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The Uganda Bureau of Statistics ("UBOS") is an agency of the Ugandan government. Formed by the Uganda Bureau of Statistics Act, 1998, the agency is mandated to "coordinate, monitor and supervise Uganda's National Statistical System".
Many governments publish open data they produce or commission on official websites to be freely used, reused, or redistributed by anyone. [1] [2] These sites are often created as part of open government initiatives.
Website Afghanistan: Central Statistics Organization: nsia.gov.af Bahrain: Information & eGovernment Authority - Bahrain Open Data Portal : data.gov.bh Bangladesh: Bangladesh Bureau of Statistics: bbs.gov.bd Bhutan: National Statistics Bureau nsb.gov.bt Brunei: Department of Economic Planning and Statistics deps.gov.bn Cambodia
The USGS Gap Analysis Program maintains four primary data sets: land cover, protected areas, species and aquatic. The GAP Land Cover Data Set is the most complete map ever produced of vegetative associations for the US. Classified into 551 ecological systems, and 32 modified ecological systems (where human impacts have had an effect).
Chris Ndatira Mukiza is a Ugandan economist, who is the executive director of the Uganda Bureau of Statistics, the government agency responsible for the collection, analysis, dissemination and storage of nationally important data. [1] [2]
Metadata about publications, datasets, grants, preprints from 17,633 members (journals, publishers, etc.) Free Crossref: DeepDyve: Multidisciplinary: 20,000,000 Commercial website that sells access to scientific and scholarly articles from a large range of academic publishers (over 1700 journals). Limited free access. Free & Subscription DeepDyve
Marcella Nasseri found her missing brother Thomas Manizak through a USA TODAY story after 25 years. New details emerge of his background.
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.