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    612 Phytoplankton at Lake Stechlin

    DOI Info:

    • DOI: 10.18728/igb-fred-612.0
    • Citation suggestion: Silke Schmidt (2021-12-01 ) Phytoplankton at Lake Stechlin. IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries. dataset. https://doi.org/10.18728/igb-fred-612.0
    • DOI history

      Date DOI PackageId Note
      2021-12-0110.18728/igb-fred-612.0612this package latest
    Title
    Phytoplankton at Lake Stechlin
    Period
    1994-01-01 till 2020-12-31
    Period length
    26 years 11 months 30 days
    Sampling interval
    14 days Irregular Interval
    Description

    Phytoplankton taxa at Lake Stechlin

    Keywords
    phytoplankton, taxa, species
    Study site
    Lake Stechlin
    Contact
    Sabine Wollrab
    Licence for data
    All rights reserved. Please send a request to Sabine Wollrab if you like to use this data. Mind our data policy: IGB Data Policy

    Metadata files

    TitleUpload dateFiletypeLicenceActions
    Phytoplankton_Stechlin.pdf01. Dec. 2021 15:24.pdfODC-By Download

    Data files (e.g. excel)

    TitlecreatedFiletypeActions
    phytoplankton_Stechlin_wide.csv 01. Dec. 2021 15:24 datatable: .csv
    Error: To access file, please get in touch with the contact person.

    Machine Readable Metadata Files

    FRED provides all metadata of this package in a maschine readable format. There is a pure XML file and one EML file in Ecological Metadata Language. Both files are published under the freeODC-ByLicence.

    • Phytoplankton_at_Lake_Stechlin.xml
    • Phytoplankton_at_Lake_Stechlin.eml

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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)