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:exactMatch 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

707 concepts found, displaying 341 to 360.First1415161718192021Last
Id Label Status Status Modified Notation
PC_EMP Percentage of total employment Quick edit Valid 2013-09-24 PC_EMP
PC_EMP_AESELL Percentage of persons employed working in enterprises which received orders via computer networks Quick edit Valid 2023-05-10 PC_EMP_AESELL
PC_EMP_CUSE Percentage of persons employed using a computer Quick edit Valid 2013-09-24 PC_EMP_CUSE
PC_EMP_CUSE2 Percentage of persons employed working in enterprises which use computers Quick edit Valid 2013-09-24 PC_EMP_CUSE2
PC_EMP_FTE Percentage of total employment - numerator in full-time equivalent (FTE) Quick edit Valid 2013-09-24 PC_EMP_FTE
PC_EMP_HC Percentage of total employment - numerator in head count (HC) Quick edit Valid 2013-09-24 PC_EMP_HC
PC_EMP_IACC Percentage of persons employed working in an enterprise with internet access Quick edit Valid 2013-09-24 PC_EMP_IACC
PC_EMP_IUSE Percentage of persons employed using a computer with access to the www Quick edit Valid 2013-09-24 PC_EMP_IUSE
PC_EMP_PMD Percentage of persons employed working in enterprises which provide mobile devices Quick edit Valid 2013-09-24 PC_EMP_PMD
PC_EMP_PMD1 Percentage of persons employed working in enterprises which provide mobile devices (as of 2016) Quick edit Valid 2017-01-10 PC_EMP_PMD1
PC_EMP_PREEMP Percentage of persons employed and previously employed Quick edit Valid 2023-05-10 PC_EMP_PREEMP
PC_EMP_PREEMP_M12 Percentage of persons employed and previously employed within 12 months Quick edit Valid 2023-05-10 PC_EMP_PREEMP_M12
PC_ENT Percentage of enterprises Quick edit Valid 2013-09-24 PC_ENT
PC_ENT_ADE Percentage of enterprises using ADE Quick edit Valid 2013-09-24 PC_ENT_ADE
PC_ENT_ADS Percentage of enterprises using internet ads Quick edit Valid 2016-11-30 PC_ENT_ADS
PC_ENT_AEBUY Percentage of enterprises sending e-commerce orders over the last calendar year Quick edit Valid 2013-09-24 PC_ENT_AEBUY
PC_ENT_AESELL Percentage of enterprises receiving e-commerce orders over the last calendar year Quick edit Valid 2013-09-24 PC_ENT_AESELL
PC_ENT_AI_EC Percentage of the enterprises which ever considered to use any of the AI technologies Quick edit Valid 2023-05-10 PC_ENT_AI_EC
PC_ENT_AI_TANY Percentage of the enterprises using at least one AI technologies Quick edit Valid 2023-05-10 PC_ENT_AI_TANY
PC_ENT_AI_TX Percentage of the enterprises using no AI technologies Quick edit Valid 2023-05-10 PC_ENT_AI_TX
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?