GSA 2020 Connects Online

Paper No. 92-2
Presentation Time: 5:40 PM

A PYTHON-BASED WEB APPLICATION TO GAUGE SCIENTIFIC IMPACT USING AUTHOR SEQUENCE


BURTON, Zachary F.M., Department of Geological Sciences, Stanford University, Stanford, CA 94305 and BURTON, Owen M., Data Science Program, Lambda School, San Francisco, CA 94104

Measurement of scholarly output is central to bibliometric practice. In the sciences—including the geosciences—scientometric analysis aims to quantify impact, relevance, and performance of scientists and their work. Application of scientometrics to assess productivity of researchers is influential in determining a scientist’s career progression (e.g., metrics often influence university hiring and promotion decisions), in determining the funding a scientist obtains, and in determining the awards and accolades a scientist receives. Since the 1960s, the conventional metrics of citation count, publication count, and journal impact factor have been employed essentially to the exclusion of all else. A notable exception is the h-index, which was introduced in 2005 to gauge the output and impact of individual researchers (in contrast to the journal-centric impact factor). The h-index has been readily adopted by the scientific community, and despite the proliferation of hundreds of alternative indices, remains regarded as a good—or at least useful—indicator of scientific productivity and impact. However, a noted shortcoming of the h-index, as well as of total citation and publication counts, is that these measures ignore an author’s degree of contribution to a given multiauthor publication. Although author contributions often vary substantially (e.g., degree of contribution typically corresponds to byline sequence, excluding the last author), all authors currently receive equal credit for a given publication when their individual citation counts and h-indices are computed. To ameliorate this lack of granularity, we develop an open-source Python-based web application to calculate author position-specific citation counts and h-indices for any scientist’s Google Scholar profile. This browser-based tool provides a more nuanced view of scientific output and contribution and should be useful to both researchers and institutions. The app requires no coding skills to operate.