Data for Good at Meta (previously Facebook)
Member since 13 March 2019
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  • 12000+ Downloads
    Updated 24 May 2022 | Dataset date: September 01, 2016-April 01, 2018
    This dataset updates: As needed
    More than 200 million businesses use Facebook. Meta partners with various academic and international organizations to survey these businesses throughout the year to learn about their perspectives, challenges and opportunities. With more businesses leveraging online tools each day, these surveys provide a lens into a new mobilized and digital economy. The Future of Business Survey (FoBS) is a collaboration between Meta, the OECD and the World Bank to provide timely insights on the perceptions, challenges, and outlook of online Small and Medium Enterprises or Businesses (SMEs/SMBs). The target population consists of SMEs that have an active Facebook business Page and include both newer and longer-standing businesses, spanning across a variety of sectors. The Future of Business Survey was first launched as a monthly survey in 17 countries in February 2016 and expanded to 42 countries in 2018. In 2019, the Future of Business survey increased coverage to 97 countries and moved to a bi-annual cadence. In 2020, the Future of Business Survey shifted to do additional monthly waves with questions focused on business challenges related to COVID-19. Meta also shares information from other SMB surveys, such as those that feed into the Global State of Small Business Reports, which are fielded to active Facebook Page Administrators and the general population of Facebook users. These surveys are conducted in approximately 30 countries across the globe and are also conducted on a roughly bi-annual basis. Survey questions for all surveys cover a range of topics depending on the survey wave such as business characteristics, challenges, financials and strategy in addition to custom modules related to regulation, gender inequity, access to finance, digital technologies, reduction in revenues, business closures, reduction of employees and challenges/needs of the business. Aggregated country level data is available to the public here for each wave and controlled access microdata is available to Data for Good partners. To request access to survey microdata or to see published Meta reports, please visit: futureofbusinesssurvey.org Update 12/12/21: We have transitioned all small business survey datasets to have survey weights applied. Files with weighted estimates have now replaced the previously posted unweighted estimates. Update 10/4/21: Aggregate data in files [gsosb_2021julyaugust_data_aggregate_weighted.csv] and [gsosb_2021february_data_aggregate_weighted.csv] have been updated to provide weighted results and to correct an error found in those two files. These files were discovered to present results for large businesses rather than small and medium businesses and have been updated to provide the information for the latter group. Downloads of these two files that took place between April 1 and September 30 2021 were affected and analysis using downloads from this period may need to be amended. No analyses or reports published by Facebook were affected. Please contact dataforgood@fb.com for any questions.
  • 42000+ Downloads
    Updated 24 May 2022 | Dataset date: March 01, 2020-May 25, 2022
    This dataset updates: Every day
    NOTE: We plan to no longer update this dataset after May 22 2022. These data sets are intended to inform researchers and public health experts about how populations are responding to physical distancing measures. In particular, there are two metrics, Change in Movement and Stay Put, that provide a slightly different perspective on movement trends. Change in Movement looks at how much people are moving around and compares it with a baseline period that predates most social distancing measures, while Stay Put looks at the fraction of the population that appear to stay within a small area during an entire day. Full details, including the privacy protections in this data, are available here: https://research.fb.com/blog/2020/06/protecting-privacy-in-facebook-mobility-data-during-the-covid-19-response/
  • 1200+ Downloads
    Updated 20 April 2022 | Dataset date: September 19, 2019-September 19, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Oman: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 2900+ Downloads
    Updated 19 April 2022 | Dataset date: May 20, 2019-May 20, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Sierra Leone: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49). There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.
  • 3200+ Downloads
    Updated 19 April 2022 | Dataset date: September 19, 2019-September 19, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Italy: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 1000+ Downloads
    Updated 15 April 2022 | Dataset date: May 01, 2020-May 01, 2020
    This dataset updates: As needed
    This dataset contains two APIs with daily COVID-19 Trends and Impact Survey data. The University of Maryland API is for accessing global survey data and CMU API is for accessing US survey data.
