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    29 Müggelsee zooplankton

    Title
    Müggelsee zooplankton
    Period
    1979-04-18 till 2018-12-17
    Period length
    39 years 7 months 29 days
    Sampling interval
    7 days
    Description

    Daphnia longispina - female, adult with asexual eggs.jpg

    Image.: https://commons.wikimedia.org/wiki/File:Daphnia_longispina_-_female,_adult_with_asexual_eggs.jpg - Dieter Ebert,

     

    Zooplankton count of Mueggelsee weekly sampling long term program. 1979 - 2015 weekly data

    Mesh 30 µm

    Keywords
    zooplankton, rotifers, rotatoria, daphnia, copepod, mueggelsee, nauplia
    Study site
    Müggelsee
    Sampling types
    Zooplankton
    Contact
    Jan Köhler
    Licence for data
    All rights reserved. Please send a request to Jan Köhler if you like to use this data. Mind our data policy: Lakebase Data Policy
    Current doi
    10.18728/igb-fred-574.2

    Metadata files

    TitleUpload dateFiletypeLicenceActions
    Zooplankton_LT_Müggelsee_Metadata.pdf03. Feb. 2021 16:43.pdfODC-By Download

    Data files (e.g. excel)

    TitlecreatedFiletypeActions
    zooplankton_size_1982-1992.zip 24. Feb. 2021 09:58 datatable: .zip
    Error: To access file, please get in touch with the contact person.
    zooplankton_long_table_1979-2018.csv 13. Mar. 2019 13:54 datatable: .csv
    Error: To access file, please get in touch with the contact person.
    zooplankton_wide_table_1979-2018.csv 13. Mar. 2019 13:40 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.

    • Müggelsee_zooplankton.xml
    • Müggelsee_zooplankton.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)