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  • 1
    Publication Date: 2022-05-26
    Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biodiversity Data Journal 5 (2017): e10989, doi:10.3897/BDJ.5.e10989.
    Description: The Ocean Biogeographic Information System (OBIS) is the world’s most comprehensive online, open-access database of marine species distributions. OBIS grows with millions of new species observations every year. Contributions come from a network of hundreds of institutions, projects and individuals with common goals: to build a scientific knowledge base that is open to the public for scientific discovery and exploration and to detect trends and changes that inform society as essential elements in conservation management and sustainable development. Until now, OBIS has focused solely on the collection of biogeographic data (the presence of marine species in space and time) and operated with optimized data flows, quality control procedures and data standards specifically targeted to these data. Based on requirements from the growing OBIS community to manage datasets that combine biological, physical and chemical measurements, the OBIS-ENV-DATA pilot project was launched to develop a proposed standard and guidelines to make sure these combined datasets can stay together and are not, as is often the case, split and sent to different repositories. The proposal in this paper allows for the management of sampling methodology, animal tracking and telemetry data, biological measurements (e.g., body length, percent live cover, ...) as well as environmental measurements such as nutrient concentrations, sediment characteristics or other abiotic parameters measured during sampling to characterize the environment from which biogeographic data was collected. The recommended practice builds on the Darwin Core Archive (DwC-A) standard and on practices adopted by the Global Biodiversity Information Facility (GBIF). It consists of a DwC Event Core in combination with a DwC Occurrence Extension and a proposed enhancement to the DwC MeasurementOrFact Extension. This new structure enables the linkage of measurements or facts - quantitative and qualitative properties - to both sampling events and species occurrences, and includes additional fields for property standardization. We also embrace the use of the new parentEventID DwC term, which enables the creation of a sampling event hierarchy. We believe that the adoption of this recommended practice as a new data standard for managing and sharing biological and associated environmental datasets by IODE and the wider international scientific community would be key to improving the effectiveness of the knowledge base, and will enhance integration and management of critical data needed to understand ecological and biological processes in the ocean, and on land.
    Keywords: Darwin Core Archive ; Sample event ; Species occurrence ; Environmental data ; Ecosystem data ; Telemetry data ; Data standardisation ; Oceanographic data
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-10-21
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Tanhua, T., Pouliquen, S., Hausman, J., O'Brien, K., Bricher, P., de Bruin, T., Buck, J. J. H., Burger, E. F., Carval, T., Casey, K. S., Diggs, S., Giorgetti, A., Glaves, H., Harscoat, V., Kinkade, D., Muelbert, J. H., Novellino, A., Pfeil, B., Pulsifer, P. L., Van de Putte, A., Robinson, E., Schaap, D., Smirnov, A., Smith, N., Snowden, D., Spears, T., Stall, S., Tacoma, M., Thijsse, P., Tronstad, S., Vandenberghe, T., Wengren, M., Wyborn, L., & Zhao, Z. Ocean FAIR data services. Frontiers in Marine Science, 6, (2019): 440, doi:10.3389/fmars.2019.00440.
    Description: Well-founded data management systems are of vital importance for ocean observing systems as they ensure that essential data are not only collected but also retained and made accessible for analysis and application by current and future users. Effective data management requires collaboration across activities including observations, metadata and data assembly, quality assurance and control (QA/QC), and data publication that enables local and interoperable discovery and access and secures archiving that guarantees long-term preservation. To achieve this, data should be findable, accessible, interoperable, and reusable (FAIR). Here, we outline how these principles apply to ocean data and illustrate them with a few examples. In recent decades, ocean data managers, in close collaboration with international organizations, have played an active role in the improvement of environmental data standardization, accessibility, and interoperability through different projects, enhancing access to observation data at all stages of the data life cycle and fostering the development of integrated services targeted to research, regulatory, and operational users. As ocean observing systems evolve and an increasing number of autonomous platforms and sensors are deployed, the volume and variety of data increase dramatically. For instance, there are more than 70 data catalogs that contain metadata records for the polar oceans, a situation that makes comprehensive data discovery beyond the capacity of most researchers. To better serve research, operational, and commercial users, more efficient turnaround of quality data in known formats and made available through Web services is necessary. In particular, automation of data workflows will be critical to reduce friction throughout the data value chain. Adhering to the FAIR principles with free, timely, and unrestricted access to ocean observation data is beneficial for the originators, has obvious benefits for users, and is an essential foundation for the development of new services made possible with big data technologies.
    Description: We thank the funding agencies and the data management projects that have made this work possible through dedicated funding for the data management activities and improvements. TT and JB acknowledge support from the EU Horizon 2020 project AtlantOS (grant agreement 633211). JM acknowledges support from the Integrated Oceanography and Multiple Uses of the Continental Shelf and the Adjacent Ocean Integrated Center of Oceanography (INCT-Mar COI, CNPq, Proc. 565062/2010-7). DS acknowledges support from the H2020 project SeaDataCloud (grant agreement 730960). SP acknowledges support from the EU Horizon 2020 project ENVRIplus (grant agreement 654182). AN acknowledges support from the EMODnet Physics (grant number EASME/EMFF/2016/1.3.1.2-Lot3/SI2.749411). HG acknowledges funding from the EU H2020 Ocean Data Interoperability Platform (ODIP) project (Grant No: 654310). JH acknowledges that funding came from the National Aeronautics and Space Agency as managed by the California Institute of Technology under task number 80NM0018F0848. AVdP acknowledges support from Belspo in the framework the EU Lifewatch ERIC (grant agreement FR/36/AN3). KO’B acknowledges that his publication is partially funded by the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA15OAR4320063, Contribution No. 2018-0175.
    Keywords: FAIR ; Ocean ; Data management ; Data services ; Ocean observing ; Standardization ; Interoperability
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Limitation Availability
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