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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 81 to 100.First12345678Last
Id Label Status Status Modified Notation
AT2125000 Reifnitzbach Quick edit Valid 2018-01-19 AT2125000
AT2126000 Tiebelmündung - Bleistätter Moor Quick edit Valid 2018-01-19 AT2126000
AT2127000 Fronwiesen Quick edit Valid 2018-01-19 AT2127000
AT2128000 Kalk-Tuffquellen Völkermarkter Stausee Quick edit Valid 2018-01-19 AT2128000
AT2129000 Hohe Tauern, Kärnten II Quick edit Valid 2018-01-19 AT2129000
AT2130000 Lendspitz-Maiernigg Quick edit Valid 2018-01-19 AT2130000
AT2131000 Mannsberg-Boden Quick edit Valid 2018-01-19 AT2131000
AT2132000 Hainsche-Moor Quick edit Valid 2018-01-19 AT2132000
AT2133000 Guntschacher Au Quick edit Valid 2018-01-19 AT2133000
AT2134000 Mittagskogel - Karawanken Westteil Quick edit Valid 2018-01-19 AT2134000
AT2135000 Kalktuffquellen Lappenbach Quick edit Valid 2018-01-19 AT2135000
AT2136000 Gelbe Alpenrose in Lendorf Quick edit Valid 2018-01-19 AT2136000
AT2137000 Schlossberg Griffen Quick edit Valid 2018-01-19 AT2137000
AT2138000 Gurkmündung Quick edit Valid 2018-01-19 AT2138000
AT2139000 Grünspitz-Streifenfarn in Radenthein Quick edit Valid 2018-01-19 AT2139000
AT2140000 Millstätter See-Süd Quick edit Valid 2018-01-19 AT2140000
AT2141000 Watzelsdorfer Moos Quick edit Valid 2018-01-19 AT2141000
AT2142000 Ziegelteich bei Hörtendorf Quick edit Valid 2018-01-19 AT2142000
AT2143000 Lanzendorfer Moor Quick edit Valid 2018-01-19 AT2143000
AT2144000 Gutschen Quick edit Valid 2018-01-19 AT2144000
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?