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    600 Upper Lake Nehmitz ice observations 2008-2020

    DOI Info:

    • DOI:10.18728/igb-fred-600.0
    • Citation suggestion: Silke Schmidt (2021-11-24 ) Upper Lake Nehmitz ice observations 2008-2020. IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries. dataset. https://doi.org/10.18728/igb-fred-600.0
    • FRED-datapackage: 599
    Title
    Upper Lake Nehmitz ice observations 2008-2020
    Period
    2008-12-01 till 2020-03-31
    Period length
    11 years 3 months 30 days
    Sampling interval
    Irregular Interval
    Description

    Ice observations at Upper Lake Nehmitz including percentage of ice cover and percentage of snow cover on ice in the years 2008-2020.

    Keywords
    ice, snow, ice cover, snow cover
    Study site
    Lake Nehmitz
    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
    Eis_Metadata_2008-2020_Nehmitz.pdf24. Nov. 2021 14:21.pdfODC-By Download

    Data files (e.g. excel)

    TitlecreatedFiletypeActions
    Eis_Nehmitz_2008-2020.csv 24. Nov. 2021 14:21 datatable: .csv
    Error: To access file, please get in touch with the contact person.

    Machine Readable Metadata Files

    Title Upload dateFiletypeLicenseActions
    General_Metadata_Upper_Lake_Nehmitz_ice_observations_2008-2020.xml01. Oct. 2022 23:43xmlODC-By Download
    General_Metadata_Upper_Lake_Nehmitz_ice_observations_2008-2020.eml01. Oct. 2022 23:43emlODC-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)