(Image adapted from UltimateLibrarian via Flickr. CC.)
I've found that in the last year I'm getting more and more questions about Impact Factors, h-indexes, and the like. Last May we gave an overview of using Web of Science to calculate individual impact factors that was popular with the faculty attendees.
When looking into helping faculty discover/calculate these numbers, I've found that they're surprisingly complicated...both finding the numbers and explaining just what exactly is being calculated.
Are others seeing more of an interest in these numbers as well? How are you teaching it?
I thought I'd highlight a new(ish) resource that you can use to learn more and/or point your patrons/students to if questions arise. Back in August a group of U of M librarians put together a suite of webpages to provide support on this topic.
I've found that in the last year I'm getting more and more questions about Impact Factors, h-indexes, and the like. Last May we gave an overview of using Web of Science to calculate individual impact factors that was popular with the faculty attendees.
When looking into helping faculty discover/calculate these numbers, I've found that they're surprisingly complicated...both finding the numbers and explaining just what exactly is being calculated.
Are others seeing more of an interest in these numbers as well? How are you teaching it?
I thought I'd highlight a new(ish) resource that you can use to learn more and/or point your patrons/students to if questions arise. Back in August a group of U of M librarians put together a suite of webpages to provide support on this topic.
You can access these pages at https://www.lib.umn.edu/researchsupport/impact
You can also find them under Services in the top navigation bar under Researcher Support.
Also U of M Mathematics Librarian, Kris Fowler, co-authored an article on the topic that is a good (and quick!) read. The full text is available through ArXiv at http://bit.ly/aCgu91.
