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    546 Mueggelsee zooplankton

    DOI Info:

    • DOI:10.18728/546.1
    • Citation suggestion: Rita Adrian https://orcid.org/0000-0002-6318-7189, AG Adrian - (dep. 2) - Langzeitentwicklung von Seen und Klimafolgenforschung (2020-10-08 ) Mueggelsee zooplankton. IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries. dataset. https://doi.org/10.18728/546.1
    • FRED-datapackage: 29
    • Previous DOI version :10.18728/527.0
    • Successor DOI version :10.18728/igb-fred-574.2
    Title
    Mueggelsee zooplankton
    Period
    1979-04-18 till 2018-12-17
    Period length
    39 years 7 months 29 days
    Sampling interval
    7 days Irregular Interval
    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

    Study site
    Müggelsee
    Sampling types
    Zooplankton
    Contact
    Rita Adrian
    Licence for data
    All rights reserved. Please send a request to Rita Adrian if you like to use this data. Mind our data policy: Lakebase Data Policy

    Metadata files

    TitleUpload dateFiletypeLicenceActions
    Metadata_weekly_sampling_Müggelsee.pdf27. Apr. 2017 09:54.pdfODC-By Download

    Data files (e.g. excel)

    TitlecreatedFiletypeActions
    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

    Title Upload dateFiletypeLicenseActions
    General_Metadata_Mueggelsee_zooplankton.xml15. Aug. 2022 18:29xmlODC-By Download
    General_Metadata_Mueggelsee_zooplankton.eml15. Aug. 2022 18:29emlODC-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)