Governments are taking a wide range of measures in response to the COVID-19 outbreak. The Oxford COVID-19 Government Response Tracker (OxCGRT) aims track and compare government responses to the coronavirus outbreak worldwide rigorously and consistently.
The OxCGRT systematically collects information on several different common policy responses governments have taken, scores the stringency of such measures, and aggregates these scores into a common Stringency Index. For more, please visit > https://www.bsg.ox.ac.uk/research/research-projects/oxford-covid-19-government-response-tracker
Average time needed to get from a municipality to the nearest law enforcement building (police station, police station, barracks, command, etc.) on foot. Data source: Humdata June 2020. Categorized by country, department and municipality.
For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform https://predisan.gis4tech.com/ca4 for detailed, accurate information.
Number of public order buildings per 100,000 inhabitants based on territorial analysis with GIS (own elaboration). Data source: Humdata June 2020 by country, department and municipality.
For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform https://predisan.gis4tech.com/ca4 for detailed, accurate information.
Information on protected areas in Central America is expressed in square kilometres. Categorized by country, departments and municipality.
For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform https://predisan.gis4tech.com/ca4 for detailed, accurate information.
This dataset brings together data from a range of sources to provide a greater overall and comparative understanding of the current situation and context inside each district. The core indicators consist of key drivers (conflict, basic commodity prices, exclusion and marginalization, and disrupted access to life-saving services and income sources) and their major expected humanitarian impacts (food insecurity, cholera). ACAPS tracks changes in these indicators and alerts the humanitarian community to emerging trends or risks that could overwhelm local coping mechanisms in Afghanistan, triggering a humanitarian emergency.
The UNU-WIDER Government Revenue Dataset (GRD) aims to present a complete picture of government revenue and tax trends over time and allows for analysis at the country, regional or cross-country level.
The GRD provides data on government tax and non-tax revenues, social contributions, and grants in both local currency and as a percentage of GDP. It also highlights the portion of government revenues that accrue from natural resource extraction. The dataset covers the latest available tax and revenue data for the period from 1980—2019 (or —2020 where available) for 196 countries.
The data can be accessed online through the GRD Explorer tool, which allows users to compare countries, regions, and indicators as well as to visualize the data, or by download in Stata and Excel formats. The dataset is updated annually based on changes or updates to the underlying data, as well as on feedback from users with regard to particular countries or regions. For more information please visit https://www.wider.unu.edu/project/grd
Region-level data collected from the official website of Russian Federal Agency Rospotrebnadzor (https://стопкоронавирус.рф/). Dataset exists attributes: data, infected, recovered, died. The dataset contains information of 85 Russian regions.
Registry of Russian social-oriented non profit organizations recognized by the government as affected by COVID-19 and that receive government support. The Ministry of Economic Development of Russia published the register of non profit non government organizations (NGOs) that will be provided with additional measures of support.
Dataset columns: name of organization, OGRN, INN, Responsible government agency, Status, Orgform.
The dataset contains information about 11 208 NGOs of 85 Russian regions.
The #COVID19 Government Measures Dataset puts together all the measures implemented by governments worldwide in response to the Coronavirus pandemic. Data collection includes secondary data review. The researched information available falls into five categories:
Social distancing
Movement restrictions
Public health measures
Social and economic measures
Lockdowns
Each category is broken down into several types of measures.
ACAPS consulted government, media, United Nations, and other organisations sources.
For any comments, please contact us at info@acaps.org
Please note note that some measures together with non-compliance policies may not be recorded and the exact date of implementation may not be accurate in some cases, due to the different way of reporting of the primary data sources we used.
The COVID-19 Humanitarian Exemptions to Government Measures Dataset puts together all the measures implemented by governments worldwide in response to the Coronavirus pandemic.
This dataset presents the distribution of the 4 local languages officially recognized in the DRC, and this distribution is made by territory. These are Kikongo, Swahili, Lingala and Kiluba. French and English are recognized as international languages. There are several dialects in the DRC regrouped in these 4 languages.
The AFDB Statistical Data Portal has been developed in response to the increasing demand for statistical data and indicators relating to African Countries. The Portal provides multiple customized tools to gather indicators, analyze them, and export them into multiple formats.
With the Data Portal, you can visualize Socio-Economic indicators over a period of time, gain access to presentation-ready graphics and perform comprehensive analysis on a Country and Regional level
Dataset shows the County Allocation of Revenue Act 2017 and Office of the Controller of Budget approved Estimates.The FY 2017/18 Total Includes Ksh 4.0 Billion allocated to County Governments as Conditional Grant Under The KDSP(Level 2) Grant.
Polling station locations
Abstract: This data comes from http://vote.iebc.or.ke
Use the _sphericalmercator versions with TileMill, will be much faster. Otherwise, you're probably fine with the unprojected versions.
There are simple endpoints for requesting json encoded data. download.py iterates, caches, and builds the output
Instructions: Polling station location Shapefile can be downloaded from https://github.com/mikelmaron/kenya-election-data/tree/master/output
Polling Station of Pakistan compiled by ALHASAN SYSTEMS Private Limited as one of its R&D projects and in the public interest.
ALHASAN SYSTEMS made these Polling Stationpublic before Pakistan’s General Election 2018in its Open Data/ Open Access [OD/OA] Seminar on May 5, 2013. This data is used thoroughly in Pakistan by many stakeholders and researchers including UN and other donor agencies. For further details on the use of this data please download Alhasan Systems monthly Election Bulletins from [http://www.alhasan.com/bulletins/election].
ALHASAN SYSTEMS is a privately owned development company with a history that goes back to 1990. At present is registered in Pakistan and Canada. This hi-tech knowledge management, business psychology modeling, and publishing company is constantly contributing its data and services to both humanitarian and developmental causes through its Public/ Private Partnership [PPP] SKIM and ODOA initiatives. ALHASAN SYSTEMS strives to provide the most cost effective solutions and services, which not only serve its clients’ immediate requirements but also contribute to the much larger cause of community welfare and development. Its area of professional services spreads from environment, energy, health, natural resources, critical infrastructure, utilities management, tourism, and investments, to community development and crisis management. ALHASAN SYSTEMS corporate roadmap focuses on new trends in the field of Geomatics Engineering, Geo-engineering, Data Management, Bio Interfacing, Business Psychology Modeling, Hi-tech publishing, e-Learning, and Smart Power Gridding and Engineering Services. This is possible when fairly serious ecological, political, and moral ramifications are addressed strategically. That’s why social awareness, advocacy, and capacity building remain at the heart of ALHASAN SYSTEMS.
ALHASAN SYSTEMS constantly update its data in relation to its projects and also as a service to larger public bodies as well as research community to promote its pioneering 100% self-financed Open Data/ Open Access [OD/OA] initiative in Pakistan. We also share a number of additional layers and thousands of maps each year free-of-cost in the larger public interest.
All our data are made available through Pakistan’s only Metadata portal [www.geopakistan.pk] launched in 2012 by iMMAP in collaboration with its partners under USAID funding. This portal is now hosted and maintained at NED University of Engineering & Technology with hundreds of registered researchers in Pakistan.
Alhasan Systems is also a United Nations Humanitarian Data Exchange Portal [https://data.hdx.rwlabs.org/] member agency and share its resources through HDX for larger humanitarian benefits.
