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    745 EPTO genera of France

    DOI Info:

    • DOI:10.18728/igb-fred-745.1
    • Citation suggestion: Afroditi Grigoropoulou https://orcid.org/0000-0002-7884-097X, Mathieu Floury, Kris Van Looy (2022-07-04 ) EPTO genera of France. IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries. dataset. https://doi.org/10.18728/igb-fred-745.1
    • FRED-datapackage: 625
    • Previous DOI version :10.18728/igb-fred-710.0
    Title
    EPTO genera of France
    Sampling interval
    Irregular Interval
    Description

    Study site: France. Authors: Mathieu Floury & Kris Van Looy. Sampling days available upon communication with Mathieu Floury.

     

    Contact details:

    Mathieu Floury. E-mail: mathieu.floury@univ-lyon1.fr. ORCID: https:/orcid.org/0000-0002-4952-5807. Affiliation: 1) Univ Lyon, Université Claude Bernard Lyon 1, CNRS, ENTPE, UMR 5023 LEHNA, F-69622, Villeurbanne, France 2) Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany.

    Kris Van Looy. E-mail: kris.van-looy@irstea.fr. ORCID: https:/orcid.org/0000-0001-5436-2320. Affiliation: currently OVAM, Belgium.

     

    Study site
    _global
    GeoNode references

    GeoNode layers

    • EPTO_genera_of_France
    Contact
    Afroditi Grigoropoulou
    Licence for data
    This data are made available under the Open Database License:Open Data Commons Attribution License

    Metadata files

    TitleUpload dateFiletypeLicenceActions
    Column_explanation.pdf02. May. 2022 17:20.pdfODC-By Download

    Data files (e.g. excel)

    TitlecreatedFiletypeActions
    EPTO_genera_of_France.csv 04. Jul. 2022 12:35 datatable: .csv Download

    Machine Readable Metadata Files

    Title Upload dateFiletypeLicenseActions
    General_Metadata_EPTO_genera_of_France.xml15. Aug. 2022 18:52xmlODC-By Download
    General_Metadata_EPTO_genera_of_France.eml15. Aug. 2022 18:52emlODC-By Download

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    Parsing data File

    Estimated Time:

    Why does it take so much time?

    While parsing a file, the database has to perform various tasks, some of them needs a lot of CPU and memory for larger files.

    • preprocessing: means automatic detection of headlines, table body, format values or csv-separators
    • copying: means read the file cell by cell and copy all elements to the database. During this format settings can be calculated (for example iso-time)
    • analyzing: check out for different data types (can be time, numeric or text)