Big Data Project Inventory
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.
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
Organization / Dept: Austria - Statistics Austria
- Scanner data
- Division: Analysis/ Quality Management/ Methods
- Name: Alexander Kowarik
- Email: firstname.lastname@example.org
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.
- Pilot intended to go to production to replace existing data
- Price statistics
- Data providers: Not Specified
- Other partners: Not Specified
- Partnerships Comments: Not Specified
- SDG Goals: Not Specified
- SDG Comments: Not Specified
- SDG Relevance: Not Specified
- Data Access Rights: Only for this project
- Intermediary: Yes
- Intermediary Comments: Market research company
- Data Coverage: Only a portion of all data
- Coverage Geo Pop: Part of country / low % of market
- Cost Implication: Commercial
- 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
- Accessibility, Relevance
- Methods Used:
- Traditional statistical methods
- Developed New Methods: Yes
- Technologies Used: No detail provided
- Timeframe To Produce Indicator: NA