AndreaBozzo/ceres-open-data-index huggingface dataset:
UKCS CO2 storage appraisal rank (ETRS89)

<p><span style='background-color:rgb(255,255,255); color:rgb(0,0,0); font-family:Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, sans-serif; font-size:12pt;'><span style='font-style:normal; font-variant-caps:normal; font-variant-ligatures:none !important; font-weight:400; letter-spacing:normal; line-height:20.85px; margin:0px; padding:0px; text-align:left; text-decoration-color:initial; text-decoration-style:initial; text-indent:0px; text-transform:none; word-spacing:0px;'>This dataset presents the NSTA's CO2 Storage Appraisal Ranking for the UK Continental Shelf (UKCS). The data is structured as a regular hexagonal grid covering the full extent of the UKCS. Each hexagon contains scores for 24 geological formations, ranging from Devonian to Eocene in age, derived from a weighted combination of four input components: lithological character, well data coverage, seismic data coverage, and an NSTA-assigned prioritisation score. An integrated composite score, aggregating the individual formation scores, is also included. Higher scores indicate areas where multiple formations show favourable conditions for CO2 storage appraisal and are therefore prioritised by the NSTA for early appraisal activity. The analysis is preliminary and will be updated as additional data and methodological refinements are incorporated. Full methodology details are available via the CO2 Storage Appraisal Ranking interactive map application.</span></span><span style='background-color:rgb(255,255,255); color:rgb(204,53,149); font-family:Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, sans-serif; font-size:12pt;'><span style='font-style:normal; font-variant-caps:normal; font-variant-ligatures:normal; font-weight:400; letter-spacing:normal; line-height:20.85px; margin:0px; padding:0px; text-align:left; text-decoration-color:initial; text-decoration-style:initial; text-indent:0px; text-transform:none; word-spacing:0px;'>&nbsp;</span></span></p>

Organization: North Sea Transition Authority
UKCS CO2 storage appraisal rank (ED50)

<p><span style='background-color:rgb(255,255,255); color:rgb(0,0,0); font-family:Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, sans-serif; font-size:12pt;'><span style='font-style:normal; font-variant-caps:normal; font-variant-ligatures:none !important; font-weight:400; letter-spacing:normal; line-height:20.85px; margin:0px; padding:0px; text-align:left; text-decoration-color:initial; text-decoration-style:initial; text-indent:0px; text-transform:none; word-spacing:0px;'>This dataset presents the NSTA's CO2 Storage Appraisal Ranking for the UK Continental Shelf (UKCS). The data is structured as a regular hexagonal grid covering the full extent of the UKCS. Each hexagon contains scores for 24 geological formations, ranging from Devonian to Eocene in age, derived from a weighted combination of four input components: lithological character, well data coverage, seismic data coverage, and an NSTA-assigned prioritisation score. An integrated composite score, aggregating the individual formation scores, is also included. Higher scores indicate areas where multiple formations show favourable conditions for CO2 storage appraisal and are therefore prioritised by the NSTA for early appraisal activity. The analysis is preliminary and will be updated as additional data and methodological refinements are incorporated. Full methodology details are available via the CO2 Storage Appraisal Ranking interactive map application.</span></span><span style='background-color:rgb(255,255,255); color:rgb(204,53,149); font-family:Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, sans-serif; font-size:12pt;'><span style='font-style:normal; font-variant-caps:normal; font-variant-ligatures:normal; font-weight:400; letter-spacing:normal; line-height:20.85px; margin:0px; padding:0px; text-align:left; text-decoration-color:initial; text-decoration-style:initial; text-indent:0px; text-transform:none; word-spacing:0px;'>&nbsp;</span></span></p>

Organization: North Sea Transition Authority
UKCS regional aquifers - geology (ETRS89)

<p>The NSTA Regional Aquifer Presence Maps publication contains a series of geological maps, each representing a discrete stratigraphic play interval within the UK Continental Shelf. The feature classes aim to characterise the subsurface geological framework relevant to potential aquifer-based subsurface storage (including CO₂ storage, hydrogen storage, and compressed air energy storage).</p><p><br />Each feature class includes attribute information describing:</p><ul><li>Gross Depositional Environment (GDE) – interpreted paleoenvironmental setting controlling sediment distribution.</li><li>Depositional Facies – sedimentary facies classification.</li><li>Lithology Group and Lithology – simplified lithological descriptors indicating dominant sediment composition.</li><li>Chronostratigraphic Age – standardised age assignment for each interval.</li></ul><p><br />These datasets are built upon the regional geological interpretations produced during the UKCS Regional Geology Maps project undertaken by Lloyd’s Register and the OGA. This work integrated seismic interpretation, well data, field data, stratigraphic correlation, and regional geological understanding to generate consistent interval based geological maps across the basin.</p><p><br />Potential Applications<br />The maps are designed to function as an early-stage screening tool to guide:</p><ul><li>identification of intervals with favourable or unfavourable characteristics for subsurface storage;</li><li>regional assessment of aquifer presence, continuity, and variability;</li><li>prioritisation of areas where more detailed appraisal or data acquisition may be warranted;</li></ul><p><br />While not a substitute for detailed geological modelling or licence scale site characterisation, the maps provide a baseline understanding of the geological context and help focus effort where it is likely to provide the greatest value.</p>

