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751 IberArtro-TRICHOPTERA

DOI Info:

  • DOI: 10.18728/igb-fred-751.1
  • How to cite: Afroditi Grigoropoulou https://orcid.org/0000-0002-7884-097X, Nuria Bonada, Raul Acosta (2022-07-04 ) IberArtro-TRICHOPTERA. IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries. dataset. https://doi.org/10.18728/igb-fred-751.1
  • Previous DOI version :10.18728/igb-fred-716.0
  • Successor DOI version :10.18728/igb-fred-790.2
  • This Data has been updated! You will be redirected to the latest version within a few seconds. Press STOP to stay on this specific version.

    DOI history

    Date DOI PackageId Note
    2022-05-0310.18728/igb-fred-716.0716
    2022-07-0410.18728/igb-fred-751.1751this package
    2022-11-1510.18728/igb-fred-790.2790 latest
Title
IberArtro-TRICHOPTERA
Sampling interval
Irregular Interval
Description

Study site: Iberian Peninsula. Authors: Núria Bonada & Raúl Acosta.

 

Contact details:

Raúl Acosta. E-mail: racosta@ub.edu. ORCID: https:/orcid.org/0000-0003-0923-8237. Affiliation: University of Barcelona.

Núria Bonada. E-mail: bonada@ub.edu. ORCID: https:/orcid.org/0000-0002-2983-3335. Affiliation: University of Barcelona.

 

Species Groups
Study site
_global
GeoNode references

GeoNode layers

  • IberArtro_TRICHOPTERA0
Contact
Afroditi Grigoropoulou
Licence for data
This data are made available under the Open Database License:Open Data Commons Attribution License

Metadata files

TitleUpload dateFiletypeLicenceActions
Column_explanation.pdf02. May. 2022 18:40.pdfODC-By Download

Data files (e.g. excel)

TitlecreatedFiletypeActions
IberArtro-TRICHOPTERA.csv 04. Jul. 2022 12:56 datatable: .csv Download

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.

  • IberArtro-TRICHOPTERA.xml
  • IberArtro-TRICHOPTERA.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)