TY - JOUR
T1 - Scholar Plot
T2 - Design and Evaluation of an Information Interface for Faculty Research Performance
AU - Majeti, Dinesh
AU - Akleman, Ergun
AU - Ahmed, Mohammed Emtiaz
AU - Petersen, Alexander M.
AU - Uzzi, Brian
AU - Pavlidis, Ioannis
N1 - Publisher Copyright:
Copyright © 2020 Majeti, Akleman, Ahmed, Petersen, Uzzi and Pavlidis.
PY - 2019
Y1 - 2019
N2 - The ability to objectively assess academic performance is critical to rewarding academic merit, charting academic policy, and promoting science. Quintessential to performing these functions is first the ability to collect valid and current data through increasingly automated online interfaces. Moreover, it is crucial to remove disciplinary and other biases from these data, presenting them in ways that support insightful analysis at various levels. Existing systems are lacking in some of these respects. Here we present Scholar Plot (SP), an interface that harvests bibliographic and research funding data from online sources. SP addresses systematic biases in the collected data through nominal and normalized metrics. Eventually, SP combines synergistically these metrics in a plot form for expert appraisal, and an iconic form for broader consumption. SP's plot and iconic forms are scalable, representing equally well individual scholars and their academic units, thus contributing to consistent ranking practices across the university organizational structure. In order to appreciate the design principles underlying SP, in particular the informativeness of nominal vs. normalized metrics, we also present the results of an evaluation survey taken by senior faculty (n = 28) with significant promotion and tenure assessment experience.
AB - The ability to objectively assess academic performance is critical to rewarding academic merit, charting academic policy, and promoting science. Quintessential to performing these functions is first the ability to collect valid and current data through increasingly automated online interfaces. Moreover, it is crucial to remove disciplinary and other biases from these data, presenting them in ways that support insightful analysis at various levels. Existing systems are lacking in some of these respects. Here we present Scholar Plot (SP), an interface that harvests bibliographic and research funding data from online sources. SP addresses systematic biases in the collected data through nominal and normalized metrics. Eventually, SP combines synergistically these metrics in a plot form for expert appraisal, and an iconic form for broader consumption. SP's plot and iconic forms are scalable, representing equally well individual scholars and their academic units, thus contributing to consistent ranking practices across the university organizational structure. In order to appreciate the design principles underlying SP, in particular the informativeness of nominal vs. normalized metrics, we also present the results of an evaluation survey taken by senior faculty (n = 28) with significant promotion and tenure assessment experience.
KW - information visualization
KW - research career evaluation
KW - science of science
KW - scientometrics
KW - university evaluation
UR - http://www.scopus.com/inward/record.url?scp=85102302075&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85102302075&partnerID=8YFLogxK
U2 - 10.3389/frma.2019.00006
DO - 10.3389/frma.2019.00006
M3 - Article
C2 - 33870038
AN - SCOPUS:85102302075
SN - 2504-0537
VL - 4
JO - Frontiers in Research Metrics and Analytics
JF - Frontiers in Research Metrics and Analytics
M1 - 6
ER -