Some months ago, a post described a review of Academic Analytics data for Georgetown faculty.
After collegially reviewing data and methods with Academic Analytics, we concluded that most of the discrepancies between information collected from faculty CVs and Academic Analytics’ data were the product of the type of work covered and collected by Academic Analytics, timing issues relating to faculty hiring, and date ranges associated with certain Academic Analytics data. It is clear to me that Academic Analytics does a good job of collecting and making available the data that it purports to collect, and that the data largely are accurate. For that reason Academic Analytics can be a useful tool for universities, and it has the potential to become even more useful as it expands the nature and types of data it collects. Importantly, the results reported in my prior blog represented Georgetown’s attempt to completely replicate scholarly performance data as they appear on faculty members’ CVs. Academic Analytics, of course, neither claims nor seeks to address every data element that appears in faculty CVs, and instead aims to build a comparative scholarly performance matrix across all research universities. That difference in aim and purpose largely accounts for many of the discrepancies reported in my prior blog. We continue to believe that Academic Analytics’ data are valuable and important.