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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
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
 

Vocabulary concepts

36,682 concepts found, displaying 32,221 to 32,240.First1,6081,6091,6101,6111,6121,6131,6141,615Last
Id Label Status Status Modified Notation
78410 Moisson Quick edit Valid 2013-05-30 78410
78413 Mondreville Quick edit Valid 2013-05-30 78413
78415 Montainville Quick edit Valid 2013-05-30 78415
78416 Montalet-le-Bois Quick edit Valid 2013-05-30 78416
78417 Montchauvet Quick edit Valid 2013-05-30 78417
78418 Montesson Quick edit Valid 2013-05-30 78418
78420 Montfort-l'Amaury Quick edit Valid 2013-05-30 78420
78423 Montigny-le-Bretonneux Quick edit Valid 2013-05-30 78423
78431 Morainvilliers Quick edit Valid 2013-05-30 78431
78437 Mousseaux-sur-Seine Quick edit Valid 2013-05-30 78437
78439 Mulcent Quick edit Valid 2013-05-30 78439
78440 Les Mureaux Quick edit Valid 2013-05-30 78440
78442 Neauphle-le-Château Quick edit Valid 2013-05-30 78442
78443 Neauphle-le-Vieux Quick edit Valid 2013-05-30 78443
78444 Neauphlette Quick edit Valid 2013-05-30 78444
78451 Nézel Quick edit Valid 2013-05-30 78451
78455 Noisy-le-Roi Quick edit Valid 2013-05-30 78455
78460 Oinville-sur-Montcient Quick edit Valid 2013-05-30 78460
78464 Orcemont Quick edit Valid 2013-05-30 78464
78465 Orgerus Quick edit Valid 2013-05-30 78465
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?