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      AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture

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      1 , 2 , 1 , 2 , 3 , 4 , 5 , 1 , 2 , 6 , 7 , 8 , 1 , 9 , 10 , 11 , 12 , 13 , 14 , 3 , 1 , 14 , 15 , 16 , 3 , 11 , 17 , 6 , 18 , 19 , 20 , 21 , 22 , 22 , 11 , 1 , 23 , 16 , 16 , 7 , 24 , 19 , 10 , 7 , 25 , 3 , 12 , 25 , 8 , 25 , 15 , 26 , 27 , 3 , 3
      Database: The Journal of Biological Databases and Curation
      Oxford University Press

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          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.

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          Most cited references75

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          The Arabidopsis Information Resource (TAIR): gene structure and function annotation

          The Arabidopsis Information Resource (TAIR, http://arabidopsis.org) is the model organism database for the fully sequenced and intensively studied model plant Arabidopsis thaliana. Data in TAIR is derived in large part from manual curation of the Arabidopsis research literature and direct submissions from the research community. New developments at TAIR include the addition of the GBrowse genome viewer to the TAIR site, a redesigned home page, navigation structure and portal pages to make the site more intuitive and easier to use, the launch of several TAIR web services and a new genome annotation release (TAIR7) in April 2007. A combination of manual and computational methods were used to generate this release, which contains 27 029 protein-coding genes, 3889 pseudogenes or transposable elements and 1123 ncRNAs (32 041 genes in all, 37 019 gene models). A total of 681 new genes and 1002 new splice variants were added. Overall, 10 098 loci (one-third of all loci from the previous TAIR6 release) were updated for the TAIR7 release.
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            Uberon, an integrative multi-species anatomy ontology

            We present Uberon, an integrated cross-species ontology consisting of over 6,500 classes representing a variety of anatomical entities, organized according to traditional anatomical classification criteria. The ontology represents structures in a species-neutral way and includes extensive associations to existing species-centric anatomical ontologies, allowing integration of model organism and human data. Uberon provides a necessary bridge between anatomical structures in different taxa for cross-species inference. It uses novel methods for representing taxonomic variation, and has proved to be essential for translational phenotype analyses. Uberon is available at http://uberon.org
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              The MetaCyc database of metabolic pathways and enzymes

              Abstract MetaCyc (https://MetaCyc.org) is a comprehensive reference database of metabolic pathways and enzymes from all domains of life. It contains more than 2570 pathways derived from >54 000 publications, making it the largest curated collection of metabolic pathways. The data in MetaCyc is strictly evidence-based and richly curated, resulting in an encyclopedic reference tool for metabolism. MetaCyc is also used as a knowledge base for generating thousands of organism-specific Pathway/Genome Databases (PGDBs), which are available in the BioCyc (https://BioCyc.org) and other PGDB collections. This article provides an update on the developments in MetaCyc during the past two years, including the expansion of data and addition of new features.
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                Author and article information

