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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
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 3,381 to 3,400.First166167168169170171172173Last
Id Label Status Status Modified Notation
DE3314331 Wald bei Burg Dinklage Quick edit Valid 2018-01-19 DE3314331
DE3315331 Diepholzer Moor Quick edit Valid 2018-01-19 DE3315331
DE3317301 Neustädter Moor Quick edit Valid 2018-01-19 DE3317301
DE3318331 Swinelake bei Barenburg Quick edit Valid 2018-01-19 DE3318331
DE3319331 Hohes Moor bei Kirchdorf Quick edit Valid 2018-01-19 DE3319331
DE3319332 Teichfledermaus-Gewässer im Raum Nienburg Quick edit Valid 2018-01-19 DE3319332
DE3320331 Marklohe Quick edit Valid 2018-01-19 DE3320331
DE3321331 Nienburger Bruch Quick edit Valid 2018-01-19 DE3321331
DE3322331 Fledermauslebensraum bei Rodewald Quick edit Valid 2018-01-19 DE3322331
DE3324331 Hellern bei Wietze Quick edit Valid 2018-01-19 DE3324331
DE3326331 Henneckenmoor bei Scheuen Quick edit Valid 2018-01-19 DE3326331
DE3329301 Rössenbergheide-Külsenmoor, Heiliger Hain Quick edit Valid 2018-01-19 DE3329301
DE3329331 Teichgut in der Oerreler Heide Quick edit Valid 2018-01-19 DE3329331
DE3329332 Großes Moor bei Gifhorn Quick edit Valid 2018-01-19 DE3329332
DE3331301 Hartauniederung zwischen Lüdelsen und Ahlum Quick edit Valid 2018-01-19 DE3331301
DE3331302 Ohreaue Quick edit Valid 2018-01-19 DE3331302
DE3332301 Tangelnscher Bach und Bruchwälder Quick edit Valid 2018-01-19 DE3332301
DE3332302 Jeetze südlich Beetzendorf Quick edit Valid 2018-01-19 DE3332302
DE3333301 Buchenwald östlich Klötze Quick edit Valid 2018-01-19 DE3333301
DE3333302 Eiskeller in Klötze Quick edit Valid 2018-01-19 DE3333302
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?