AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification.

Lin Dai, Ming Tian, Jiayan Wu, Jingfa Xiao, Xumin Wang, Jeffrey P Townsend, Zhang Zhang
Author Information
  1. Lin Dai: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.

Abstract

SUMMARY: Community curation-harnessing community intelligence in knowledge curation, bears great promise in dealing with the flood of biological knowledge. To exploit the full potential of the scientific community for knowledge curation, multiple biological wikis (bio-wikis) have been built to date. However, none of them have achieved a substantial impact on knowledge curation. One of the major limitations in bio-wikis is insufficient community participation, which is intrinsically because of lack of explicit authorship and thus no credit for community curation. To increase community curation in bio-wikis, here we develop AuthorReward, an extension to MediaWiki, to reward community-curated efforts in knowledge curation. AuthorReward quantifies researchers' contributions by properly factoring both edit quantity and quality and yields automated explicit authorship according to their quantitative contributions. AuthorReward provides bio-wikis with an authorship metric, helpful to increase community participation in bio-wikis and to achieve community curation of massive biological knowledge.
AVAILABILITY: http://cbb.big.ac.cn/software.
CONTACT: zhangzhang@big.ac.cn
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

References

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Grants

  1. P01 GM068067/NIGMS NIH HHS

MeSH Term

Algorithms
Authorship
Cooperative Behavior
Internet
Software