Usage data


Usage data is a big debate at the moment...not all 'use' is 'real' use (robots etc) and 'activity' and ‘use’ aren’t quite the same thing of course. There are three main aspects to usage data. The first is tracking use to deliver improved resources discovery, for example by ‘recommender services’. (‘People who found that also search for this…’). The second is to track use as a means of obtaining a use factor for the libraries ‘collection’ and deliver better value for money and finally it can be used to create an ‘impact’ factor to rate a scholarly article.
Usage data for recommender services
ExLibris has taken the lead here with its bX recommender service which was launched in 2009. The bX service generates recommendations based on the analysis of tens of millions of linking activities carried out by users at research institutions worldwide. The recommendations are accessible through a library’s SFX® or another Open URL resolver. ExLibris delivers bX a SaaS application.

Usage data for management of e-resources
One of the reasons for buying an ERM is to provide effective management of the library's e-resources/e-journals and usage data will be key. Trying to get usage statistics has long been the bane of electronic resources librarians. Some databases are very expensive and libraries need to be certain they are really being used and meeting the needs of users. Particularly in an environment of shrinking/tight budgets, Statistics can also help in negotiations with suppliers on price. Two linked initiatives are improving the availability and management of usage data:

COUNTER (Counting Online Usage of Networked Electronic Resources) was launched in 2002 with a mission is to develop an international code of standards and protocols) governing the recording and exchange of online usage data that’s agreed upon and used by both publishers and libraries. Currently over 100 journal and database vendors/producers of over 15,000 journals are COUNTER compliant. In addition, 13 vendors of books and reference works are compliant. Unfortunately, though vendors who followed COUNTER protocols (and allowed themselves to be audited by COUNTER approved auditors) provided good statistics, actually getting the statistics can time a consuming procedure. No mechanism existed for automatically retrieving, combining, and storing COUNTER usage data from different sources.

SUSHI (Standardized Usage Statistics Harvesting Initiative) was created to solve the above problem and reduced the amount of time and effort required to get usage statistics and put them in a usable format.

Aggregating usage data on a national and global scale also provides benefits. For example ‘ScholarlyStats has been developed to provide information professionals with a single point of access to their vendor usage statistics. Providing faster access to consolidated data, it can help you to analyze usage of your online content more easily and more effectively. ScholarlyStats delivers consolidated reports to libraries around the globe, providing a clearer view of usage of over 70,000 journals and almost 450 databases from 46 platforms