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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
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

11,204 concepts found, displaying 901 to 920.First4243444546474849Last
Id Label Status Status Modified Notation
01060048 Klein Gladebrügge Quick edit Valid 2009-01-01 01060048
01060049 Klein Rönnau Quick edit Valid 2009-01-01 01060049
01060050 Krems II Quick edit Valid 2009-01-01 01060050
01060051 Kükels Quick edit Valid 2009-01-01 01060051
01060052 Latendorf Quick edit Valid 2009-01-01 01060052
01060053 Leezen Quick edit Valid 2009-01-01 01060053
01060054 Lentföhrden Quick edit Valid 2009-01-01 01060054
01060056 Mönkloh Quick edit Valid 2009-01-01 01060056
01060057 Mözen Quick edit Valid 2009-01-01 01060057
01060058 Nahe Quick edit Valid 2009-01-01 01060058
01060059 Negernbötel Quick edit Valid 2009-01-01 01060059
01060060 Nehms Quick edit Valid 2009-01-01 01060060
01060061 Neuengörs Quick edit Valid 2009-01-01 01060061
01060062 Neversdorf Quick edit Valid 2009-01-01 01060062
01060063 Norderstedt, Stadt Quick edit Valid 2009-01-01 01060063
01060064 Nützen Quick edit Valid 2009-01-01 01060064
01060065 Oering Quick edit Valid 2009-01-01 01060065
01060066 Oersdorf Quick edit Valid 2009-01-01 01060066
01060067 Pronstorf Quick edit Valid 2009-01-01 01060067
01060068 Rickling Quick edit Valid 2009-01-01 01060068
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?