Organization: North Sea Transition Authority
2009 Ortho OSNI

<div style='text-align:left;'><p style='font-size:12pt;'>The primary objective from this project was to acquire historical shoreline information for all of the Northern Ireland coastline. Having this detailed understanding of the coast’s shoreline position and geometry over annual to decadal time periods is essential in any management of the coast.</p><div style='text-align:left;'><p style='font-size:12pt;'>The
historical shoreline analysis was based on all available Ordnance Survey maps
and aerial imagery information. Analysis looked at position and geometry over
annual to decadal time periods, providing a dynamic picture of how the
coastline has changed since the start of the early 1800s.<br /></p><div style='text-align:left;'><p><span style='font-size:12pt;'>Once
all datasets were collated, data was interrogated using the ArcGIS package –
Digital Shoreline Analysis System (DSAS). DSAS is a software package which
enables a user to calculate rate-of</span><font size='3'>-change s</font><span style='font-size:12pt;'>tatistics from multiple historical
shoreline positions. Rate-of-change was collected at 25m intervals and
displayed both statistically and spatially allowing for areas of
retreat/accretion to be identified at any given stretch of coastline.</span><br /></p><p><span style='font-size:16px;'>The DSAS software will produce the following rate-of-change statistics:</span></p><p></p><ol><li><span style='font-size:16px;'>Net Shoreline Movement (NSM) – the distance between the oldest and the youngest shorelines.</span></li><li>Shoreline Change Envelope (SCE) – a measure of the total change in shoreline movement considering all available shoreline positions and reporting their distances, without reference to their specific dates.</li><li>End Point Rate (EPR) – derived by dividing the distance of shoreline movement by the time elapsed between the oldest and the youngest shoreline positions.</li><li>Linear Regression Rate (LRR) – determines a rate of change statistic by fitting a least square regression to all shorelines at specific transects.</li><li>Weighted Linear Regression Rate (WLR) - calculates a weighted linear regression of shoreline change on each transect. It considers the shoreline uncertainty giving more emphasis on shorelines with a smaller error.</li></ol><p></p><p><span style='font-size:16px;'>The end product provided by Ulster University is an invaluable tool and digital asset that has helped to visualise shoreline change and assess approximate rates of historical change at any given coastal stretch on the Northern Ireland coast.</span></p></div></div></div>

Tags: 3d, analysis, coastal, historic, ireland, marine, northern, observatory, rates, shoreline-change, shorelines, survey
Organization: OpenDataNI
March 2022 - North Coast Post-Storm Survey -  LiDAR Point Cloud

<div style='text-align:Left; font-size:12pt;'><p>Fugro were commissioned to undertake a post-storm LiDAR survey of the soft sedimentary areas along the north coast of Northern Ireland in March 2022 This survey was to cover the following areas: Curran Strand, Portrush East Strand, Portstewart Strand and Downhill Beach to Magilligan.</p><div style='text-align:Left; font-size:12pt;'><p>This project was commissioned following the successive storm events during February and March 2022 (Storm Dudley, Storm Eunice and Storm Franklin) which did considerable damage to the sandy beaches along the North Coast. The objective of this survey was to ascertain change which has occurred along these soft sediment coastlines at the north coast since the baseline survey, which was acquired in 2021.</p><div style='text-align:Left; font-size:12pt;'><p>Data was provided in the same format as the topographic LiDAR data collected in the Northern Ireland 3-Dimensional Coastal Survey to allow changes between these two datasets to be ascertained.</p><div style='text-align:Left; font-size:12pt;'><p>This is the LiDAR point cloud provided as an output from this post-storm LiDAR survey.<br /></p></div></div></div></div>

Tags: 3d, cloud, coastal, ireland, lidar, northern, observatory, point, post-storm
Organization: OpenDataNI
Census 21 - English proficiency ward

