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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 2,901 to 2,920.First142143144145146147148149Last
Id Label Status Status Modified Notation
PL323 Krosnienski (NUTS 2013) Quick edit Valid 2013-09-25 PL323
PL324 Przemyski (NUTS 2013) Quick edit Valid 2013-09-25 PL324
PL325 Rzeszowski (NUTS 2013) Quick edit Valid 2013-09-25 PL325
PL326 Tarnobrzeski (NUTS 2013) Quick edit Valid 2013-09-25 PL326
PL33 Swietokrzyskie (NUTS 2013) Quick edit Valid 2013-09-25 PL33
PL330 Swietokrzyski (NUTS 2003) Quick edit Valid 2013-09-25 PL330
PL331 Kielecki (NUTS 2013) Quick edit Valid 2013-09-25 PL331
PL332 Sandomiersko-jedrzejowski (NUTS 2013) Quick edit Valid 2013-09-25 PL332
PL34 Podlaskie (NUTS 2013) Quick edit Valid 2013-09-25 PL34
PL341 Bialostocko-suwalski (NUTS 2003) Quick edit Valid 2013-09-25 PL341
PL342 Lomzynski (NUTS 2003) Quick edit Valid 2013-09-25 PL342
PL343 Bialostocki (NUTS 2013) Quick edit Valid 2013-09-25 PL343
PL344 Lomzynski (NUTS 2013) Quick edit Valid 2013-09-25 PL344
PL345 Suwalski (NUTS 2013) Quick edit Valid 2013-09-25 PL345
PL4 Makroregion Pólnocno-Zachodni Quick edit Valid 2013-09-25 PL4
PL41 Wielkopolskie Quick edit Valid 2013-09-25 PL41
PL411 Pilski Quick edit Valid 2013-09-25 PL411
PL412 Poznanski (NUTS 2003) Quick edit Valid 2013-09-25 PL412
PL413 Kaliski (NUTS 2003) Quick edit Valid 2013-09-25 PL413
PL414 Koninski Quick edit Valid 2013-09-25 PL414
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?