Technical Metadata

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The Experts below are selected from a list of 261 Experts worldwide ranked by ideXlab platform

George Sanger - One of the best experts on this subject based on the ideXlab platform.

Matthias Lange - One of the best experts on this subject based on the ideXlab platform.

  • PGP Repository: A Plant Phenomics and Genomics Data Publication Infrastructure
    Database : the journal of biological databases and curation, 2016
    Co-Authors: Daniel Arend, Astrid Junker, Uwe Scholz, Danuta Schüler, Juliane Wylie, Matthias Lange
    Abstract:

    Plant genomics and phenomics represents the most promising tools for accelerating yield gains and overcoming emerging crop productivity bottlenecks. However, accessing this wealth of plant diversity requires the characterization of this material using state-of-the-art genomic, phenomic and molecular technologies and the release of subsequent research data via a long-term stable, open-access portal. Although several international consortia and public resource centres offer services for plant research data management, valuable digital assets remains unpublished and thus inaccessible to the scientific community. Recently, the Leibniz Institute of Plant Genetics and Crop Plant Research and the German Plant Phenotyping Network have jointly initiated the Plant Genomics and Phenomics Research Data Repository (PGP) as infrastructure to comprehensively publish plant research data. This covers in particular cross-domain datasets that are not being published in central repositories because of its volume or unsupported data scope, like image collections from plant phenotyping and microscopy, unfinished genomes, genotyping data, visualizations of morphological plant models, data from mass spectrometry as well as software and documents.The repository is hosted at Leibniz Institute of Plant Genetics and Crop Plant Research using e!DAL as software infrastructure and a Hierarchical Storage Management System as data archival backend. A novel developed data submission tool was made available for the consortium that features a high level of automation to lower the barriers of data publication. After an internal review process, data are published as citable digital object identifiers and a core set of Technical Metadata is registered at DataCite. The used e!DAL-embedded Web frontend generates for each dataset a landing page and supports an interactive exploration. PGP is registered as research data repository at BioSharing.org, re3data.org and OpenAIRE as valid EU Horizon 2020 open data archive. Above features, the programmatic interface and the support of standard Metadata formats, enable PGP to fulfil the FAIR data principles-findable, accessible, interoperable, reusable.Database URL:http://edal.ipk-gatersleben.de/repos/pgp/.

Dunja Mladenic - One of the best experts on this subject based on the ideXlab platform.

  • A framework for acquiring semantic sensor descriptions
    2012
    Co-Authors: Luka Bradesko, Alexandra Moraru, Blaz Fortuna, Carolina Fortuna, Dunja Mladenic
    Abstract:

    There has been great effort in developing ontologies for modeling sensor networks, describing various types of sensors and their context. However, when faced with a large scale deployment, the process of acquiring and managing semantic sensor Metadata is challenging. This paper focuses on acquiring contextual Metadata of sensors, such as location and surrounding environment, as opposed to Technical Metadata which can be derived from sensor's firmware. More specifically, the paper proposes a framework for collecting contextual Metadata information with help of the mobile devices, which allows usage on the deployment site and as such lowers the cost.

  • SSN - A Framework for Acquiring Semantic Sensor Descriptions (Short Paper).
    2012
    Co-Authors: Luka Bradesko, Alexandra Moraru, Blaz Fortuna, Carolina Fortuna, Dunja Mladenic
    Abstract:

    There has been great effort in developing ontologies for modeling sensor networks, describing various types of sensors and their context. However, when faced with a large scale deployment, the process of acquiring and managing semantic sensor Metadata is challenging. This paper focuses on acquiring contextual Metadata of sensors, such as location and surrounding environment, as opposed to Technical Metadata which can be derived from sensor’s firmware. More specifically, the paper proposes a framework for collecting contextual Metadata information with help of the mobile devices, which allows usage on the deployment site and as such lowers the cost.

Daniel Arend - One of the best experts on this subject based on the ideXlab platform.

  • PGP Repository: A Plant Phenomics and Genomics Data Publication Infrastructure
    Database : the journal of biological databases and curation, 2016
    Co-Authors: Daniel Arend, Astrid Junker, Uwe Scholz, Danuta Schüler, Juliane Wylie, Matthias Lange
    Abstract:

    Plant genomics and phenomics represents the most promising tools for accelerating yield gains and overcoming emerging crop productivity bottlenecks. However, accessing this wealth of plant diversity requires the characterization of this material using state-of-the-art genomic, phenomic and molecular technologies and the release of subsequent research data via a long-term stable, open-access portal. Although several international consortia and public resource centres offer services for plant research data management, valuable digital assets remains unpublished and thus inaccessible to the scientific community. Recently, the Leibniz Institute of Plant Genetics and Crop Plant Research and the German Plant Phenotyping Network have jointly initiated the Plant Genomics and Phenomics Research Data Repository (PGP) as infrastructure to comprehensively publish plant research data. This covers in particular cross-domain datasets that are not being published in central repositories because of its volume or unsupported data scope, like image collections from plant phenotyping and microscopy, unfinished genomes, genotyping data, visualizations of morphological plant models, data from mass spectrometry as well as software and documents.The repository is hosted at Leibniz Institute of Plant Genetics and Crop Plant Research using e!DAL as software infrastructure and a Hierarchical Storage Management System as data archival backend. A novel developed data submission tool was made available for the consortium that features a high level of automation to lower the barriers of data publication. After an internal review process, data are published as citable digital object identifiers and a core set of Technical Metadata is registered at DataCite. The used e!DAL-embedded Web frontend generates for each dataset a landing page and supports an interactive exploration. PGP is registered as research data repository at BioSharing.org, re3data.org and OpenAIRE as valid EU Horizon 2020 open data archive. Above features, the programmatic interface and the support of standard Metadata formats, enable PGP to fulfil the FAIR data principles-findable, accessible, interoperable, reusable.Database URL:http://edal.ipk-gatersleben.de/repos/pgp/.

Luka Bradesko - One of the best experts on this subject based on the ideXlab platform.

  • A framework for acquiring semantic sensor descriptions
    2012
    Co-Authors: Luka Bradesko, Alexandra Moraru, Blaz Fortuna, Carolina Fortuna, Dunja Mladenic
    Abstract:

    There has been great effort in developing ontologies for modeling sensor networks, describing various types of sensors and their context. However, when faced with a large scale deployment, the process of acquiring and managing semantic sensor Metadata is challenging. This paper focuses on acquiring contextual Metadata of sensors, such as location and surrounding environment, as opposed to Technical Metadata which can be derived from sensor's firmware. More specifically, the paper proposes a framework for collecting contextual Metadata information with help of the mobile devices, which allows usage on the deployment site and as such lowers the cost.

  • SSN - A Framework for Acquiring Semantic Sensor Descriptions (Short Paper).
    2012
    Co-Authors: Luka Bradesko, Alexandra Moraru, Blaz Fortuna, Carolina Fortuna, Dunja Mladenic
    Abstract:

    There has been great effort in developing ontologies for modeling sensor networks, describing various types of sensors and their context. However, when faced with a large scale deployment, the process of acquiring and managing semantic sensor Metadata is challenging. This paper focuses on acquiring contextual Metadata of sensors, such as location and surrounding environment, as opposed to Technical Metadata which can be derived from sensor’s firmware. More specifically, the paper proposes a framework for collecting contextual Metadata information with help of the mobile devices, which allows usage on the deployment site and as such lowers the cost.