Preliminary Study on the Impact of Literature Curation in a Model Organism Database on Article Citation Rates

Abstract

Literature curation by model organism databases (MODs) results in the interconnection of papers, genes, gene functions, and other experimentally supported biological information, and aims to make research data more discoverable and accessible to the research community. That said, there is a paucity of quantitative data about if and how literature curation affects access and reuse of the curated data. One potential measure of data reuse is the citation rate of the article used in curation. If articles and their corresponding data are easier to find, then we might expect that curated articles would exhibit different citation profiles when compared to articles that are not curated. That is, what are the effects of having scholarly articles curated by MODs on their citation rates? To address this question we have been comparing the citation behavior of different groups of articles and asking the following questions: (1) given a collection of 'similar' articles about Arabidopsis, is there a difference in the citation numbers between articles that have been curated in TAIR (The Arabidopsis Information Resource) and ones that have not, (2) for articles annotated in TAIR, is there a difference in the citation behavior before vs. after curation and, (3) is there a difference in citation behavior between Arabidopsis articles added to TAIR's database and those that are not in TAIR? Our data indicate that curated articles do have a different citation profile than non-curated articles that appears to result from increased visibility in TAIR. We believe data of this type could be used to quantify the impact of literature curation on data reuse and may also be useful for MODs and funders seeking incentives for community literature curation. This project is a research partnership between TAIR and Elsevier Labs.