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      The environment ontology in 2016: bridging domains with increased scope, semantic density, and interoperation

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          Abstract

          Background

          The Environment Ontology (ENVO; http://www.environmentontology.org/), first described in 2013, is a resource and research target for the semantically controlled description of environmental entities. The ontology's initial aim was the representation of the biomes, environmental features, and environmental materials pertinent to genomic and microbiome-related investigations. However, the need for environmental semantics is common to a multitude of fields, and ENVO's use has steadily grown since its initial description. We have thus expanded, enhanced, and generalised the ontology to support its increasingly diverse applications.

          Methods

          We have updated our development suite to promote expressivity, consistency, and speed: we now develop ENVO in the Web Ontology Language (OWL) and employ templating methods to accelerate class creation. We have also taken steps to better align ENVO with the Open Biological and Biomedical Ontologies (OBO) Foundry principles and interoperate with existing OBO ontologies. Further, we applied text-mining approaches to extract habitat information from the Encyclopedia of Life and automatically create experimental habitat classes within ENVO.

          Results

          Relative to its state in 2013, ENVO's content, scope, and implementation have been enhanced and much of its existing content revised for improved semantic representation. ENVO now offers representations of habitats, environmental processes, anthropogenic environments, and entities relevant to environmental health initiatives and the global Sustainable Development Agenda for 2030. Several branches of ENVO have been used to incubate and seed new ontologies in previously unrepresented domains such as food and agronomy. The current release version of the ontology, in OWL format, is available at http://purl.obolibrary.org/obo/envo.owl.

          Conclusions

          ENVO has been shaped into an ontology which bridges multiple domains including biomedicine, natural and anthropogenic ecology, ‘omics, and socioeconomic development. Through continued interactions with our users and partners, particularly those performing data archiving and sythesis, we anticipate that ENVO’s growth will accelerate in 2017. As always, we invite further contributions and collaboration to advance the semantic representation of the environment, ranging from geographic features and environmental materials, across habitats and ecosystems, to everyday objects in household settings.

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          Most cited references 58

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          The metagenomics RAST server – a public resource for the automatic phylogenetic and functional analysis of metagenomes

          Background Random community genomes (metagenomes) are now commonly used to study microbes in different environments. Over the past few years, the major challenge associated with metagenomics shifted from generating to analyzing sequences. High-throughput, low-cost next-generation sequencing has provided access to metagenomics to a wide range of researchers. Results A high-throughput pipeline has been constructed to provide high-performance computing to all researchers interested in using metagenomics. The pipeline produces automated functional assignments of sequences in the metagenome by comparing both protein and nucleotide databases. Phylogenetic and functional summaries of the metagenomes are generated, and tools for comparative metagenomics are incorporated into the standard views. User access is controlled to ensure data privacy, but the collaborative environment underpinning the service provides a framework for sharing datasets between multiple users. In the metagenomics RAST, all users retain full control of their data, and everything is available for download in a variety of formats. Conclusion The open-source metagenomics RAST service provides a new paradigm for the annotation and analysis of metagenomes. With built-in support for multiple data sources and a back end that houses abstract data types, the metagenomics RAST is stable, extensible, and freely available to all researchers. This service has removed one of the primary bottlenecks in metagenome sequence analysis – the availability of high-performance computing for annotating the data.
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            Species Distribution Models: Ecological Explanation and Prediction Across Space and Time

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              The FAIR Guiding Principles for scientific data management and stewardship

              There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
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                Author and article information

                Contributors
                pier.buttigieg@awi.de
                Journal
                J Biomed Semantics
                J Biomed Semantics
                Journal of Biomedical Semantics
                BioMed Central (London )
                2041-1480
                23 September 2016
                23 September 2016
                2016
                : 7
                Affiliations
                [1 ]Alfred Wegener Institut, Helmholtz Zentrum für Polar- und Meeresforschung, Am Handelshafen 12, 27570 Bremerhaven, Germany
                [2 ]Institute of Marine Biology Biotechnology and Aquaculture, Hellenic Centre for Marine Research, P.O Box 2214, Heraklion, 71003 Crete Greece
                [3 ]Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
                [4 ]National Center for Ecological Analysis and Synthesis, Univ. of Calif. Santa Barbara, Santa Barbara, CA 93101 USA
                [5 ]CyVerse, Thomas J. Keating Bioresearch Building, 1657 East Helen St, Tucson, AZ 85721 USA
                Article
                97
                10.1186/s13326-016-0097-6
                5035502
                27664130
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: 0753144
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100004963, Seventh Framework Programme;
                Award ID: 287589
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100006132, Office of Science;
                Award ID: DE-AC02-05CH11231
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000936, Gordon and Betty Moore Foundation;
                Award ID: GBMF4491
                Award Recipient :
                Funded by: CyVerse
                Award ID: DBI-0735191
                Funded by: CyVerse
                Award ID: DBI-1265383
                Funded by: LifeWatchGreece Research Infrastructure
                Award ID: 384676-94/GSRT
                Award ID: NSRF(C&E)
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100006132, Office of Science;
                Award ID: DE-AC02-05CH11231
                Award ID: DE-AC02-05CH11231
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000781, European Research Council;
                Award ID: 294757
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2016

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