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.

The Sensors are Here! A High-Resolution Application on Understanding Individual Travel Patterns in African Cities

Country/Area: United Republic of Tanzania
Organization / Dept: World Bank Group
    Data sources:

Contact information

Project description:

The objective of this project is to collect high-resolution and high-frequency data on intra-city movements of a randomly selected group of individuals that will be interviewed as part of a planned household survey in Dar es Salaam, Tanzania. The project will combine detailed socio-economic information solicited on individuals and households as part the 3,000 household Measuring Living Standards within Dar es Salaam Survey (MLDS) with (i) follow-up phone interviews and (ii) sensor-embedded smartphone based high-frequency data collection on time- and GPS-stamped intra-city movements of a randomly selected sub-sample of MLDS respondents.

Objective:

Statistics Area:


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

SDG Indicators
  • SDG Goals:
    • 10 - Reduced Inequalities
    • 11 - Sustainable Cities & Communities
    • 17 - Partnerships for the Goals
  • SDG Comments: 10.2, 10.4, 11a, 17.18, 17.19
  • SDG Relevance: Yes

Data Access

    No detail provided


Data Coverage

    No detail provided


Data Quality

    No detail provided

  • No detail provided

Methodology
  • Methods Used: No detail provided

Technologies
  • Technologies Used: No detail provided

Other
  • Timeframe To Produce Indicator: NA