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      CEDAR OnDemand: a browser extension to generate ontology-based scientific metadata

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          Abstract

          Background

          Public biomedical data repositories often provide web-based interfaces to collect experimental metadata. However, these interfaces typically reflect the ad hoc metadata specification practices of the associated repositories, leading to a lack of standardization in the collected metadata. This lack of standardization limits the ability of the source datasets to be broadly discovered, reused, and integrated with other datasets. To increase reuse, discoverability, and reproducibility of the described experiments, datasets should be appropriately annotated by using agreed-upon terms, ideally from ontologies or other controlled term sources.

          Results

          This work presents “CEDAR OnDemand”, a browser extension powered by the NCBO (National Center for Biomedical Ontology) BioPortal that enables users to seamlessly enter ontology-based metadata through existing web forms native to individual repositories. CEDAR OnDemand analyzes the web page contents to identify the text input fields and associate them with relevant ontologies which are recommended automatically based upon input fields’ labels (using the NCBO ontology recommender) and a pre-defined list of ontologies. These field-specific ontologies are used for controlling metadata entry. CEDAR OnDemand works for any web form designed in the HTML format. We demonstrate how CEDAR OnDemand works through the NCBI (National Center for Biotechnology Information) BioSample web-based metadata entry.

          Conclusion

          CEDAR OnDemand helps lower the barrier of incorporating ontologies into standardized metadata entry for public data repositories. CEDAR OnDemand is available freely on the Google Chrome store https://chrome.google.com/webstore/search/CEDAROnDemand

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          Most cited references22

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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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            ChEBI: a database and ontology for chemical entities of biological interest

            Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of molecular entities focused on ‘small’ chemical compounds. The molecular entities in question are either natural products or synthetic products used to intervene in the processes of living organisms. Genome-encoded macromolecules (nucleic acids, proteins and peptides derived from proteins by cleavage) are not as a rule included in ChEBI. In addition to molecular entities, ChEBI contains groups (parts of molecular entities) and classes of entities. ChEBI includes an ontological classification, whereby the relationships between molecular entities or classes of entities and their parents and/or children are specified. ChEBI is available online at http://www.ebi.ac.uk/chebi/
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                Author and article information

                Contributors
                ahmad.chan@yale.edu
                marcosmr@stanford.edu
                sunid@stanford.edu
                attila.egyedi@stanford.edu
                willrett@stanford.edu
                jgraybeal@stanford.edu
                musen@stanford.edu
                kei.cheung@yale.edu
                steven.kleinstein@yale.edu
                Journal
                BMC Bioinformatics
                BMC Bioinformatics
                BMC Bioinformatics
                BioMed Central (London )
                1471-2105
                16 July 2018
                16 July 2018
                2018
                : 19
                : 268
                Affiliations
                [1 ]ISNI 0000000419368710, GRID grid.47100.32, Department of Pathology, , Yale School of Medicine, ; New Haven, CT USA
                [2 ]ISNI 0000000419368710, GRID grid.47100.32, Interdepartmental Program in Computational Biology and Bioinformatics, , Yale University, ; New Haven, CT USA
                [3 ]ISNI 0000000419368710, GRID grid.47100.32, Department of Emergency Medicine and Yale Center for Medical Informatics, , Yale University School of Medicine, ; New Haven, CT USA
                [4 ]ISNI 0000000419368956, GRID grid.168010.e, Stanford Center for Biomedical Informatics Research, , Stanford University, ; Stanford, CA USA
                Author information
                http://orcid.org/0000-0002-6517-5261
                Article
                2247
                10.1186/s12859-018-2247-6
                6048706
                30012108
                7b3921cb-60e1-498a-8045-1f4e157b0b56
                © The Author(s). 2018

                Open Access This 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.

                History
                : 5 September 2017
                : 14 June 2018
                Funding
                Funded by: NIH BIG DATA TO KNOWLEDGE
                Award ID: U54AI117925
                Award Recipient :
                Categories
                Software
                Custom metadata
                © The Author(s) 2018

                Bioinformatics & Computational biology
                ontology,metadata,cedar,fair,bioportal,ncbi,ncbo
                Bioinformatics & Computational biology
                ontology, metadata, cedar, fair, bioportal, ncbi, ncbo

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