AndreaBozzo/ceres-open-data-index huggingface dataset:
Central African Republic - Humanitarian Response Plan

This data has been produced by the United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) on behalf of the Humanitarian Country Team and partners. The data provides the Humanitarian Country Team’s shared understanding of the crisis, including the most pressing humanitarian need and the estimated number of people who need assistance. It represents a consolidated evidence base and helps inform joint strategic response planning.

Tags: funding, humanitarian response plan-hrp, hxl, people in need-pin
Organization: OCHA Central African Republic
Afghanistan - Natural Disaster Incidents in 2019

1)	Natural disaster events include avalanches, earthquakes, flooding, heavy rainfall & snowfall, and landslides & mudflows as recorded by OCHA field offices based on assessments in the field. 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) people, who may or may not require humanitarian assistance. 3)  The information includes assessment figures from OCHA, ANDMA, IOM, Red Crescent Societies, national NGOs, international NGOs, and ERM. 4) The number of affected people and houses damaged or destroyed are based on the reports received. These figures may change as updates are received.

Tags: affected population, climate hazards, damage assessment, earthquake-tsunami, flooding, hxl, natural disasters
Organization: OCHA Afghanistan
Afghanistan - Who does What Where (April to June 2020)

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed [here](https://www.humanitarianresponse.info/en/operations/afghanistan/3w). 

Tags: hxl, operational capacity, operational presence, who is doing what and where-3w-4w-5w
Organization: OCHA Afghanistan
Afghanistan - Who does What Where (October to December 2020)

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed [here](https://www.humanitarianresponse.info/en/operations/afghanistan/3w). 

Tags: hxl, operational capacity, operational presence, who is doing what and where-3w-4w-5w
Organization: OCHA Afghanistan
Afghanistan - Who does What Where (January to March 2020)

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed [here](https://www.humanitarianresponse.info/en/operations/afghanistan/3w). 

Tags: hxl, operational capacity, operational presence, who is doing what and where-3w-4w-5w
Organization: OCHA Afghanistan
Afghanistan - Natural Disaster Incidents in 2020

1) Natural disaster events include avalanches, earthquakes, flooding, heavy rainfall & snowfall, and landslides & mudflows as recorded by OCHA field offices based on assessments in the field. 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) people, who may or may not require humanitarian assistance. 3)  The information includes assessment figures from OCHA, ANDMA, IOM, Red Crescent Societies, national NGOs, international NGOs, and ERM. 4) The number of affected people and houses damaged or destroyed are based on the reports received. These figures may change as updates are received.

Tags: affected population, climate hazards, damage assessment, earthquake-tsunami, flooding, hxl, natural disasters
Organization: OCHA Afghanistan
Afghanistan - Conflict Induced Displacements in 2020

Newly displaced population due to conflict between 01 January 2020 and 30 December 2020, compiled by OCHA sub offices based on inter-agency assessment results. This data is a snapshot as of 30 Mar 2021 and the numbers are expected to change as new assessment figures become available.

Tags: conflict-violence, hxl, internally displaced persons-idp
Organization: OCHA Afghanistan
Afghanistan - Who does What Where (October to December 2019)

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed [here](https://www.humanitarianresponse.info/en/operations/afghanistan/3w). 

Tags: hxl, operational capacity, operational presence, who is doing what and where-3w-4w-5w
Organization: OCHA Afghanistan
AI building footprint in Izabal, Guatemala

Izabal department (GT-IZ), Guatemala: AI predictions of building footprint on Bing Maps images (approximately 2016-2019), see https://github.com/rodekruis/automated-building-detection. Produced in support to DRRT Guatemala for hurricane Eta and Iota. Coordinate reference system: WGS 84 / EPSG:4326

Tags: cyclones-hurricanes-typhoons, facilities-infrastructure, geodata, populated places-settlements
Organization: Netherlands Red Cross - 510
AI + OSM buildings in Camarines Sur (1-nov-2020)

OpenStreetMap buildings of Camarines Sur (as of 1-nov-2020) and AI predictions on Bing Maps images (approximately 2016-2019).
Produced in support of Philippines Red Cross for typhoon Goni (1-nov-2020)
Coordinate reference system: WGS 84 / EPSG:4326

Tags: facilities-infrastructure, geodata
Organization: Netherlands Red Cross - 510
AI building footprint in southern Guatemala

Southern Guatemala: AI predictions  of building footprint on Bing Maps images (approximately 2016-2019), see https://github.com/rodekruis/automated-building-detection. Produced in support to DRRT Guatemala for hurricane Eta and Iota. Coordinate reference system: WGS 84 / EPSG:4326

Tags: cyclones-hurricanes-typhoons, facilities-infrastructure, geodata, populated places-settlements
Organization: Netherlands Red Cross - 510
Democratic Republic of the Congo: Projected COVID-19 Sub-national Cases

The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts.

