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Abstract

Die Deutsche Bibliothek, the Library of Congress, and OCLC Online Computer Library Center are jointly developing a virtual international authority file (VIAF) for personal names which links authority records from the world's national bibliographic agencies and will be made freely available on the Web. The goals of the project are to prove the viability of automatically linking authority records from different national authority files and to demonstrate its benefits. The authority and bibliographic files from the Library of Congress and Die Deutsche Bibliothek were used to create the initial VIAF which contains over six million names with over a half million links. A key aspect of the project was the development of automated name matching algorithms which use information from both authority records and the corresponding bibliographic records. The practicality of algorithmically linking the personal names between national authority files was demonstrated; seventy percent of the authority records for personal names common to both files were automatically linked with an error rate of less than one percent. The long-term goal of the VIAF project is to combine the authoritative names from many national libraries and other significant sources into a shared global authority service.

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Abstract

A draft of Functional Requirements for Authority Records (FRAR) was made available for worldwide review on IFLANET from July through October 2005. The FRANAR Working Group received comments from 12 individuals and 13 institutions (including 6 national libraries and 3 national-level cataloguing committees). The working group expresses its appreciation to all who took the time to prepare comments. The comments received were compiled into a comments log which totaled 145 pages. Seven members of the Working Group met at the Koninklijke Bibliothek, The Hague, Netherlands, on December 9, 2005, to consider these comments and to start revising the draft to reflect decisions made in response to the comments. The group was able to deal with about two-thirds of the comments during the meeting and, since the December meeting has had a series of four conference calls to complete discussions of the remaining comments, with additional calls anticipated before the Seoul meetings.

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Content

Bill Howe and his colleagues at the University of Washington, in Seattle, decided to find out. First, they trained a computer algorithm to distinguish between various sorts of figures-which they defined as diagrams, equations, photographs, plots (such as bar charts and scatter graphs) and tables. They exposed their algorithm to between 400 and 600 images of each of these types of figure until it could distinguish them with an accuracy greater than 90%. Then they set it loose on the more-than-650,000 papers (containing more than 10m figures) stored on PubMed Central, an online archive of biomedical-research articles. To measure each paper's influence, they calculated its article-level Eigenfactor score-a modified version of the PageRank algorithm Google uses to provide the most relevant results for internet searches. Eigenfactor scoring gives a better measure than simply noting the number of times a paper is cited elsewhere, because it weights citations by their influence. A citation in a paper that is itself highly cited is worth more than one in a paper that is not.
As the team describe in a paper posted (http://arxiv.org/abs/1605.04951) on arXiv, they found that figures did indeed matter-but not all in the same way. An average paper in PubMed Central has about one diagram for every three pages and gets 1.67 citations. Papers with more diagrams per page and, to a lesser extent, plots per page tended to be more influential (on average, a paper accrued two more citations for every extra diagram per page, and one more for every extra plot per page). By contrast, including photographs and equations seemed to decrease the chances of a paper being cited by others. That agrees with a study from 2012, whose authors counted (by hand) the number of mathematical expressions in over 600 biology papers and found that each additional equation per page reduced the number of citations a paper received by 22%. This does not mean that researchers should rush to include more diagrams in their next paper. Dr Howe has not shown what is behind the effect, which may merely be one of correlation, rather than causation. It could, for example, be that papers with lots of diagrams tend to be those that illustrate new concepts, and thus start a whole new field of inquiry. Such papers will certainly be cited a lot. On the other hand, the presence of equations really might reduce citations. Biologists (as are most of those who write and read the papers in PubMed Central) are notoriously mathsaverse. If that is the case, looking in a physics archive would probably produce a different result.

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Date

10. 9.2000 17:18:29