-15 semiautomatic rifles and ammunition as soon as he turned 18. He had never been convicted of a felony or had a history of criminal violence, so there was no prohibition against him buying the weapons.

The current system also fails. In 2015, Dylann Roof killed nine people with a .45-caliber Glock pistol that held 13 rounds at a historic African American church in Charleston, S.C. Roof legally purchased his gun from a store, but the FBI said he should have failed the background check because he had been charged with possessing Suboxone without a prescription. However, because of clerical mistakes, the FBI said the examiner did not get hold of the report before the three-day waiting period ended, and so the store went through with the purchase.

This three-day period has become known as the “Charleston loophole” that some lawmakers have sought to close. But it’s possible Roof might have passed the background check if it had been done correctly. The FBI statement incorrectly referred to a felony drug charge, but it was a misdemeanor for possession; he did not admit to being an addict. The FBI later said Roof would have been denied a gun based on an “inference of current use.”

Firearms prohibitions based on mental health

Anyone who slaughters innocent people with firearms in theory would be expected to have mental health issues. But most people who have mental health issues are not killers; in fact, they are more likely to be victims of gun violence. Nearly one in five adults in the United States live with a mental illness , according to the National Institute of Mental Health , while epidemiological research suggests that nearly half the U.S. population may experience some symptoms of mental illness in their lifetime.

That makes it difficult to know when to draw the line, especially because mental illness is not a predictor of violence. “Databases that track gun homicides, such as the National Center for Health Statistics, similarly show that fewer than 5 percent of the 120,000 gun-related killings in the United States between 2001 and 2010 were perpetrated by people diagnosed with mental illness,” noted Jonathan Metzl and Kenneth MacLeish of Vanderbilt University in a 2016 study . They said that other factors, such as alcohol and drug use, may increase the risk of turning toward violent crime even more. A history of childhood abuse is also considered a predictive risk factor.

Red-flag (“extreme risk”) laws — which generally allow police to take firearms away from people who exhibit concerning behavior — have been passed in 19 states and the District of Columbia, according to Everytown for Gun Safety, which advocates for gun-control laws. Between 1999 and 2021, at least 16,857 extreme risk petitions were filed, the group says. Florida, which passed such a law after the Marjory Stoneman Douglas High School shooting in 2018, has used it 6,000 times since then. A 2019 study found that as many as 21 mass shootings might have been prevented in California after the state in 2016 implemented such a law.

Yet New York’s red-flag law was not invoked against Payton Gendron, the suspect in the racist attack in Buffalo this month that left 10 people dead. He had said in school he planned to commit a murder-suicide and was taken to a hospital for a mental health evaluation. Police chose not to seek a red-flag order, apparently because he did not name a specific target. New York’s governor has since signed an executive order seeking to strengthen the law.

( About our rating scale )

Send us facts to check by filling out this form

Sign up for The Fact Checker weekly newsletter

The Fact Checker is a verified signatory to the International Fact-Checking Network code of principles

Why Idaho prosecutors won’t charge man who shouted racist slur at Utah women’s basketball team

The incident occurred during the ncaa tournament, leaving members of the utes distraught..

(Young Kwak | AP) Utah head coach Lynne Roberts watches during the first half of a second-round college basketball game against Gonzaga in the NCAA Tournament in Spokane, Wash., Monday, March 25, 2024.

An 18-year-old Idaho man who officials say admitted to shouting a racist slur at members of the University of Utah women’s basketball team will not be charged with a crime.

After two months of investigating the incident that took place during the opening weekend of the NCAA Tournament, city attorneys in Coeur d’Alene, Idaho, decided last week not to prosecute the man based on a lack of probable cause and the potential violation of his constitutional right to free speech.

The man, a student at a Coeur d’Alene high school, admitted to shouting the N-word and a sexually explicit comment from a car as the Utes players walked nearby, according to a charging decision document obtained by The Salt Lake Tribune.

The incident, which took place on March 21 as Utah was preparing for a tournament game against Gonzaga, was captured on surveillance video.

On May 3, Coeur d’Alene Chief Deputy City Attorney Ryan Hunter wrote that the city attorney’s office considered charging the man with disturbing the peace, disorderly conduct and malicious harassment. But the document stated there was “insufficient evidence” that the man “acted with a specific intent to intimidate or harass any specific person.”

“[O]n the contrary, the sum of the evidence supports that [his] intent was to be funny,” Hunter wrote.

Hunter also concluded that the man’s conduct didn’t rise to the level of pursuing prosecution for the other two charges. He also wrote that the man’s comment and use of the N-word could not “meet the legal requirements for any of the narrow categories of unprotected speech.”

“Our office shares in the outrage sparked by [the accused’s] abhorrently racist and misogynistic statement, and we join in unequivocally condemning that statement and the use of a racial slur in this case, or in any circumstance,” Hunter wrote. “However, that cannot, under current law, form the basis for criminal prosecution in this case.”

The Tribune is not identifying the 18-year-old man as he has not been criminally charged.

Coeur d’Alene police’s investigation into the incident did not match up exactly with initial reports of the night.

A few hours after the incident, Robert Moyer, a university donor, reported it to a police officer, per body cam footage obtained by The Tribune. Moyer said people in trucks revving their engines shouted the N-word at the team and the traveling party as they went to dinner.

“It was aggressive,” Moyer said. “It wasn’t passive. It was like they were having fun f---ing with us.”

The charging decision document states video surveillance shows three trucks making “significant noise while accelerating,” but that it wasn’t during the time the Utah contingent was walking into the restaurant. The document also states there is no audio evidence that suggests people inside those trucks said the N-word during that time.

On March 25, Utes coach Lynne Roberts first made the allegations public, saying her team experienced “racial hate crimes” while staying in Coeur d’Alene, which is more than 30 minutes from Spokane, Washington, where the first two rounds of the tournament were being held.