Access the - [code repository](https://github.com/OCHA-DAP/pa-ocha-bucky) , including all the source code scripts necessary to run the model.
View the - [technical documentation](https://ocha-bucky.readthedocs.io/en/latest/) and  - [FAQs](https://ocha-bucky.readthedocs.io/en/latest/faq.html) explaining how to configure and run the source code in the repository.
Download the - [methodology paper](https://s3.eu-central-1.amazonaws.com/hdx-ckan-filestore-prod/resources/2d9592f8-2980-4466-96f5-f0de23ea7ffa/ochabucky_final.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Expires=180&X-Amz-Credential=AKIARZNKTAO7U6UN77MP%2F20201130%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-SignedHeaders=host&X-Amz-Date=20201130T094845Z&X-Amz-Signature=9b35288654c79b895b900198e5a75e5fd00d447dd7f487445897dad6f4301fc3)  providing details on model assumptions and the main equations.
Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries.
Download the - [OCHA-Bucky model card](https://s3.eu-central-1.amazonaws.com/hdx-ckan-filestore-prod/resources/89a2ff67-ef20-4005-9732-bfc23d76bf4b/ocha-bucky-model-card.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Expires=180&X-Amz-Credential=AKIARZNKTAO7U6UN77MP%2F20201130%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-SignedHeaders=host&X-Amz-Date=20201130T095024Z&X-Amz-Signature=a322a7e660bfa47675a9f6b16f0c25105c1b55b5c2407652182d0a90c91c8554)  created according to the Centre’s Peer Review Framework.

The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels. 

Tags: covid-19, hxl
Organization: Johns Hopkins Applied Physics Lab
Myanmar: Response Plan projects

Projects proposed, in progress, or completed as part of the annual Myanmar Humanitarian Response Plans (HRPs) or other Humanitarian Programme Cycle plans. The original data is available on https://hpc.tools

**Important:** some projects in Myanmar might be missing, and others might not apply specifically to Myanmar. See _Caveats_ under the _Additional information_ tab.

Tags: humanitarian response plan-hrp, hxl, who is doing what and where-3w-4w-5w
Organization: OCHA Humanitarian Programme Cycle Tools (HPC Tools)
South Sudan: Projected COVID-19 Sub-national Cases

The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts.

Access the - [code repository](https://github.com/OCHA-DAP/pa-ocha-bucky) , including all the source code scripts necessary to run the model.
View the - [technical documentation](https://ocha-bucky.readthedocs.io/en/latest/) and  - [FAQs](https://ocha-bucky.readthedocs.io/en/latest/faq.html) explaining how to configure and run the source code in the repository.
Download the - [methodology paper](https://s3.eu-central-1.amazonaws.com/hdx-ckan-filestore-prod/resources/2d9592f8-2980-4466-96f5-f0de23ea7ffa/ochabucky_final.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Expires=180&X-Amz-Credential=AKIARZNKTAO7U6UN77MP%2F20201130%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-SignedHeaders=host&X-Amz-Date=20201130T094845Z&X-Amz-Signature=9b35288654c79b895b900198e5a75e5fd00d447dd7f487445897dad6f4301fc3)  providing details on model assumptions and the main equations.
Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries.
Download the - [OCHA-Bucky model card](https://s3.eu-central-1.amazonaws.com/hdx-ckan-filestore-prod/resources/89a2ff67-ef20-4005-9732-bfc23d76bf4b/ocha-bucky-model-card.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Expires=180&X-Amz-Credential=AKIARZNKTAO7U6UN77MP%2F20201130%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-SignedHeaders=host&X-Amz-Date=20201130T095024Z&X-Amz-Signature=a322a7e660bfa47675a9f6b16f0c25105c1b55b5c2407652182d0a90c91c8554)  created according to the Centre’s Peer Review Framework.

The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels. 

Tags: covid-19, hxl
Organization: Johns Hopkins Applied Physics Lab
Afghanistan: Projected COVID-19 Sub-national Cases

The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts.

