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    583 Biodiversity in time and space (Statistical modeling and data analysis)

    Title
    Biodiversity in time and space (Statistical modeling and data analysis)
    Period
    2019-02-14 till 2022-04-30
    Period length
    3 years 2 months 16 days
    Description

    The data of this work package were published on zenodo and can be reached via the following dois:

     

    Benjamin Kraemer. (2019, August 8). bkraemer/GlobalLakeLevels: GlobalLakeLevels (Version v1.0-beta.1). Zenodo. http://doi.org/10.5281/zenodo.3363187. R Code for calculating trends in water levels in large lakes using satellite altimetry data reprocessed by the USDA

    Karan Kakouei. (2021). Phytoplankton and cyanobacteria abundances in mid‐21st century lakes depend strongly on future land use and climate projections [Data set]. https://doi.org/10.1111/gcb.15866

    Keywords
    Biodiversity, Statistical modeling, GlobalLakeLevels, Phytoplankton, cyanobacteria, abundances
    Study site
    _multiple sites
    Contact
    Benjamin Kraemer, Karan Kakouei, Rita Adrian
    Licence for data
    All rights reserved. Please send a request to Benjamin Kraemer, Karan Kakouei, Rita Adrian if you like to use this data. Mind our data policy: IGB Data Policy
    Project
    LimnoScenES Project Website

    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.

    • Biodiversity_in_time_and_space_(Statistical_modeling_and_data_analysis).xml
    • Biodiversity_in_time_and_space_(Statistical_modeling_and_data_analysis).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)