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AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification
Lin Dai1, Ming Tian, Jiayan Wu
1CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
To boost community participation in biological wikis (bio-wikis), a new system called AuthorReward was developed. This system quantifies contributions to knowledge curation, providing explicit authorship and encouraging more researchers to participate.
Area of Science:
- Bioinformatics
- Computational Biology
- Knowledge Management
Background:
- Biological knowledge is rapidly expanding, necessitating efficient curation methods.
- Existing biological wikis (bio-wikis) struggle with community participation due to a lack of authorship credit.
- Insufficient community engagement limits the impact of bio-wikis in knowledge curation.
Purpose of the Study:
- To address the challenge of low community participation in bio-wikis.
- To develop a system that rewards community efforts in biological knowledge curation.
- To increase the effectiveness of bio-wikis through enhanced community engagement.
Main Methods:
- Developed AuthorReward, an extension for MediaWiki platforms.
- Quantified researcher contributions by considering both edit quantity and quality.
- Implemented an automated system for assigning explicit authorship based on contributions.
Main Results:
- AuthorReward provides a metric for evaluating community curation efforts.
- The system aims to incentivize researchers by providing explicit authorship.
- Expected to increase community participation in bio-wikis.
Conclusions:
- AuthorReward offers a promising solution to enhance community curation in bio-wikis.
- By rewarding contributions, the system can foster greater engagement from the scientific community.
- This approach can help manage the vast amount of biological knowledge more effectively.
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