Access the - [code repository](https://github.com/OCHA-DAP/pa-ocha-bucky) , including all the source code scripts necessary to run the model.
View the - [technical documentation](https://ocha-bucky.readthedocs.io/en/latest/) and  - [FAQs](https://ocha-bucky.readthedocs.io/en/latest/faq.html) explaining how to configure and run the source code in the repository.
Download the - [methodology paper](https://s3.eu-central-1.amazonaws.com/hdx-ckan-filestore-prod/resources/2d9592f8-2980-4466-96f5-f0de23ea7ffa/ochabucky_final.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Expires=180&X-Amz-Credential=AKIARZNKTAO7U6UN77MP%2F20201130%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-SignedHeaders=host&X-Amz-Date=20201130T094845Z&X-Amz-Signature=9b35288654c79b895b900198e5a75e5fd00d447dd7f487445897dad6f4301fc3)  providing details on model assumptions and the main equations.
Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries.
Download the - [OCHA-Bucky model card](https://s3.eu-central-1.amazonaws.com/hdx-ckan-filestore-prod/resources/89a2ff67-ef20-4005-9732-bfc23d76bf4b/ocha-bucky-model-card.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Expires=180&X-Amz-Credential=AKIARZNKTAO7U6UN77MP%2F20201130%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-SignedHeaders=host&X-Amz-Date=20201130T095024Z&X-Amz-Signature=a322a7e660bfa47675a9f6b16f0c25105c1b55b5c2407652182d0a90c91c8554)  created according to the Centre’s Peer Review Framework.

The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels. 

Tags: covid-19, hxl
Organization: Johns Hopkins Applied Physics Lab
Iraq: Projected COVID-19 Sub-national Cases

The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts.

Access the - [code repository](https://github.com/OCHA-DAP/pa-ocha-bucky) , including all the source code scripts necessary to run the model.
View the - [technical documentation](https://ocha-bucky.readthedocs.io/en/latest/) and  - [FAQs](https://ocha-bucky.readthedocs.io/en/latest/faq.html) explaining how to configure and run the source code in the repository.
Download the - [methodology paper](https://s3.eu-central-1.amazonaws.com/hdx-ckan-filestore-prod/resources/2d9592f8-2980-4466-96f5-f0de23ea7ffa/ochabucky_final.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Expires=180&X-Amz-Credential=AKIARZNKTAO7U6UN77MP%2F20201130%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-SignedHeaders=host&X-Amz-Date=20201130T094845Z&X-Amz-Signature=9b35288654c79b895b900198e5a75e5fd00d447dd7f487445897dad6f4301fc3)  providing details on model assumptions and the main equations.
Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries.
Download the - [OCHA-Bucky model card](https://s3.eu-central-1.amazonaws.com/hdx-ckan-filestore-prod/resources/89a2ff67-ef20-4005-9732-bfc23d76bf4b/ocha-bucky-model-card.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Expires=180&X-Amz-Credential=AKIARZNKTAO7U6UN77MP%2F20201130%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-SignedHeaders=host&X-Amz-Date=20201130T095024Z&X-Amz-Signature=a322a7e660bfa47675a9f6b16f0c25105c1b55b5c2407652182d0a90c91c8554)  created according to the Centre’s Peer Review Framework.

The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels. 

Tags: covid-19
Organization: Johns Hopkins Applied Physics Lab
Somalia: Projected COVID-19 Sub-national Cases

The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts.

Access the - [code repository](https://github.com/OCHA-DAP/pa-ocha-bucky) , including all the source code scripts necessary to run the model.
View the - [technical documentation](https://ocha-bucky.readthedocs.io/en/latest/) and  - [FAQs](https://ocha-bucky.readthedocs.io/en/latest/faq.html) explaining how to configure and run the source code in the repository.
Download the - [methodology paper](https://s3.eu-central-1.amazonaws.com/hdx-ckan-filestore-prod/resources/2d9592f8-2980-4466-96f5-f0de23ea7ffa/ochabucky_final.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Expires=180&X-Amz-Credential=AKIARZNKTAO7U6UN77MP%2F20201130%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-SignedHeaders=host&X-Amz-Date=20201130T094845Z&X-Amz-Signature=9b35288654c79b895b900198e5a75e5fd00d447dd7f487445897dad6f4301fc3)  providing details on model assumptions and the main equations.
Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries.
Download the - [OCHA-Bucky model card](https://s3.eu-central-1.amazonaws.com/hdx-ckan-filestore-prod/resources/89a2ff67-ef20-4005-9732-bfc23d76bf4b/ocha-bucky-model-card.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Expires=180&X-Amz-Credential=AKIARZNKTAO7U6UN77MP%2F20201130%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-SignedHeaders=host&X-Amz-Date=20201130T095024Z&X-Amz-Signature=a322a7e660bfa47675a9f6b16f0c25105c1b55b5c2407652182d0a90c91c8554)  created according to the Centre’s Peer Review Framework.

The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels. 

Tags: covid-19, hxl
Organization: Johns Hopkins Applied Physics Lab
Afghanistan - Who does What Where (July to September 2020)

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed [here](https://www.humanitarianresponse.info/en/operations/afghanistan/3w). 

