Big Data Project Inventory

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The GWG Big Data Inventory is a catalog of Big Data projects that are relevant for official statistics, SDG indicators and other statistics needed for decision-making on public policies, as well as for management and monitoring of public sector programs/projects. This inventory is a joint product of the World Bank and the United Nations Statistics Division (UNSD) put together on behalf of the UN Global Working Group (GWG) on Big Data for Official Statistics. The tasks related to the content of the inventory are led by the World Bank and UNSD, and the technical side is serviced by the UNSD technical team.


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If you are working on a project that you would like to be considered for inclusion in this Inventory, even if the project is in an initial phase, please fill out this application form.

Please note that the project should either use Big Data sources and/or utilize Big Data techniques, and ideally have some relevance or implications for official statistics, SDG indicators or other statistics needed for decision-making on public policies. The Global Working Group will review submissions and include those projects that meet these criteria, or possibly contact you for further information. Please note that the information submitted below, once approved, will be made public on the GWG Big Data Project Inventory website.

CPI with Scanner Data

Country/Area: Austria
Organization / Dept: Austria - Statistics Austria
    Data sources:
  • Scanner data

Contact information

Project description:

Scanner data from big retail chains can be used to collect prices and quantities. Currently a pilot with a small data snapshot is being conducted. Negotiations with retail chains are ongoing.

Objective:

  • Pilot intended to go to production to replace existing data

Statistics Area:

  • Price statistics


Partnerships
  • Data providers: Not Specified
  • Other partners: Not Specified
  • Partnerships Comments: Not Specified

SDG Indicators
  • SDG Goals: Not Specified
  • SDG Comments: Not Specified
  • SDG Relevance: Not Specified

Data Access
  • Data Access Rights: Only for this project
  • Intermediary: Yes
  • Intermediary Comments: Market research company

Data Coverage
  • Data Coverage: Only a portion of all data
  • Coverage Geo Pop: Part of country / low % of market
  • Cost Implication: Commercial

Data Quality
  • Validation With Training Data: Yes
  • Validation Comments: Results are compared to the current method for estimating prices based on collection.
  • Data Quality Concerns: No
  • Quality Aspects Evaluated:
    • Institutional/Business Environment
    • Privacy and Security
    • Completeness, Usability, Time Factors
    • Accuracy, including selectivity
    • Coherence, including linkability to other sources
    • Validity
    • Accessibility, Relevance

Methodology
  • Methods Used:
    • Traditional statistical methods
  • Developed New Methods: Yes

Technologies
  • Technologies Used: No detail provided

Other
  • Timeframe To Produce Indicator: NA