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      Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies.

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          Abstract

          The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers.

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          Most cited references22

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          Creating the gene ontology resource: design and implementation.

          (2001)
          The exponential growth in the volume of accessible biological information has generated a confusion of voices surrounding the annotation of molecular information about genes and their products. The Gene Ontology (GO) project seeks to provide a set of structured vocabularies for specific biological domains that can be used to describe gene products in any organism. This work includes building three extensive ontologies to describe molecular function, biological process, and cellular component, and providing a community database resource that supports the use of these ontologies. The GO Consortium was initiated by scientists associated with three model organism databases: SGD, the Saccharomyces Genome database; FlyBase, the Drosophila genome database; and MGD/GXD, the Mouse Genome Informatics databases. Additional model organism database groups are joining the project. Each of these model organism information systems is annotating genes and gene products using GO vocabulary terms and incorporating these annotations into their respective model organism databases. Each database contributes its annotation files to a shared GO data resource accessible to the public at http://www.geneontology.org/. The GO site can be used by the community both to recover the GO vocabularies and to access the annotated gene product data sets from the model organism databases. The GO Consortium supports the development of the GO database resource and provides tools enabling curators and researchers to query and manipulate the vocabularies. We believe that the shared development of this molecular annotation resource will contribute to the unification of biological information.
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            Molecular biological access to the chemistry of unknown soil microbes: a new frontier for natural products.

            Cultured soil microorganisms have provided a rich source of natural-product chemistry. Because only a tiny fraction of soil microbes from soil are readily cultured, soil might be the greatest untapped resource for novel chemistry. The concept of cloning the metagenome to access the collective genomes and the biosynthetic machinery of soil microflora is explored here.
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              Is Open Access

              The Genomic Standards Consortium

              A vast and rich body of information has grown up as a result of the world's enthusiasm for 'omics technologies. Finding ways to describe and make available this information that maximise its usefulness has become a major effort across the 'omics world. At the heart of this effort is the Genomic Standards Consortium (GSC), an open-membership organization that drives community-based standardization activities, Here we provide a short history of the GSC, provide an overview of its range of current activities, and make a call for the scientific community to join forces to improve the quality and quantity of contextual information about our public collections of genomes, metagenomes, and marker gene sequences.
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                Author and article information

                Journal
                PLoS ONE
                PloS one
                Public Library of Science (PLoS)
                1932-6203
                1932-6203
                2014
                : 9
                : 3
                Affiliations
                [1 ] The iPlant Collaborative, University of Arizona, Tucson, Arizona, United States of America.
                [2 ] University of California, Berkeley, Berkeley, California, United States of America.
                [3 ] Department of Ecology and Evolutionary Biology and the CU Museum of Natural History, University of Colorado at Boulder, Boulder, Colorado, United States of America.
                [4 ] Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States of America.
                [5 ] University of Florida, Florida Museum of Natural History, Gainesville, Florida, United States of America.
                [6 ] Research Informatics, California Academy of Sciences, San Francisco, California, United States of America.
                [7 ] Gonzaga University, Computer Science, Spokane, Washington, United States of America.
                [8 ] Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany.
                [9 ] University of California, Berkeley, Gump South Pacific Research Station, Moorea, French Polynesia.
                [10 ] GBIF Norway, Natural History Museum, University in Oslo, Oslo, Norway.
                [11 ] LH Bailey Hortorium, Department of Plant Biology, Cornell University, Ithaca, New York, United States of America.
                [12 ] Biodiversity Institute of Ontario, University of Guelph, Guelph, ON, Canada.
                [13 ] School of Information Resources and Library Science, University of Arizona, Tucson, Arizona, United States of America.
                [14 ] Biodiversity Institute and Ecology & Evolutionary Biology, The University of Kansas, Lawrence, Kansas, United States of America.
                [15 ] University of Florida, Gainesville, Florida, United States of America.
                [16 ] Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas, United States of America.
                [17 ] The BioVeL Project, School of Computer Science, The University of Manchester, Manchester, United Kingdom.
                [18 ] GBIF Secretariat, Copenhagen, Denmark.
                [19 ] National Center for Ecological Analysis and Synthesis, Santa Barbara, California, United States of America.
                [20 ] Department of Philosophy, University at Buffalo, Buffalo, New York, United States of America.
                [21 ] Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado, United States of America.
                [22 ] Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America.
                [23 ] 3101 VLSB, Museum of Vertebrate Zoology, University of California, Berkeley, Berkeley, California, United States of America.
                [24 ] Informatics Branch, Information Technology Office, National Museum of Natural History, Smithsonian Institution, Washington, DC, United States of America.
                [25 ] University of California San Diego, La Jolla, California, United States of America.
                Article
                PONE-D-13-23846
                10.1371/journal.pone.0089606
                3940615
                24595056
                51738a1f-543d-4e17-9e38-06c877bb8426
                History

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