Improving OpenURL Analytics for Better Resource Access
In this content, various practices and techniques are discussed for enhancing the effectiveness of OpenURLs through analytics. It covers topics such as defining element weights, statistical approaches to determining weights, failure rates analysis, and calculated element weights based on real data and research findings. The aim is to optimize the completion scores and success rates of OpenURLs for seamless resource access and information retrieval. Practical examples and recommendations are provided to aid in understanding and implementing these strategies.
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Presentation Transcript
IOTA: Improving OpenURL Through Analytics Nettie Lagace (@abugseye) NISO Associate Director for Programs CEAL Workshop on Electronic Resources Standards and Best Practices March 25, 2014 Thanks to Oliver Pesch of EBSCO for much of this slide material.
SAMPLE OPEN URL DATA ?date=2008-02-04 &issn=1083-3013 &volume=13 &issue=20 &atitle=the+casualties+of+war Simple example assuming equal element weights Element Description (Total for This OpenURL) Total Weights Completeness Score... Weight This OpenURL 1 ATitle Article title 5 / 8 1 AuLast Author s last name = .625 1 1 Date Date of publication 1 ISSN ISSN 1 1 Issue Issue number 1 1 SPage Start page 1 Title Journal Title 1 Volume Volume number 1 1 5 TOTAL 8
IOTA Recommended Practice Defines a technique for determining element weights Tested with real link resolvers and real OpenURLs Based on research which looked for a correlation with data elements on the OpenURL and success of the OpenURL
A Statistical Approach to Determining Element Weights Select a set of perfect OpenURLs include all key data elements and resolve to full text Perform step-wise regression Test failure rates for each element by removing that element Use failure rates as basis for weights Use weights to calculate Completeness Scores and to test for correlation between weights and success for larger sample
Failure Rates from 1500 OpenURL test sample Author s last name is least Element removed from the OpenURL important Description Failure Percentage ATitle Article title .74% Date is surprisingly low AuLast Author s last name .07% Date Date of publication .4% ISSN ISSN (either online or print ISSN) 22.02% Issue Issue number 20.27% SPage Start page 33.27% Volume is most critical Title Journal Title (either Title or Jtitle) .61% Volume Volume number 74.14%
Calculated Element Weights Element Description Weight* ATitle Article title 1.87 AuLast Author s last name 0.83 Date Date of publication 1.61 ISSN ISSN (either online or print ISSN) 3.34 Issue Issue number 3.31 SPage Start page 3.52 Title Journal Title (either Title or Jtitle) 1.78 Volume Volume number 3.87 *Element weight calculation: log10 (failure-rate-per-10,000 OpenURLs)
Results 1.2000 1.0000 Average of Completeness Score 0.8000 0.6000 0.4000 Average of Success Score 0.2000 0.0000 Correlation Coefficient .80 Tests conducted on sample of 15,000 OpenURLs randomly pulled from IOTA database
IOTA Online Tool 23.3+ million OpenURLs processed Reporting interface Analyze data elements (metrics) across vendors or database (Source) Analyze (Source) for all data elements
Analysis of vendors by element (metric)
Analysis of elements by vendor
How to use IOTA materials The Technical Report provides suggestions for improving OpenURLs The interactive tool offers a means to pin-point irregularities in data provided on OpenURLs The Recommended Practice describes how to create a Completeness Index Completeness Index allows OpenURL quality problems to be quantified
Why you should use IOTA Link resolver vendors can implement the Completeness Index in their products to help identify problematic OpenURL sources Librarians can use suggestions and Completeness Index to more effectively communicate quality problems to content providers Content providers can use the online interactive tool to identify problems with the data they provide
Thank you! Questions? nlagace@niso.org @abugseye I Want To Go To Magnolia Mountain by lilomooney is licensed under CC-BY 2.0
