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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 3,081 to 3,100.First151152153154155156157158Last
Id Label Status Status Modified Notation
DE2844305 Großer Boberowsee (MV) Quick edit Valid 2018-01-19 DE2844305
DE2845301 Stolpseewiesen-Siggelhavel Quick edit Valid 2018-01-19 DE2845301
DE2846301 Kleine Schorfheide - Havel Quick edit Valid 2018-01-19 DE2846301
DE2846302 Templiner Kanalwiesen Quick edit Valid 2018-01-19 DE2846302
DE2846323 Fledermausquartier Brauerei Templin Quick edit Valid 2018-01-19 DE2846323
DE2847301 Großer Briesensee Quick edit Valid 2018-01-19 DE2847301
DE2847302 Labüskewiesen Quick edit Valid 2018-01-19 DE2847302
DE2847303 Kölpinsee Quick edit Valid 2018-01-19 DE2847303
DE2847304 Platkowsee-Netzowsee-Metzelthin Quick edit Valid 2018-01-19 DE2847304
DE2847325 Lübbesee Ergänzung Quick edit Valid 2018-01-19 DE2847325
DE2848301 Arnimswalde Quick edit Valid 2018-01-19 DE2848301
DE2848302 Eulenberge Quick edit Valid 2018-01-19 DE2848302
DE2848303 Kronhorst-Groß Fredenwalde Quick edit Valid 2018-01-19 DE2848303
DE2848304 Schwemmpfuhl Quick edit Valid 2018-01-19 DE2848304
DE2848305 Poratzer Moränenlandschaft Ergänzung Quick edit Valid 2018-01-19 DE2848305
DE2849301 Hintenteiche bei Biesenbrow Quick edit Valid 2018-01-19 DE2849301
DE2849302 Melzower Forst Quick edit Valid 2018-01-19 DE2849302
DE2849303 Suckower Haussee Quick edit Valid 2018-01-19 DE2849303
DE2849304 Steinhöfel-Schmiedeberg-Friedrichsfelde Quick edit Valid 2018-01-19 DE2849304
DE2849325 Oberückersee Quick edit Valid 2018-01-19 DE2849325
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?