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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

Species Groups
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.pdf 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 free CC BY 4.0 Licence.

  • 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)