                Journal
                Database (Oxford)
                Database (Oxford)
                databa
                Database: The Journal of Biological Databases and Curation
                Oxford University Press
                1758-0463
                2018
                18 September 2018
                18 September 2018
                : 2018
                : bay088
                Affiliations
                [1 ]Corn Insects and Crop Genetics Research Unit, USDA-ARS, Ames, IA, USA
                [2 ]Computer Science, Iowa State University, Ames, IA, USA
                [3 ]Horticulture, Washington State University, Pullman, WA, USA
                [4 ]National Agricultural Library, USDA Agricultural Research Service, Beltsville, MD, USA
                [5 ]Cyverse, University of Arizona, Tucson, AZ, USA
                [6 ]Bioversity International, Informatics Unit, Conservation and Availability Programme, Parc Scientifique Agropolis II, Montpellier, France
                [7 ]The Arabidopsis Information Resource, Phoenix Bioinformatics, Fremont, CA, USA
                [8 ]USDA, Plant, Soil and Nutrition Research, Ithaca, NY, USA
                [9 ]Texas Advanced Computing Center, The University of Texas at Austin, Austin, TX, USA
                [10 ]Entomology and Plant Pathology, University of Tennessee Knoxville, Knoxville, TN, USA
                [11 ]Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
                [12 ]Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
                [13 ]Division of Animal Sciences and Division of Plant Sciences, University of Missouri, Columbia, MO, USA
                [14 ]National Center for Genome Resources, Santa Fe, NM, USA
                [15 ]Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA
                [16 ]Animal Science, Iowa State University, Ames, USA
                [17 ]Laboratory of Informatics, Robotics, Microelectronics of Montpellier, University of Montpellier & CNRS, Montpellier, France
                [18 ]DIADE, University of Montpellier, IRD, Montpellier, France
                [19 ]Crop Improvement and Genetics Research Unit, USDA-ARS, Albany, CA, USA
                [20 ]School of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson, AZ, USA
                [21 ]Boyce Thompson Institute, Ithaca, NY, USA
                [22 ]Genomics Division, Lawrence Berkeley National Laboratories, Berkeley, CA, USA
                [23 ]Marriott Library, University of Utah, Salt Lake City, UT, USA
                [24 ]Department of Plant Sciences, University of Saskatchewan, Saskatoon, Canada
                [25 ]Plant Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
                [26 ]Cold Spring Harbor Laboratory, DNA Learning Center, Cold Spring Harbor, NY, USA
                [27 ]Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, USA
                Author notes
                Corresponding author: Tel: 510-220-3339; Email: lisaharper@ 123456me.com , lisa.harper@ 123456ars.usda.gov

                These authors contributed equally to this work and are all first authors.

                Article
                bay088
                10.1093/database/bay088
                6146126
                30239679
                846c1dcd-f864-4a7a-9ad5-9f0a638d3105
                © The Author(s) 2018. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 29 March 2018
                : 19 July 2018
                : 30 July 2018
                Page count
                Pages: 32
                Funding
                Funded by: U.S. Department of Agriculture 10.13039/100000199
                Award ID: 5030-21000-068-00D
                Award ID: 2030-21000-021-00D
                Award ID: 3625-21000-062-00D
                Award ID: 5030-21000-061-00D
                Award ID: 2014-2014-07898
                Award ID: 2014-51181-22376
                Award ID: 2015-70016-23028
                Award ID: 2016-67015-24767
                Award ID: 8062-21000-041-00D
                Award ID: AFRI-005515
                Award ID: NRSP-10
                Award ID: NRSP-8
                Funded by: National Science Foundation 10.13039/100000001
                Award ID: 1443040
                Award ID: 0735191
                Award ID: 1265383
                Award ID: 1444806
                Award ID: 1127112
                Award ID: 1340112
                Award ID: 1444573
                Award ID: 1564366
                Funded by: National Institutes of Health 10.13039/100000002
                Award ID: 5R01HG004483
                Award ID: 5R01GM080203
                Funded by: U.S. Department of Energy 10.13039/100000015
                Award ID: DE-AC02-05CH11231
                Funded by: Bill and Melinda Gates Foundation 10.13039/100000865
                Award ID: OP1052983
                Award ID: OPP1048542
                Funded by: University of Montpellier 10.13039/501100008222
                Award ID: ANR-11-BINF- 0002
                Funded by: Agence Nationale de la Recherche 10.13039/501100001665
                Funded by: Consultative Group for International Agricultural Research
                Funded by: Fondazione Edmund Mach
                Funded by: International Center for Tropical Agriculture 10.13039/501100005346
                Funded by: Research and Innovation Center
                Funded by: The Northern Pulse Growers
                Funded by: US Dry Pea and Lentil Council
                Funded by: The US Land Grant Universities
                Funded by: Washington Tree Fruit Research
                Categories
                Original Article

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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