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    749 Odonata of Aoos basin in Greece

    DOI Info:

    • DOI:10.18728/igb-fred-749.1
    • Citation suggestion: Afroditi Grigoropoulou https://orcid.org/0000-0002-7884-097X, Vassiliki Kati, Nikos Boukas (2022-07-04 ) Odonata of Aoos basin in Greece. IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries. dataset. https://doi.org/10.18728/igb-fred-749.1
    • FRED-datapackage: 673
    • Previous DOI version :10.18728/igb-fred-714.0
    Title
    Odonata of Aoos basin in Greece
    Sampling interval
    Irregular Interval
    Description

    Study site: Greece. Authors: Vassiliki Kati & Nikos Boukas. @ BCL  (Biodiversity Conservation Lab). Boukas N., Kati V. 2021. Inventory of Odonata species in Aoos river basin in Greece. University of Ioannina. Funding by Pindos Perivallontiki (Mava Foundation).

     

    Contact details:

    Vassiliki Kati. E-mail: vkati@uoi.gr. ORCID: https:/orcid.org/0000-0003-3357-4556. Affiliation: University of Ioannina.

    Nikos Boukas. E-mail: bionickbukas@hotmail.com.  Affiliation: University of Ioannina.

     

     

    Study site
    _global
    GeoNode references

    GeoNode layers

    • Odonata_of_Aoos_basin_in_Greece
    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 17:54.pdfODC-By Download

    Data files (e.g. excel)

    TitlecreatedFiletypeActions
    Odonata_of_Aoos_basin_in_Greece.csv 04. Jul. 2022 12:46 datatable: .csv Download

    Machine Readable Metadata Files

    Title Upload dateFiletypeLicenseActions
    General_Metadata_Odonata_of_Aoos_basin_in_Greece.xml15. Aug. 2022 18:08xmlODC-By Download
    General_Metadata_Odonata_of_Aoos_basin_in_Greece.eml15. Aug. 2022 18:08emlODC-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)