Open access scientometrics and the UK research assessment exercise (Article, English),Harnad, S PROCEEDINGS OF ISSI 2007: 11TH INTERNATIONAL CONFERENCE OF THE INTERNATIONAL SOCIETY FOR SCIENTOMETRICS AND INFORMETRICS, VOLS I AND II. 2007. p.27-33

[Eugene Garfield]

Email: 	        harnad at ecs.soton.ac.uk
TITLE:          Open access scientometrics and the UK research assessment
                exercise (Article, English)
AUTHOR:         Harnad, S
SOURCE:         PROCEEDINGS OF ISSI 2007: 11TH INTERNATIONAL CONFERENCE
                OF THE INTERNATIONAL SOCIETY FOR SCIENTOMETRICS AND
                INFORMETRICS, VOLS I AND II. 2007. p.27-33 INT SOC
                SCIENTOMETRICS & INFORMETRICS-ISSI, LEUVEN

SEARCH TERM(S):  GARFIELD E  rauth; SCIENTOMETRIC*  item_title;
                 GARFIELD E         SCIENCE               122:108   1955

KEYWORDS:       open access; research assessment exercise; united kingdom

ABSTRACT:       Scientometric predictors of research performance need to
be validated by showing that they have a high correlation with the 
external criterion they are trying to predict. The UK Research Assessment 
Exercise (RAE) together with the growing movement toward making the full- 
texts of research articles freely available on the web offer a unique 
opportunity to test and validate a wealth of old and new scientometric 
predictors, through multiple regression analysis: Publications, journal 
impact factors, citations, co-citations, citation chronometrics (age, 
growth, latency to peak, decay rate), hub/authority scores, h-index, prior 
funding, student counts, co-authorship scores, endogamy/exogamy, textual 
proximity, download/co-downloads and their chronometrics, etc. can all be 
tested and validated jointly, discipline by discipline, against their RAE 
panel rankings in the forthcoming parallel panel-based and metric RAE in 
2008. The weights of each predictor can be calibrated to maximize the 
joint correlation with the rankings. Open Access Scientometrics will 
provide powerful new means of navigating, evaluating, predicting and 
analyzing the growing Open Access database, as well as powerful incentives 
for making it grow faster.