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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

6,250 concepts found, displaying 5,741 to 5,760.First284285286287288289290291Last
Id Label Status Status Modified Notation
593958 Dolenice Quick edit Valid 2013-05-30 593958
593966 Dolní Dubňany Quick edit Valid 2013-05-30 593966
593974 Dyjákovice Quick edit Valid 2013-05-30 593974
593982 Dyjákovičky Quick edit Valid 2013-05-30 593982
593991 Dyje Quick edit Valid 2013-05-30 593991
594008 Džbánice Quick edit Valid 2013-05-30 594008
594016 Grešlové Mýto Quick edit Valid 2013-05-30 594016
594024 Havraníky Quick edit Valid 2013-05-30 594024
594032 Hevlín Quick edit Valid 2013-05-30 594032
594041 Hluboké Mašůvky Quick edit Valid 2013-05-30 594041
594059 Hnanice Quick edit Valid 2013-05-30 594059
594067 Hodonice Quick edit Valid 2013-05-30 594067
594075 Horní Břečkov Quick edit Valid 2013-05-30 594075
594083 Horní Dubňany Quick edit Valid 2013-05-30 594083
594091 Horní Dunajovice Quick edit Valid 2013-05-30 594091
594105 Horní Kounice Quick edit Valid 2013-05-30 594105
594113 Hostěradice Quick edit Valid 2013-05-30 594113
594121 Hostim Quick edit Valid 2013-05-30 594121
594130 Hrabětice Quick edit Valid 2013-05-30 594130
594148 Hrádek Quick edit Valid 2013-05-30 594148
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?