  • 900+ Downloads
    Updated 17 March 2022 | Dataset date: September 19, 2019-September 19, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Slovakia: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 1200+ Downloads
    Updated 17 March 2022 | Dataset date: September 19, 2019-September 19, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Moldova: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 1500+ Downloads
    Updated 17 March 2022 | Dataset date: September 19, 2019-September 19, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Romania: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 1100+ Downloads
    Updated 17 March 2022 | Dataset date: September 19, 2019-September 19, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Hungary: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 1500+ Downloads
    Updated 17 March 2022 | Dataset date: September 19, 2019-September 19, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Poland: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 14000+ Downloads
    Updated 11 February 2022 | Dataset date: April 01, 2021-May 25, 2022
    This dataset updates: As needed
    The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources. The data is provided for 93 low and middle-income countries at 2.4km resolution. Please cite / attribute any use of this dataset using the following: Microestimates of wealth for all low- and middle-income countries Guanghua Chi, Han Fang, Sourav Chatterjee, Joshua E. Blumenstock Proceedings of the National Academy of Sciences Jan 2022, 119 (3) e2113658119; DOI: 10.1073/pnas.2113658119 More details are available here: https://dataforgood.fb.com/tools/relative-wealth-index/ Research publication for the Relative Wealth Index is available here: https://www.pnas.org/content/119/3/e2113658119 Press coverage of the release of the Relative Wealth Index here: https://www.fastcompany.com/90625436/these-new-poverty-maps-could-reshape-how-we-deliver-humanitarian-aid An interactive map of the Relative Wealth Index is available here: http://beta.povertymaps.net/
  • 10+ Downloads
    Updated 4 March 2022 | Dataset date: September 19, 2019-September 19, 2019
    This data is by request only
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Ukraine: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 7300+ Downloads
    Updated 27 January 2022 | Dataset date: August 04, 2019-August 04, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Ethiopia : (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 1500+ Downloads
    Updated 25 January 2022 | Dataset date: September 19, 2019-September 19, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Portugal: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 1800+ Downloads
    Updated 25 January 2022 | Dataset date: May 20, 2019-May 20, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Algeria: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 3700+ Downloads
    Updated 7 January 2022 | Dataset date: October 15, 2020-May 25, 2022
    This dataset updates: Every week
    This bucket contains FAIR COVID-19 US county level forecast data
  • 1700+ Downloads
    Updated 15 January 2022 | Dataset date: September 19, 2019-September 19, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Qatar: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 1300+ Downloads
    Updated 15 January 2022 | Dataset date: September 19, 2019-September 19, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Bahrain: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 3100+ Downloads
    Updated 14 January 2022 | Dataset date: September 21, 2020-September 21, 2020
    This dataset updates: Every year
    This data contains aggregated weighted statistics at the regional level by gender for the 2020 Survey on Gender Equality At Home as well as the country and regional level for the 2021 wave. The Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. Researchers and nonprofits interested in access to survey microdata can apply at: https://dataforgood.facebook.com/dfg/tools/survey-on-gender-equality-at-home
  • 4400+ Downloads
    Updated 19 March 2019 | Dataset date: January 24, 2019-January 24, 2019
    This dataset updates: Never
    Facebook has produced a model to help map global medium voltage (MV) grid infrastructure, i.e. the distribution lines which connect high-voltage transmission infrastructure to consumer-serving low-voltage distribution. The data found here are model outputs for six select African countries: Malawi, Nigeria, Uganda, DRC, Cote D’Ivoire, and Zambia. The grid maps are produced using a new methodology that employs various publicly-available datasets (night time satellite imagery, roads, political boundaries, etc) to predict the location of existing MV grid infrastructure. The model documentation and code are also available , so data scientists and planners globally can replicate the model to expand model coverage to other countries where this data is not already available. You can find the model code and documentation here: https://github.com/facebookresearch/many-to-many-dijkstra Note: current model accuracy is approximately 70% when compared to existing ground-truthed data. Accuracy can be further improved by integrating other locally-relevant information into the model and running it again. Resolution: geotiff is provided at Bing Tile Level 20
  • 300+ Downloads
    Updated 20 December 2021 | Dataset date: July 04, 2021-May 25, 2022
    This dataset updates: Every six months
    Commuting zones are geographic areas where people live and work and are useful for understanding local economies, as well as how they differ from traditional boundaries. Learn more here: https://dataforgood.facebook.com/dfg/tools/commuting-zones
  • 18000+ Downloads
    Updated 15 December 2021 | Dataset date: October 13, 2021-October 13, 2021
    This dataset updates: As needed
    We use an anonymized snapshot of all active Facebook users and their friendship networks to measure the intensity of connectedness between locations. The Social Connectedness Index (SCI) is a measure of the social connectedness between different geographies. Specifically, it measures the relative probability that two individuals across two locations are friends with each other on Facebook. Details on the underlying data and the construction of the index are provided in the “Facebook Social Connectedness Index - Data Notes.pdf” file. Please also see https://dataforgood.fb.com/ as well as the associated research paper “Social Connectedness: Measurement, Determinants and Effects,” published in the Journal of Economic Perspectives (https://www.aeaweb.org/articles?id=10.1257/jep.32.3.259). Region identifiers are taken from GADM v2.8 https://gadm.org/download_country_v2.html. Future versions will update IDs to be compatible with the newest GADM version.
  • 7300+ Downloads
    Updated 8 April 2019 | Dataset date: October 01, 2018-October 01, 2018
    This dataset updates: As needed
    This zip file contains 28 cloud optimized tiff files that cover the continent of Africa. Each of the 28 files represents a region or area - these are not divided by country. Notes: The country-by-country files that were previously hosted here have been moved into separate datasets. You can find all of them here. South Sudan, Sudan, Somalia and Ethiopia are intentionally omitted from this dataset. However, a country-level dataset for Ethiopia can be found here. These 28 tiff files represent 2015 population estimates. However, please note that many of the country-level files include 2020 population estimates including: Angola, Benin, Botswana, Burundi, Cameroon, Cabo Verde, Cote d'Ivoire, Djibouti, Eritrea, Eswatini, The Gambia, Ghana, Lesotho, Liberia, Mozambique, Namibia, Sao Tome & Principe, Sierra Leone, South Africa, Togo, Zambia, and Zimbabwe.
  • 2000+ Downloads
    Updated 21 June 2019 | Dataset date: June 19, 2019-June 19, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Vietnam: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).