Tags: hxl, operational capacity, operational presence, who is doing what and where-3w-4w-5w
Organization: OCHA Afghanistan
Sudan: Projected COVID-19 Sub-national Cases

The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts.

Access the - [code repository](https://github.com/OCHA-DAP/pa-ocha-bucky) , including all the source code scripts necessary to run the model.
View the - [technical documentation](https://ocha-bucky.readthedocs.io/en/latest/) and  - [FAQs](https://ocha-bucky.readthedocs.io/en/latest/faq.html) explaining how to configure and run the source code in the repository.
Download the - [methodology paper](https://s3.eu-central-1.amazonaws.com/hdx-ckan-filestore-prod/resources/2d9592f8-2980-4466-96f5-f0de23ea7ffa/ochabucky_final.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Expires=180&X-Amz-Credential=AKIARZNKTAO7U6UN77MP%2F20201130%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-SignedHeaders=host&X-Amz-Date=20201130T094845Z&X-Amz-Signature=9b35288654c79b895b900198e5a75e5fd00d447dd7f487445897dad6f4301fc3)  providing details on model assumptions and the main equations.
Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries.
Download the - [OCHA-Bucky model card](https://s3.eu-central-1.amazonaws.com/hdx-ckan-filestore-prod/resources/89a2ff67-ef20-4005-9732-bfc23d76bf4b/ocha-bucky-model-card.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Expires=180&X-Amz-Credential=AKIARZNKTAO7U6UN77MP%2F20201130%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-SignedHeaders=host&X-Amz-Date=20201130T095024Z&X-Amz-Signature=a322a7e660bfa47675a9f6b16f0c25105c1b55b5c2407652182d0a90c91c8554)  created according to the Centre’s Peer Review Framework.

The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels. 

Tags: covid-19, hxl
Organization: Johns Hopkins Applied Physics Lab
Multi-purpose cash transfers and health among vulnerable Syrian refugees in Lebanon

This is the underlying data for a manuscript published in BMC Public Health (doi: 10.1186/s12889-021-11196-8). The manuscript presents findings from a prospective cohort study conducted from May 2018 through July 2019 to evaluate the impact of MPCs on health care-seeking and expenditures by Syrian refugees in Lebanon.

Organization: Johns Hopkins School of Public Health
Multi-purpose cash transfers and health among vulnerable Syrian refugees in Jordan: A prospective cohort study

This is the underlying data for a manuscript titled "Multi-purpose cash transfers and health among vulnerable Syrian refugees in Jordan: A prospective cohort study" to be published in PLOS Global Public Health . The manuscript presents findings from a prospective cohort study conducted from May 2018 through July 2019 to evaluate the impact of MPCs on health care-seeking and expenditures by Syrian refugees in Jordan.

Organization: Johns Hopkins School of Public Health
Improving Diabetes Control for Syrian Refugees in Jordan: A Longitudinal Cohort Study Comparing the Effects of Cash Transfers and Health Education Interventions

This is the underlying data for a manuscript currently pending publication. The manuscript presents findings from a quasi-experimental prospective cohort study was implemented from October 2018 through January 2020 to assess the effectiveness of multi-purpose cash, community health volunteer-led education, and conditional cash transfers with respect to health measures among Syrian refugees with type II diabetes in Jordan.

Organization: Johns Hopkins School of Public Health
South Sudan - Village Assessment - Health Facilities - [IOM-DTM]

This survey was conducted by IOM DTM covering 182 out of 219 bomas (achieving 83 per cent coverage) in Wau, Rubkona, Bor South, Torit, Magwi, Aweil Centre and Malakal counties.

The dataset has health facilities' names, locations and the services available there.

Tags: geodata, health
Organization: International Organization for Migration (IOM)
South Sudan - Village Assessment - Multi Sector Services Availability - [IOM-DTM]

This survey was conducted by IOM DTM covering 182 out of 219 bomas (achieving 83 per cent coverage) in Wau, Rubkona, Bor South, Torit, Magwi, Aweil Centre and Malakal counties.

The dataset has multi sector services availability names, locations and the services available there.

Organization: International Organization for Migration (IOM)
Nepal Displacement - [IDPs] - Baseline Assessment - Floods2020 - [IOM DTM]

Large-scale flooding and landslides have been triggered in several districts across Nepal following heavy rainfalls in July 2020. From the onset of monsoon on 12 June until 25 July, 130 people lost their lives, 115 were injured and 51 went missing due to floods and landslides according to the National Disaster Risk Reduction and Management Authority. 

Tags: affected population, baseline population, displacement, flooding, hxl, internally displaced persons-idp, natural disasters
Organization: International Organization for Migration (IOM)