**THIS DATASET HAS BEEN WITHDRAWN** Ethiopia experienced severe drought in 2015-16. Many rural communities experienced declines in the performance of their water supply systems. As a result UNICEF commissioned a real-time monitoring and responsive operation and maintenance programme for point source rural water supplies across Central, Northern and Eastern Ethiopia. The water point monitoring survey was coordinated by UNICEF and conducted by World Vision Ethiopia and Oxfam Ethiopia. Data was collected between January and May 2016. Akvo Flow, a mobile survey tool, was used to collect data using questionnaires which were completed by enumerators and uploaded to central servers in near real time. The dataset includes data on functionality, access, usage and water quantity from 5196 rural water points. UNICEF provided the dataset to BGS. BGS reorganised, cleaned, and conducted quality control and analysis of the dataset. A companion paper has been published with more details of the methodology and results of the monitoring survey, https://doi.org/10.1038/s41467-020-14839-3

High frequency (100 Hz) data from two horizontal induction coils measuring the Earth's magnetic field at the Eskdalemuir Observatory in the United Kingdom. The data covers the period from January 2019 to December 2019. Also included are examples of Matlab code and the frequency calibration files to convert to the raw data to SI units. Thumbnail spectrograms and metadata are also supplied.

High frequency (100 Hz) data from two horizontal induction coils measuring the Earth's magnetic field at the Eskdalemuir Observatory in the United Kingdom. The data covers the period from January 2018 to December 2018. Also included are examples of Matlab code and the frequency calibration files to convert to the raw data to SI units. Thumbnail spectrograms and metadata are also supplied.

The newGeoSure Insurance Product (newGIP) provides the potential insurance risk due to natural ground movement. It incorporates the combined effects of the 6 GeoSure hazards on (low-rise) buildings: landslides, shrink-swell clays, soluble rocks, running sands, compressible ground and collapsible deposits. These hazards are evaluated using a series of processes including statistical analyses and expert elicitation techniques to create a derived product that can be used for insurance purposes such as identifying and estimating risk and susceptibility. The evaluated hazards are then linked to a postcode database - the Derived Postcode Database (DPD), which is updated biannually with new releases of Ordnance Survey Code-Point® data (current version used: 2020.1). The newGIP is provided for national coverage across Great Britain (not including the Isle of Man). This product is available in a range of GIS formats including Access (*.dbf), ArcGIS (*.shp) or MapInfo (*.tab). The newGIP is produced for use at 1:50 000 scale providing 50 m ground resolution.

This datasets contains 323 observations of borehole breakouts across and drilling induced tensile fractures from borehole imaging used to re-characterise the UK stress field orientation in 2016. This was published in the Journal of Marine and Petroleum Geology and is openly available using doi:10.1016/j.marpetgeo.2016.02.012 The observations relate to 39 wells from Central and Northern England and are provided with links to screen grabs of the images for clarity. The basic well meta data is supplied along with a description of the dataset. The Images were generated in the IMAGE DISPLAY module of the Landmark RECALL software. and are supplied on an “as shown” basis. Descriptions of the tools and the techniques used are listed in the accompanying paper: KINGDON, A., FELLGETT, M. W. & WILLIAMS, J. D. O. 2016. Use of borehole imaging to improve understanding of the in-situ stress orientation of Central and Northern England and its implications for unconventional hydrocarbon resources. Marine and Petroleum Geology, 73, 1-20.

A geographic information system (GIS) heat flow and temperature model of East Africa created by extracting data from open sources into a series of shapefiles and rasters containing information on geothermal sites, hot spring locations, digital elevation model, surface temperature, geothermal gradients, thermal conductivities and heat flow data, major faults, surface geology, crustal basement, electrification grid system and population density across East Africa. This data is stored in the World Geodetic System (WGS) 1984 Geographic Projection System.

This dataset provides digital spatial information on the location of mineral resources in Wales at a scale of 1:50 000. The term ‘mineral resources’ has a definition under international standards that includes both an economic and geological dimension. These data are based primarily on mapped geology with limited assessment of economics. Therefore, the term ‘mineral resources’ is used here in a broad sense. The dataset allows users to visualise the extent and distribution of mineral resources and to relate them to other forms of land-use (such as urban areas or designated environmentally sensitive areas) or to other factors (such as transport infrastructure and conservation information). The British Geological Survey (BGS) was awarded a grant from the Welsh Assembly Government Aggregates Levy Fund in 2009 to provide a comprehensive, relevant and accessible information base to enhance the sustainability of mineral resources for Wales. BGS co-funded this project through its Sustainable Mineral Solutions project. This work was completed in 2010. This dataset comprises the digital GIS files which were produced through this project. The major elements of minerals information presented on the maps are; the geological distribution of all onshore mineral resources in Wales, the location of mineral extraction sites, the recorded occurrences of metallic minerals, the recorded location of former slate quarries and significant areas of slate waste and the recorded location of historic building stone quarries. In 2020 minor revisions to geometry and attributes were made in in response to minor corrections that were required. The paper maps were not re-released with these data updates. Point data for mineral occurrence and mine site data has not been included in this revision as these data are superseded by other BGS datasets, such as the BGS BritPits database of mines and quarries. The BGS Mineral Resource data does not determine mineral reserves and therefore does not denote potential areas of extraction. Only onshore, mainland mineral resources are included in the dataset. This dataset has been produced by the collation and interpretation of mineral resource data principally held by the British Geological Survey. The mineral resource data presented are based on the best available information, but are not comprehensive and their quality is variable. The dataset should only be used to show a broad distribution of those mineral resources which may be of current or potential economic interest.

