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Database: The Journal of Biological Databases and Curation
Article . 2018 . Peer-reviewed
License: CC BY
Data sources: Crossref
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AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture

Authors: Lisa C. Harper; Jacqueline D. Campbell; Ethalinda K. S. Cannon; Sook Jung; Monica F. Poelchau; Ramona Walls; Carson M. Andorf; +45 Authors

AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture

Abstract

The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require data management plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices.

International audience

Countries
France, United States, France, France
Subjects by Vocabulary

Microsoft Academic Graph classification: Computer science Data management Best practice Interoperability Biological database computer.software_genre Biological data Data curation Database business.industry Metadata Data access business computer

Keywords

[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Breeding, General Biochemistry, Genetics and Molecular Biology, Databases, Library and Information Studies, Genetic, Information and Computing Sciences, Surveys and Questionnaires, Databases, Genetic, Library And Information Studies, Metadata, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Data management and data science, [INFO.INFO-WB]Computer Science [cs]/Web, Agriculture, Genomics, Biological Sciences, Bioinformatics and computational biology, Data Format, [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, Gene Ontology, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], Zero Hunger, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], General Agricultural and Biological Sciences, Information Systems

99 references, page 1 of 10

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4. Wilkinson,M.D., Dumontier,M., Aalbersberg,I.J.J. et al. (2016) The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data., 3, 160018.

5. Howe,D., Costanzo,M., Fey,P. et al. (2008) Big data: the future of biocuration. Nature, 455, 47-50.

6. Burge,S., Attwood,T.K., Bateman,A. et al. (2012) Biocurators and biocuration: surveying the 21st century challenges. Database, 2012, https://doi.org/10.1093/database/bar059.

7. Skrzypek,M.S. and Nash,R.S. (2015) Biocuration at the Saccharomyces genome database. Genesis, 53, 450-457.

8. Berardini,T.Z., Reiser,L., Li,D. et al. (2015) The Arabidopsis information resource: making and mining the “gold standard” annotated reference plant genome. Genesis, 53, 474-485.

9. Swarbreck,D., Wilks,C., Lamesch,P. et al. (2008) The Arabidopsis Information Resource (TAIR): gene structure and function annotation. Nucleic Acids Res., 36, D1009-D1014.

10. Berardini,T.Z. (2004) Functional annotation of the Arabidopsis genome using controlled vocabularies. Plant Physiol., 135, 745-755.

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  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    52
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
52
Top 10%
Top 10%
Top 10%
gold