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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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          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 references 27

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          The most unique feature of Earth is the existence of life, and the most extraordinary feature of life is its diversity. Approximately 9 million types of plants, animals, protists and fungi inhabit the Earth. So, too, do 7 billion people. Two decades ago, at the first Earth Summit, the vast majority of the world's nations declared that human actions were dismantling the Earth's ecosystems, eliminating genes, species and biological traits at an alarming rate. This observation led to the question of how such loss of biological diversity will alter the functioning of ecosystems and their ability to provide society with the goods and services needed to prosper.
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            Quantitative scenarios are coming of age as a tool for evaluating the impact of future socioeconomic development pathways on biodiversity and ecosystem services. We analyze global terrestrial, freshwater, and marine biodiversity scenarios using a range of measures including extinctions, changes in species abundance, habitat loss, and distribution shifts, as well as comparing model projections to observations. Scenarios consistently indicate that biodiversity will continue to decline over the 21st century. However, the range of projected changes is much broader than most studies suggest, partly because there are major opportunities to intervene through better policies, but also because of large uncertainties in projections.
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                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                3 March 2014
                : 9
                : 3
                [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
                King Abdullah University of Science and Technology, Saudi Arabia
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Wrote the paper: RW RB PLB JD RG NM. Edited, revised, critiqued, and wrote small sections of the manuscript: S. Baskauf S. Blum S. Bowers ND DE MAG RH AJ LK AM PM ÉÓT MS B. Smith B. Stucky AT J. Wieczorek J. Whitacre J. Wooley. Developed Biological Collections Ontology: RW RB S. Blum S. Bowers PLB JD DE MAG RH AJ LK AM NM ÉÓT MS B. Smith B. Stucky AT J. Wieczorek J. Whitacre. Developed Environment Ontology: PLB NM. Developed Population and Community Ontology: RW B. Smith PM. Designed ontology framework: B. Smith. Developed Darwin-SW: S. Baskauf.


                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Pages: 13
                We gratefully acknowledge the support from the US National Science Foundation (NSF - through the following grants: Research Coordination Network for Genomic Standards Consortium (DBI-0840989), EAGER: An Interoperable Information Infrastructure for Biodiversity Research (IIS-1255035), Collaborative Research: BiSciCol Tracker: Towards a tagging and tracking infrastructure for biodiversity science collections (DBI: 0956371, 0956350, 0956426), Collaborative Research: Data Integration for Repository Services in Biodiversity Informatics (DBI-0851313), and the National Institutes of Health (NIH - through a grant to the National Center for Biomedical Ontology (U54 HG004028). RW is supported by DBI-0735191 (The iPlant Collaborative). PLB is supported by the European Commission under Grant Agreement n° 287589 (MicroB3). NM is supported by the European Commission 7th Framework Programme (FP7) as part of its e-Infrastructures activity (Grant no. 283359, BioVeL). Any opinions, findings, conclusions, or recommendations expressed in this report are those of the participants and do not necessarily represent the official views, opinions, or policy of the National Science Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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