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Eionet
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 141 to 160.First4567891011Last
Id Label Status Status Modified Notation
01053021 Dahmker Quick edit Valid 2009-01-01 01053021
01053022 Dalldorf Quick edit Valid 2009-01-01 01053022
01053023 Dassendorf Quick edit Valid 2009-01-01 01053023
01053024 Düchelsdorf Quick edit Valid 2009-01-01 01053024
01053025 Duvensee Quick edit Valid 2009-01-01 01053025
01053026 Einhaus Quick edit Valid 2009-01-01 01053026
01053027 Elmenhorst Quick edit Valid 2009-01-01 01053027
01053028 Escheburg Quick edit Valid 2009-01-01 01053028
01053029 Fitzen Quick edit Valid 2009-01-01 01053029
01053030 Fredeburg Quick edit Valid 2009-01-01 01053030
01053031 Fuhlenhagen Quick edit Valid 2009-01-01 01053031
01053032 Geesthacht, Stadt Quick edit Valid 2009-01-01 01053032
01053033 Giesensdorf Quick edit Valid 2009-01-01 01053033
01053034 Göldenitz Quick edit Valid 2009-01-01 01053034
01053035 Göttin Quick edit Valid 2009-01-01 01053035
01053036 Grabau Quick edit Valid 2009-01-01 01053036
01053037 Grambek Quick edit Valid 2009-01-01 01053037
01053038 Grinau Quick edit Valid 2009-01-01 01053038
01053039 Groß Boden Quick edit Valid 2009-01-01 01053039
01053040 Groß Disnack Quick edit Valid 2009-01-01 01053040
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?