Roberts said the incident caused the team to change hotels, and called it “a distraction and upsetting and unfortunate.”

Donate to the newsroom now. The Salt Lake Tribune, Inc. is a 501(c)(3) public charity and contributions are tax deductible

RELATED STORIES

Investigation into racist incident involving utah women’s basketball team turns up new evidence. here’s what it shows., coeur d’alene has a long history of hate groups. why was utah put there for the ncaa tournament, utah women’s basketball experienced ‘racial hate crimes’ during ncaa tournament, coach says, utah women’s basketball season ends before the sweet 16, gordon monson: ute jenna johnson’s story is an important one that can lift every competitive soul, may’s flavorful finds: chef jeff’s budget-friendly delights at smith’s, weber state university takes utah nurse to next level in life, career., lgbtq students at byu march for progress — but say they still have a lot to fight, including ‘musket fire’ speech requirement, opinion: salt lake city school district’s restroom presentation harms students. as nonbinary and transgender educators, we see the damage., opinion: i research campus activism. recent protests, including those in utah, point to a major culture shift., what one utah student learned in hope squad helped her save a friend’s life, featured local savings.

Do dogs live long? What to know about dog life expectancy based on breed and size.

The oldest dog to ever live was Bobi, a 31-year-old Portuguese dog who likes long naps by the fire. Bobi was born in 1992 when his owner was just 8 years old and died in October 2023.

Pets are often an important pillar in a child’s life growing up. Studies from the Human Bond Research Institute found children in families with dogs have greater socio-emotional outcomes and more unstructured physical activity than those from non-dog households.

It’s understandable to wish your dog could live forever. But how long can we realistically expect them to be a part of our lives? Here's what to know:

How long do dogs live?

The lifespan of your furry friend depends on size and breed says Nicole Savageau, a veterinarian with The Vets .

Small dogs, like Chihuahuas, Yorkies, Maltese or Shih Tzus typically live between 14-16 years. Medium-sized dogs, including golden retrievers, French bulldogs and cocker spaniels, live closer to 10-12 years. Large or giant breed dogs – think Great Danes, Irish wolfhounds, Saint Bernards – usually only live between seven and 10 years. 

The only exception to the size rule Savageau has seen is cattle dogs.

“Multiple cattle dogs I saw were over 20 years old, and they are truly a medium breed, so most medium breeds would only live to be 10 to 12,” Savageau says. “These dogs are living 8+ years longer than that and I've never seen anything like that.”

Before Bobi, the world’s oldest living dog was the 29-year-old Australian cattle dog Bluey. Even Bobi, who is a purebred Rafeiro do Alentejo, comes from a breed historically used to guard property, livestock, sheep and cattle . 

Why do small dogs live longer?

There isn’t a ton known about why small dogs live longer, though a 2023 study published in the American Naturalist found larger species of dogs may be more susceptible to cancer because of selective breeding practices.

“(Big dogs) get a lot of arthritis when they’re older, they can’t move around as much so their size might be a part of it,” Savageau says. “Even when they don’t have horrible problems, they just don’t tend to live long.”

How much should dogs sleep?: Daily snooze hours, plus when to worry

Do mixed-breed dogs live longer?

There is some evidence that suggests mixed-breed dogs live longer than purebred dogs, according to a 2019 study, but the difference in lifespan decreases if the mixed-breed dogs are bigger. 

It depends on the genetic lottery, says Savageau, meaning a mixed-breed dog could miss out on the genetic conditions associated with the breeds they’re mixed with. On the flip side, they could also inherit all of the genetic conditions from the breeds they descend from. 

“Sometimes the opposite is true and mixed breed dogs actually get multiple problems from their initial genetics, and sometimes they actually do a lot better because some of those recessive genes are bred out of them,” she says. 

Golden retrievers, for example, commonly die of a spleen cancer called hemangiosarcoma around age 10-12. A mixed-breed dog who is part golden retriever could potentially miss out on that disease. But there’s no way to guarantee, Savageau says. 

How long do dogs live in human years?

Dogs age differently, and faster than humans. The first year of a puppy’s life is about 15 human years, according to the American Veterinary Medical Association. The second year is equivalent to nine human years, and then each subsequent dog year is about four to five human years. 

AVMA’s calculations are based on dogs between 21-50 lbs. So medium dogs, with a life expectancy of 10-12 years, will live to be the human equivalent of approximately 60 to 69 years old.

How to extend your dog’s life

• See the vet every year: Take your pup to its annual checkup , and make sure to get bloodwork done yearly if you have a senior dog. “A lot of times we'll get age-related diseases that can be managed and the sooner you catch them, the better managed they are and the longer they can live,” Savageau says. 
• Keep your dog lean: Obesity in dogs can decrease their lifespan by over two years
• Vaccinate and prevent diseases: Check in with your vet about diseases in your area to vaccinate your dog against. Savageau also recommends keeping up with heartworm prevention by giving your pup a deworming pill as instructed by your vet.
• Dental health: Poor dental health can cause additional problems or diseases in your dog. Check-in with your vet about recommended cleanings for your dog. 

You might not want to think about the end of your dog’s life when you first get them, but Savageau says it’s an important step every owner should take, regardless of the animal.

“From the moment you get an animal, it's good to research what their life expectancy is, and just have that in your mind,” Savageau says. “That way when the time comes, it's just easier emotionally.”

Largest dog breed in the world?: Meet the record holders

Just Curious for more? We've got you covered

USA TODAY is exploring the questions you and others ask every day. From "Do dogs smile?" to "What is glamping?" to "What is the most populous city in the world?" , we're striving to find answers to the most common questions you ask every day. Head to our Just Curious section to see what else we can answer for you.