Week 9 - Data Standards and Silos

First of all, "Library Standards and E-Resource Management: A Survey of Current Initiatives and Standards Efforts" and "Standards for the Management of Electronic Resources" relate directly to my post last week.  Both of these articles include great information on the acronyms and phrases I learned then while also focusing on data standards. For example, the first article includes a short definition I particularly like of COUNTER: "a collaboration between libraries, publishers, and content aggregators focused on creating guidelines that will lead to consistent, comparable, and credible usage statistics."  After my exercise in definitions last week and reading these articles this week, I feel confident in my understanding of ERM terms.

I found some of the statistics in Carpenter's "Improving Information Distribution Through Standards" presentation especially interesting.  First, he states that the average academic research library has approximately 40,000 serials.  I knew that electronic resource management systems were important but this particular statistic makes it extremely clear why libraries need good ways to manage the license terms, publisher, cost and other metrics regarding their serials.  When subscribing to such a large number of serials, keeping track of all of this information could easily get overwhelming.  Second, I learned that only 25% of librarians' data analysis time is actually spent analyzing.  The rest is spent primarily in obtaining and organizing the data for analysis.  This statistic emphasizes the importance of SUSHI.  Specifically, SUSHI will help librarians spend less time performing these menial tasks and more time doing actual analysis.

Speaking of analysis, I am curious about several aspects of the usage bibliometrics purposed in "Counter: Current Developments and Future Plans."  Specifically, I am wondering about the impact of calculating usage statistics for individual articles.  Might this have an effect on the author?  Would universities evaluate their faculty partially based on the usage statistics of their articles rather than relying only on metrics such as the number of times an article is cited?  Also, regarding the journal usage factor, I wonder how an article that has only an abstract in a database could be included in this calculation.  Is there any way of knowing if the researcher actually obtained the print version of the article?  Perhaps if the researcher clicked the button to search his or her local library's catalog that could be counted as a use.