Browsing by Author "Stemper, James"

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    Disciplinary Differences in Applying E-Journal Metrics
    (Library Assessment Conference, 2014-08-04) Stemper, James; Chew, Katherine; Schoeborn, Mary; Lilyard, Caroline
    Purpose: Determine if the relationship between a) journal downloads or rankings and b) faculty authoring venue or citations to them varies by discipline. Does the strength of the correlations vary by discipline? Do the social sciences or humanities differ from the physical or health sciences? Are there differences between similar disciplines (e.g. physical & health sciences), or within disciplines (e.g. nursing to pharmacy)? Determine if the newer ranking metrics Eigenfactor & SNIP correlate better with downloads and citations than Impact Factor? Determine if Scopus is a valid alternative to Local Journal Use Reports as a way of correlating faculty publication & citation practices with journal selections Methodology: Use data: 4 years of (2009-2012) collected for each subject journal set: OpenURL link resolver article view requests & publisher’s COUNTER article downloads Ranking data: 5-year Impact Factor, current EigenFactor & Source Normalized Impact Per Paper (SNIP) recorded for each journal title Citation data: 2 years (2009-2010) collected from Thomson Local Journal Use Reports (LJUR); 4 years (2009-2012) from Elsevier SciVal (Scopus) Journal value assessed by: (1) author decisions to publish there (2) external citations to these authors (3) cost effectiveness (via downloads *and* citations) using rank correlation coefficients to compare the different metrics Conclusions: Inform selection decisions Use LJUR and Scopus: LJUR reports more subscribed titles whose local faculty articles get cited by peers, but Scopus reports more subscribed journals that local faculty author in Obtain liaison/subject coordinator input: Hard to centralize collection if the “best fit” metrics vary by discipline Understand patterns of use Capture demographics of logins and interdisciplinary use Show value to the academy Defend library tax on departments Offer services to help faculty demonstrate impact e.g. for tenure portfolios
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    User-defined valued metrics for electronic journals
    (2013-02-18) Chew, Katherine; Stemper, James; Lilyard, Caroline; Schoenborn, Mary
    Purpose: Building on the work done by the California Digital Library (CDL), the University of Minnesota Libraries is developing a set of user-defined value-based electronic journal usage metrics. User value is assessed in three overall categories: (1) utility or reading value, (2) quality or citing value, and (3) cost effectiveness. In addition to analyzing vendor-generated usage metrics, also included were Affinity String data, derived from the University of Minnesota’s central authentication system that anonymously captures a user’s academic department and degree program or position at the university and combined with vendor-generated usage data, provides a granular picture of journal use down to the title level. Collection management librarians and library users can benefit from a viable, more accurate metric for use and value of library resources than cost-per-download, which would ensure that the most needed/valued resources are available to further research and learning. Methodology: Metrics were identified that are utilized to determine e-journal retainability: OpenURL link resolver requests for article views, COUNTER-compliant downloads, JCR Impact Factors, Eigenfactor Scores, local citations from Thomson Reuters Local Journal Use Reports and Affinity String requests for article views. Two years of usage data were assessed using Pearson correlation coefficients to compare the different metrics. Affinity String data is correlated with the results to determine any discipline or degree level differences. A composite score is assigned to each journal to assess its overall value in comparison to other journals within the same broad subject category. Findings: This project found SFX clickthroughs a more consistent predictor than COUNTER downloads of the journals our faculty will cite in their articles, with Eigenfactor a more consistent predictor of citation behavior than Impact Factor.