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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
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 3,121 to 3,140.First153154155156157158159160Last
Id Label Status Status Modified Notation
DE2918371 Bremische Ochtum Quick edit Valid 2018-01-19 DE2918371
DE2918401 Niedervieland Quick edit Valid 2018-01-19 DE2918401
DE2918402 Ochtum bei Grolland Quick edit Valid 2018-01-19 DE2918402
DE2919331 Sandtrockenrasen Achim Quick edit Valid 2018-01-19 DE2919331
DE2919370 Krietes Wald (Im Holze) Quick edit Valid 2018-01-19 DE2919370
DE2919371 Parks in Oberneuland Quick edit Valid 2018-01-19 DE2919371
DE2919401 Weseraue Quick edit Valid 2018-01-19 DE2919401
DE2919402 Oberneulander Wümmeniederung Quick edit Valid 2018-01-19 DE2919402
DE2921331 Wolfsgrund Quick edit Valid 2018-01-19 DE2921331
DE2921332 Wedeholz Quick edit Valid 2018-01-19 DE2921332
DE2922301 Großes und Weißes Moor Quick edit Valid 2018-01-19 DE2922301
DE2923331 Moor am Schweinekobenbach Quick edit Valid 2018-01-19 DE2923331
DE2924301 Böhme Quick edit Valid 2018-01-19 DE2924301
DE2924331 Riensheide Quick edit Valid 2018-01-19 DE2924331
DE2928331 Bobenwald Quick edit Valid 2018-01-19 DE2928331
DE2929301 Lohn Quick edit Valid 2018-01-19 DE2929301
DE2929331 Kammmolch-Biotop Mührgehege/Oetzendorf Quick edit Valid 2018-01-19 DE2929331
DE2930401 Ostheide bei Himbergen und Bad Bodenteich Quick edit Valid 2018-01-19 DE2930401
DE2931401 Drawehn Quick edit Valid 2018-01-19 DE2931401
DE2932301 Maujahn Quick edit Valid 2018-01-19 DE2932301
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?