This dataset provides digital spatial information on the location of mineral resources in the central belt of Scotland at a scale of 1:50 000. The term ‘mineral resources’ has a definition under international standards that includes both an economic and geological dimension. These data are based primarily on mapped geology with limited assessment of economics. Therefore, the term ‘mineral resources’ is used here in a broad sense. The dataset allows users to visualise the extent and distribution of mineral resources and to relate them to other forms of land-use (such as urban areas or designated environmentally sensitive areas) or to other factors (such as transport infrastructure and conservation information). The British Geological Survey (BGS) was awarded a grant from the Scottish Government Aggregates Levy Fund in 2007 to provide a comprehensive, relevant and accessible information base to enhance the sustainability of mineral resources for 18 local authorities in the central belt of Scotland. BGS co-funded this project through its Sustainable Mineral Solutions project. This work was completed in March 2008. This dataset comprises the digital GIS files which were produced through this project. In 2020 minor revisions to geometry and attributes were made in in response to minor corrections that were required. The paper maps were not re-released with these data updates. The major elements of minerals information presented are the geological distribution of all mineral resources in the central belt of Scotland. The BGS Mineral Resource data does not determine mineral reserves and therefore does not denote potential areas of extraction. Only onshore, mainland mineral resources are included in the dataset. This dataset has been produced by the collation and interpretation of mineral resource data principally held by the British Geological Survey. The mineral resource data presented are based on the best available information, but are not comprehensive and their quality is variable. The dataset should only be used to show a broad distribution of those mineral resources which may be of current or potential economic interest.

This dataset provides digital spatial information on the location of mineral resources in England at a scale of 1:50 000. The term ‘mineral resources’ has a definition under international standards that includes both an economic and geological dimension. These data are based primarily on mapped geology with limited assessment of economics. Therefore, the term ‘mineral resources’ is used here in a broad sense. The dataset allows users to visualise the extent and distribution of mineral resources and to relate them to other forms of land-use (such as urban areas or designated environmentally sensitive areas) or to other factors (such as transport infrastructure and conservation information). The dataset is derived from a set of commissioned projects to prepare a series of mineral resource maps based on counties or amalgamations of counties. Maps for England were commissioned by the central government department with responsibility for mineral planning at the time (Department of the Environment (DoE), Department of the Environment, Transport and the Regions (DETR), Department for Transport, Local Government and the Regions (DTLR), Office of the Deputy Prime Minister (ODPM), and the Department for Communities and Local Government (DCLG) between 1994 and 2006. Each map produced (with an accompanying report describing the mineral resources depicted on the map) is available to download, as a PDF file from the BGS-hosted website: www.MineralsUK.com. During 2011-2012 revisions were made to areas of the resource linework. These changes were made as a result of new research and release of a new version of DiGMap (v5). This work was on an ad hoc basis but affects all resource layers. In 2020 minor revisions to geometry and attributes were made in in response to minor corrections that were required. The paper maps were not re-released with these data updates. The BGS Mineral Resource data does not determine mineral reserves and therefore does not denote potential areas of extraction. Only onshore, mainland mineral resources are included in the dataset. This dataset has been produced by the collation and interpretation of mineral resource data principally held by the British Geological Survey. The mineral resource data presented are based on the best available information, but are not comprehensive and their quality is variable. The dataset should only be used to show a broad distribution of those mineral resources which may be of current or potential economic interest.

This dataset presents meteorological records from 3 weather stations around a glacier in southeast Iceland from 2009-2020. The weather stations were installed as part of British Geological Survey’s Glacier Observatory project, and were positioned at different altitudes close to the ice to record glacier weather. The data is in text format, and records key meteorological parameters including temperature, relative humidity, atmospheric pressure, precipitation, wind speed and direction, and solar irradiance. The weather stations were placed around Virkisjökull-Falljökull, an outlet glacier of the Öraefajökull ice cap in south east Iceland (AWS1 at 16°48'19"W, 63°57'53"N; AWS3 at 16°47'5"W, 63°58'13"N, and AWS4 at 16°48'7"W , 63°59'52"N). AWS1 was installed in September 2009, with AWS3 installed in September 2010, and AWS4 in September 2011. AWS3 and AWS4 were decommissioned in August 2018, and AWS1 in May 2020. AWS1 was located 100m from the current glacier margin at 156m a.s.l.; AWS3 sat 50m from the icefall at 444m a.s.l.; and AWS4 was situated on a clifftop overlooking the glacier at 858m a.s.l., close to the Equilibrium Line Altitude of the glacier. These were positioned at different altitudes to determine changes in weather parameters with height, thus producing for example, temperature or humidity gradients. The three stations were wirelessly linked, allowing data from the upper stations to be offloaded to the datalogger on the lower station. On-site downloads were completed using Campbell Scientific LoggerNet 4.x series software. AWS1 maintained mobile phone telemetry enabling automatic remote downloads of data from all stations on a daily basis, and remote access for software updates and health checks. Each AWS supported a slightly different sensor array, depending on the requirements of the site, and were mounted on 1.5m Campbell Scientific tripods. All of the stations were designed around a Campbell Scientific CR800 datalogger, and were solar powered, using combinations of PV panels up to 100W, supplying a Campbell Scientific 25Ah battery mounted on the tripod, plus a 110Ah gel cell battery back up in a separate housing. The data will be of use to researchers and students interested in the weather of southeast Iceland, glacier climate, local influence of glaciers on more regional synoptic weather systems, glacier climate modellers, glacier hydrologists and hydrogeologists. The BGS project was led and coordinated by Dr Jez Everest, technical support and implementation by Heiko Buxel and data Quality Assurance and checking by Dr Jon Mackay. Any periods where equipment malfunction, testing or replacement meant that no or unreliable data were collected are indicated by a ‘NAN’ value in the datasets.