‹ › ×

    FRED
    • Contact
    • GDPR policy
    • Imprint
    • About
    • Sign Up
    • Login
    • SEARCH
    • Search and find
    • Packages
    • Map
    • By Category ...
      • Study sites
      • Sampling sites
      • Parameters
      • Sampling types
      • Species groups
      • Current DOIs

    528 Chlorophyll-a_iles2016_raw_collection

    Title
    Chlorophyll-a_iles2016_raw_collection
    Period
    2016-08-24 till 2016-11-29
    Period length
    3 months 5 days
    Sampling interval
    Irregular Interval
    Note on interval
    regular every week till mid October, afterwards irregularly
    Description

    Chlorophyll-a data in different size classes (> 3 µm, 0.2-3 µm, 3-20 µm), Acetone extraction

    Keywords
    Chlorophyll-a, different size classes
    Study site
    LakeLab - Experimental Site
    Sampling locations
    LakeLab
    location
    53.1433, 13.0281
    location
    type
    Center point LakeLab
    state
    Experimental outdoor mesocosm facility with in Stechlinsee
    code
    description

    Center point of the LakeLab, an outdoor mesocosm facility within Stechlinsee.

    Contact
    Susanne Stephan
    Licence for data
    All rights reserved. Please send a request to Susanne Stephan if you like to use this data. Mind our data policy: IGB Data Policy
    Project
    ILES 16 Project Website

    Data files (e.g. excel)

    TitlecreatedFiletypeActions
    2017_F7000_ILES_geordnet_nach_Meßtag_incl_Formeln_20180122.xlsx 22. Dec. 2019 08:25 datatable: .xlsx
    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.

    • Chlorophyll-a_iles2016_raw_collection.xml
    • Chlorophyll-a_iles2016_raw_collection.eml

    You are about to leaving FRED and visting a third party website. We are not responsible for the content or availability of linked sites.

    To remain on our site, click Cancel.

    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)