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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 3,341 to 3,360.First164165166167168169170171Last
Id Label Status Status Modified Notation
DE3238301 Jederitzer Holz östlich Havelberg Quick edit Valid 2018-01-19 DE3238301
DE3238302 Elbaue zwischen Sandau und Schönhausen Quick edit Valid 2018-01-19 DE3238302
DE3238303 Kamernscher See und Trübengraben Quick edit Valid 2018-01-19 DE3238303
DE3239301 Untere Havel und Schollener See Quick edit Valid 2018-01-19 DE3239301
DE3239302 Restwälder bei Rhinow Quick edit Valid 2018-01-19 DE3239302
DE3239401 Untere Havel/Sachsen-Anhalt und Schollener See Quick edit Valid 2018-01-19 DE3239401
DE3240301 Unteres Rhinluch - Dreetzer See Quick edit Valid 2018-01-19 DE3240301
DE3240302 Gollenberg Quick edit Valid 2018-01-19 DE3240302
DE3241301 Friesacker Zootzen Quick edit Valid 2018-01-19 DE3241301
DE3241302 Görner See Quick edit Valid 2018-01-19 DE3241302
DE3242421 Rhin-Havelluch Quick edit Valid 2018-01-19 DE3242421
DE3243301 Oberes Rhinluch Quick edit Valid 2018-01-19 DE3243301
DE3243302 Mossberge Quick edit Valid 2018-01-19 DE3243302
DE3243303 Oberes Rhinluch Ergänzung Quick edit Deprecated 2023-01-26 DE3243303
DE3243304 Fledermausquartier Stallgebäude in Linum Quick edit Valid 2018-01-19 DE3243304
DE3244301 Kremmener Luch Quick edit Valid 2018-01-19 DE3244301
DE3244303 Behrensbrück Quick edit Valid 2018-01-19 DE3244303
DE3245301 Fledermauswinterquartier Lehnitz Quick edit Valid 2018-01-19 DE3245301
DE3246301 Lubowsee Quick edit Valid 2018-01-19 DE3246301
DE3246302 Briesetal Quick edit Valid 2018-01-19 DE3246302
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?