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Eionet
Data Dictionary
Edit vocabulary

Edit vocabulary

Folder Mandatory
Identifier Mandatory
Label Mandatory
Base URI Optional
Registration status Mandatory
Type Mandatory Common
Numeric concept identifiers Mandatory
Optional
Definition Optional
Version Optional
Source Optional
License Optional
 

Bound elements for concepts

Element Type Status
inCountry Vocabulary
Released
  • Step 1
  • Step 2
  • Step 3
  • Step 4
  • Step 5
29 Aug 2014
skos:broadMatch Quantitative
Released
  • Step 1
  • Step 2
  • Step 3
  • Step 4
  • Step 5
30 Sep 2013

Add new data elements

Mandatory
Mandatory
Optional
Optional (forcefully equal to identifier in this vocabulary)
 

Vocabulary concepts

28,131 concepts found, displaying 2,981 to 3,000.First146147148149150151152153Last
Id Label Status Status Modified Notation
DE2740301 Oberheide Quick edit Valid 2018-01-19 DE2740301
DE2741301 Berlinchener See, Berlinchener Luch Quick edit Valid 2018-01-19 DE2741301
DE2741302 Mönchsee Quick edit Valid 2018-01-19 DE2741302
DE2741401 Buchholzer-Krümmeler Heide Quick edit Valid 2018-01-19 DE2741401
DE2742301 Krümmeler Heide Quick edit Valid 2018-01-19 DE2742301
DE2742302 Mirower Holm Quick edit Valid 2018-01-19 DE2742302
DE2743304 Kleinseenlandschaft zwischen Mirow und Wustrow Quick edit Valid 2018-01-19 DE2743304
DE2744301 Thymen Quick edit Valid 2018-01-19 DE2744301
DE2744302 Schwarzer See Quick edit Valid 2018-01-19 DE2744302
DE2744307 Moore und Seen bei Wesenberg Quick edit Valid 2018-01-19 DE2744307
DE2744308 Wangnitzsee Quick edit Valid 2018-01-19 DE2744308
DE2744309 Schwarzer See östlich Priepert (MV) Quick edit Valid 2018-01-19 DE2744309
DE2745301 Klapperberge Quick edit Valid 2018-01-19 DE2745301
DE2745302 Hutung Sähle Quick edit Valid 2018-01-19 DE2745302
DE2745303 Kastavenseen-Molkenkammersee Quick edit Valid 2018-01-19 DE2745303
DE2745371 Sandergebiet südlich von Serrahn Quick edit Valid 2018-01-19 DE2745371
DE2746301 Hardenbeck-Küstrinchen Quick edit Valid 2018-01-19 DE2746301
DE2746302 Krüselinsee und Mechowseen Quick edit Valid 2018-01-19 DE2746302
DE2746401 Uckermärkische Seenlandschaft Quick edit Valid 2018-01-19 DE2746401
DE2747302 Stromgewässer Quick edit Valid 2018-01-19 DE2747302
CSV Import

The CSV file should contain a header row for element names and data rows for concepts.
It is strongly recommended to use an exported CSV file as a template for bulk editing. Columns and rows can be added to or deleted from the template file.
A concept can be ignored by prepending a double-slash '//' to the concept row in the CSV
    Notes:
  • If the header row contains unknown elements the import will aborted and data will be rolled back
  • Erroneous concept rows are ignored, valid data rows are still imported
  • Successful import cannot be undone (unless "undo checkout" is performed)
  • If a concept with the same identifier already exists in the vocabulary it will be overwritten
  • "Purge Vocabulary" option deletes all the vocabulary concepts before import
Note
  • With this operation, contents of RDF file will be imported into vocabulary folder.
  • Only a working copy can be updated with a RDF file upload.
  • If user select "Purge Per Predicate" option. All seen predicates will be removed from vocabulary.
  • If user select "Purge All Vocabulary Data" option. All data will be removed from vocabulary.
  • Once import is successful, operation cannot be undone. If an error occurs during import, then all data will be rolled back.
In this case, existing vocabulary information will be updated with information from imported concepts.
In this case, predicates of existing concepts will be replaced with the imported predicates.
In this case, all existing concepts will be removed and the imported concepts will be added.
In this case, all imported concepts will be removed from the vocabulary.
How to handle missing concepts?