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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
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 461 to 480.First2021222324252627Last
Id Label Status Status Modified Notation
PC_IND_BLT12 Percentage of individuals who ordered goods or services, over the internet, for private use, in the last year Quick edit Valid 2013-09-24 PC_IND_BLT12
PC_IND_BMT12X Percentage of individuals who ordered goods or services, over the internet, for private use, more than a year ago or who never did Quick edit Valid 2013-09-24 PC_IND_BMT12X
PC_IND_BPG_ANY Percentage of individuals who purchased online physical goods Quick edit Valid 2020-06-10 PC_IND_BPG_ANY
PC_IND_BRA Percentage of individuals who rented accommodation online from an enterprise or a private person Quick edit Valid 2020-06-10 PC_IND_BRA
PC_IND_BTPS Percentage of individuals who purchased online transport service from a transport enterprise or a private person Quick edit Valid 2020-06-10 PC_IND_BTPS
PC_IND_BUY3 Percentage of individuals who purchased online in the last 3 months Quick edit Valid 2015-12-01 PC_IND_BUY3
PC_IND_C3 Percentage of individuals who used a computer within the last 3 months Quick edit Valid 2013-09-24 PC_IND_C3
PC_IND_CC_AW Percentage of individuals who used internet, were aware of cloud services but did not use them Quick edit Valid 2014-09-19 PC_IND_CC_AW
PC_IND_CC_CCS Percentage of individuals who used internet and cloud services for file saving or sharing Quick edit Valid 2014-09-19 PC_IND_CC_CCS
PC_IND_CC_CCSX Percentage of individuals who used internet but not cloud services Quick edit Valid 2014-09-19 PC_IND_CC_CCSX
PC_IND_CEVR Percentage of individuals who used a computer, ever Quick edit Valid 2013-09-24 PC_IND_CEVR
PC_IND_CIANY Percentage of individuals who have done at least one of the listed computer or internet activities Quick edit Valid 2013-09-24 PC_IND_CIANY
PC_IND_CTMT3YX Percentage of individuals who have taken a computer course more than 3 years ago or never Quick edit Valid 2013-09-24 PC_IND_CTMT3YX
PC_IND_ILT12 Percentage of individuals who used internet within the last year Quick edit Valid 2013-09-24 PC_IND_ILT12
PC_IND_ILT12_SSF Percentage of employees and self-employed who used internet within the last year Quick edit Valid 2018-08-01 PC_IND_ILT12_SSF
PC_IND_IOT_BDKX Percentage of individuals who have not used any internet-connected device or systems although they knew about them Quick edit Valid 2020-06-10 PC_IND_IOT_BDKX
PC_IND_IOT_DX Percentage of individuals who have not used any internet-connected devices or systems Quick edit Valid 2020-06-10 PC_IND_IOT_DX
PC_IND_IU3 Percentage of individuals who used internet in the last 3 months Quick edit Valid 2013-09-24 PC_IND_IU3
PC_IND_IUEVR Percentage of individuals who used internet, ever Quick edit Valid 2013-09-24 PC_IND_IUEVR
PC_IND_IUGOV12 Percentage of e-government users Quick edit Valid 2013-12-17 PC_IND_IUGOV12
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?