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A non-programmers guide to enhancing and making sense of EZ Proxy logs

A non-programmers guide to enhancing and making sense of EZ Proxy logs Libraries throughout the world use OCLC’s EZproxy software to manage access to e-resources. When cleaned, processed, visualized and enhanced, these logs paint a valuable picture of a library’s impact on researcher’s lives. The purpose of this paper is to share techniques and procedures for enhancing and de-identifying EZproxy logs using Tableau, a data analytics and visualization software, and Tableau Prep, a tool used for cleaning, combining and shaping data for analysis.Design/methodology/approachIn February 2018, The Ohio State University Libraries established an automated daily process to extract and clean EZproxy log files. The assessment librarian created a series of procedures in Tableau and Tableau Prep to union, parse and enhance these files by adding information such as user major, user status (faculty, graduate or undergraduate) and the title of the requested resource. She last stripped the data set of identifiers and applied best practices for maintaining confidentiality to visualize the data.FindingsThe data set is currently 1.5m rows and growing. The visualizations may be filtered by date, user status and user department/major where applicable. Safeguards are in place to limit data presentation when filters might reveal a user’s identity.Originality/valueTableau used in concert with Tableau Prep allows an assessment librarian to clean and combine data from various sources. Once procedures for cleaning and combining data sources are established, the data driving visualizations can be set to refresh on a set schedule. This expedites the ability of librarians to derive actionable insights from EZproxy data and to share the library’s positive impact on researcher’s lives. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Performance Measurement and Metrics Emerald Publishing

A non-programmers guide to enhancing and making sense of EZ Proxy logs

Murphy, Sarah Anne
Performance Measurement and Metrics , Volume 20 (3): 10 – Dec 3, 2019
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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1467-8047
DOI
10.1108/pmm-08-2019-0034
Publisher site
See Article on Publisher Site

Abstract

Libraries throughout the world use OCLC’s EZproxy software to manage access to e-resources. When cleaned, processed, visualized and enhanced, these logs paint a valuable picture of a library’s impact on researcher’s lives. The purpose of this paper is to share techniques and procedures for enhancing and de-identifying EZproxy logs using Tableau, a data analytics and visualization software, and Tableau Prep, a tool used for cleaning, combining and shaping data for analysis.Design/methodology/approachIn February 2018, The Ohio State University Libraries established an automated daily process to extract and clean EZproxy log files. The assessment librarian created a series of procedures in Tableau and Tableau Prep to union, parse and enhance these files by adding information such as user major, user status (faculty, graduate or undergraduate) and the title of the requested resource. She last stripped the data set of identifiers and applied best practices for maintaining confidentiality to visualize the data.FindingsThe data set is currently 1.5m rows and growing. The visualizations may be filtered by date, user status and user department/major where applicable. Safeguards are in place to limit data presentation when filters might reveal a user’s identity.Originality/valueTableau used in concert with Tableau Prep allows an assessment librarian to clean and combine data from various sources. Once procedures for cleaning and combining data sources are established, the data driving visualizations can be set to refresh on a set schedule. This expedites the ability of librarians to derive actionable insights from EZproxy data and to share the library’s positive impact on researcher’s lives.

Journal

Performance Measurement and Metrics – Emerald Publishing

Published: Dec 3, 2019

Keywords: Data visualization; Library assessment; Data cleaning; EZproxy; Tableau; Tableau Prep

References

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    Yeager, H.J.
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