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Title: 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.

Authors:
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE
Contributing Org.:
AgBioData consortium
OSTI Identifier:
1471253
Alternate Identifier(s):
OSTI ID: 1490698
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Published Article
Journal Name:
Database
Additional Journal Information:
Journal Volume: 2018; Journal ID: ISSN 1758-0463
Publisher:
Oxford University Press
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES

Citation Formats

None, None. AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture. United States: N. p., 2018. Web. doi:10.1093/database/bay088.
None, None. AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture. United States. doi:10.1093/database/bay088.
None, None. Tue . "AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture". United States. doi:10.1093/database/bay088.
@article{osti_1471253,
title = {AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture},
author = {None, None},
abstractNote = {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.},
doi = {10.1093/database/bay088},
journal = {Database},
number = ,
volume = 2018,
place = {United States},
year = {2018},
month = {9}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1093/database/bay088

Citation Metrics:
Cited by: 3 works
Citation information provided by
Web of Science

Figures / Tables:

Table 1 Table 1: Survey results for ontology use in databases for each data type (from 29 respondents)

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    Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.