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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
owl:sameAs Quantitative
Released
  • Step 1
  • Step 2
  • Step 3
  • Step 4
  • Step 5
30 Sep 2013
skos:exactMatch 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

4,043 concepts found, displaying 1,681 to 1,700.First8182838485868788Last
Id Label Status Status Modified Notation
FR245 Loir-et-Cher (NUTS 2013) Quick edit Valid 2013-09-25 FR245
FR246 Loiret (NUTS 2013) Quick edit Valid 2013-09-25 FR246
FR25 Basse-Normandie (NUTS 2013) Quick edit Valid 2013-09-25 FR25
FR251 Calvados (NUTS 2013) Quick edit Valid 2013-09-25 FR251
FR252 Manche (NUTS 2013) Quick edit Valid 2013-09-25 FR252
FR253 Orne (NUTS 2013) Quick edit Valid 2013-09-25 FR253
FR26 Bourgogne (NUTS 2013) Quick edit Valid 2013-09-25 FR26
FR261 Côte-d'Or (NUTS 2013) Quick edit Valid 2013-09-25 FR261
FR262 Nièvre (NUTS 2013) Quick edit Valid 2013-09-25 FR262
FR263 Saône-et-Loire (NUTS 2013) Quick edit Valid 2013-09-25 FR263
FR264 Yonne (NUTS 2013) Quick edit Valid 2013-09-25 FR264
FR3 Nord-Pas-de-Calais (NUTS 2013) Quick edit Valid 2013-09-25 FR3
FR30 Nord-Pas-de-Calais (NUTS 2013) Quick edit Valid 2013-09-25 FR30
FR301 Nord (FR) (NUTS 2013) Quick edit Valid 2013-09-25 FR301
FR302 Pas-de-Calais (NUTS 2013) Quick edit Valid 2013-09-25 FR302
FR4 Est (FR) (NUTS 2013) Quick edit Valid 2013-09-25 FR4
FR41 Lorraine (NUTS 2013) Quick edit Valid 2013-09-25 FR41
FR411 Meurthe-et-Moselle (NUTS 2013) Quick edit Valid 2013-09-25 FR411
FR412 Meuse (NUTS 2013) Quick edit Valid 2013-09-25 FR412
FR413 Moselle (NUTS 2013) Quick edit Valid 2013-09-25 FR413
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?