ArticleDatabase : the journal of biological databases and curation2016
Crowd-sourcing and author submission as alternatives to professional curation.
Article in Database : the journal of biological databases and curation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Helping authors produce FAIR taxonomic data: evaluation of an author-driven phenotype data production prototype.Database : the journal of biological databases and curation · 2025Article
- PubChem synonym filtering process using crowdsourcing.Journal of cheminformatics · 2024Article
- AI and the democratization of knowledge.Scientific data · 2024Article
- Crowdsourcing biocuration: The Community Assessment of Community Annotation with Ontologies (CACAO).PLoS computational biology · 2021Article
- Measurement Recorder: developing a useful tool for making species descriptions that produces computable phenotypes.Database : the journal of biological databases and curation · 2020Article
- A behind-the-scenes tour of the IEDB curation process: an optimized process empirically integrating automation and human curation efforts.Immunology · 2020Article
- Community curation in PomBase: enabling fission yeast experts to provide detailed, standardized, sharable annotation from research publications.Database : the journal of biological databases and curation · 2020Review
- Text mining meets community curation: a newly designed curation platform to improve author experience and participation at WormBase.Database : the journal of biological databases and curation · 2020Article
- Biocuration: Distilling data into knowledge.PLoS biology · 2018Article
- Funding knowledgebases: Towards a sustainable funding model for the UniProt use case.F1000Research · 2017Article
- PhenoPlasm: a database of disruption phenotypes for malaria parasite genes.Wellcome open research · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Can we decrease the costs of database curation by crowd-sourcing curation work or by offloading curation to publication authors? This perspective considers the significant experience accumulated by the bioinformatics community with these two alternatives to professional curation in the last 20 years; that experience should be carefully considered when formulating new strategies for biological databases. The vast weight of empirical evidence to date suggests that crowd-sourced curation is not a successful model for biological databases. Multiple approaches to crowd-sourced curation have been attempted by multiple groups, and extremely low participation rates by 'the crowd' are the overwhelming outcome. The author-curation model shows more promise for boosting curator efficiency. However, its limitations include that the quality of author-submitted annotations is uncertain, the response rate is low (but significant), and to date author curation has involved relatively simple forms of annotation involving one or a few types of data. Furthermore, shifting curation to authors may simply redistribute costs rather than decreasing costs; author curation may in fact increase costs because of the overhead involved in having every curating author learn what professional curators know: curation conventions, curation software and curation procedures.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.