<div class="ods-dataset-customview-crosslink"><p>This dataset is linked to the following visualization: <a href="https://leicester.huwise.com/explore/assets/visualisation-census-21-english-proficiency-ward/view/">Visualization - Census 21 - English proficiency ward</a></p><hr></div><p>The census is undertaken by the Office for National Statistics every 10 years and gives us a picture of all the people and households in England and Wales. The most recent census took place in March of 2021.</p><p>The census asks every household questions about the people who live there and the type of home they live in. In doing so, it helps to build a detailed snapshot of society. Information from the census helps the government and local authorities to plan and fund local services, such as education, doctors' surgeries and roads.<br></p><p>Key census statistics for Leicester are published on the open data platform to make information accessible to local services, voluntary and community groups, and residents. There is also a <a =""="" href="https://data.leicester.gov.uk/pages/census_ward/" target=" _blank">dashboard</a> published showcasing various datasets from the census allowing users to view data for all wards and compare this with Leicester overall statistics.<br></p><p>Further information about the census and full datasets can be found on the ONS website - <a href="https://www.ons.gov.uk/census/aboutcensus/censusproducts" target="_blank">https://www.ons.gov.uk/census/aboutcensus/censusproducts</a></p><p><b>Proficiency in English</b></p><p>This dataset provides Census 2021 estimates that classify usual residents in England and Wales by their proficiency in English. The estimates are as at Census Day, 21 March 2021.</p><br><p><b>Definition:</b> How well people whose main language is not English (English or Welsh in Wales) speak English.</p><p>This dataset provides details for the electoral wards of Leicester city.</p>

Tags: Census
Organization: Leicester City Council
Boundary

<div style='text-align:Left; font-size:12pt;'><p>A pilot bathymetric LiDAR survey was commissioned in 2021 as part of the NI 3D Coastal Survey. This mapped the nearshore areas of Dundrum Bay and areas of Carlingford Lough. Natural Colour Orthophotography was captured simultaneously.</div></p>

Tags: 3d, coastal, marine, observatory, ortho, orthophotography, survey
Organization: OpenDataNI
2012 Ortho OSNI

<div style='text-align:left;'><p style='font-size:12pt;'>The primary objective from this project was to acquire historical shoreline information for all of the Northern Ireland coastline. Having this detailed understanding of the coast’s shoreline position and geometry over annual to decadal time periods is essential in any management of the coast.</p><div style='text-align:left;'><p style='font-size:12pt;'>The
historical shoreline analysis was based on all available Ordnance Survey maps
and aerial imagery information. Analysis looked at position and geometry over
annual to decadal time periods, providing a dynamic picture of how the
coastline has changed since the start of the early 1800s.<br /></p><div style='text-align:left;'><p><span style='font-size:12pt;'>Once
all datasets were collated, data was interrogated using the ArcGIS package –
Digital Shoreline Analysis System (DSAS). DSAS is a software package which
enables a user to calculate rate-of</span><font size='3'>-change s</font><span style='font-size:12pt;'>tatistics from multiple historical
shoreline positions. Rate-of-change was collected at 25m intervals and
displayed both statistically and spatially allowing for areas of
retreat/accretion to be identified at any given stretch of coastline.</span><br /></p><p><span style='font-size:16px;'>The DSAS software will produce the following rate-of-change statistics:</span></p><p></p><ol><li><span style='font-size:16px;'>Net Shoreline Movement (NSM) – the distance between the oldest and the youngest shorelines.</span></li><li>Shoreline Change Envelope (SCE) – a measure of the total change in shoreline movement considering all available shoreline positions and reporting their distances, without reference to their specific dates.</li><li>End Point Rate (EPR) – derived by dividing the distance of shoreline movement by the time elapsed between the oldest and the youngest shoreline positions.</li><li>Linear Regression Rate (LRR) – determines a rate of change statistic by fitting a least square regression to all shorelines at specific transects.</li><li>Weighted Linear Regression Rate (WLR) - calculates a weighted linear regression of shoreline change on each transect. It considers the shoreline uncertainty giving more emphasis on shorelines with a smaller error.</li></ol><p></p><p><span style='font-size:16px;'>The end product provided by Ulster University is an invaluable tool and digital asset that has helped to visualise shoreline change and assess approximate rates of historical change at any given coastal stretch on the Northern Ireland coast.</span></p></div></div></div>

Tags: 3d, analysis, coastal, historic, ireland, marine, northern, observatory, rates, shoreline-change, shorelines, survey
Organization: OpenDataNI
Footprint

<div style='text-align:Left; font-size:12pt;'><p>Fugro were commissioned to undertake a post-storm LiDAR survey of the soft sedimentary areas along the north coast of Northern Ireland in March 2022 This survey was to cover the following areas: Curran Strand, Portrush East Strand, Portstewart Strand and Downhill Beach to Magilligan.</p><div style='text-align:Left; font-size:12pt;'><p>This project was commissioned following the successive storm events during February and March 2022 (Storm Dudley, Storm Eunice and Storm Franklin) which caused considerable damage to the sandy beaches along the North Coast. The objective of this survey was to ascertain change which has occurred along these soft sediment coastlines at the north coast since the baseline survey, which was acquired in 2021.</p><div style='text-align:Left; font-size:12pt;'><p>Data was provided in the same format as the topographic LiDAR data collected in the Northern Ireland 3-Dimensional Coastal Survey to allow changes between these two datasets to be ascertained.</p><div style='text-align:Left; font-size:12pt;'><p>This is the Natural Colour Orthophotography dataset that was captured as part of the survey.</p></div></div></div></div>

Tags: 3d, coastal, ireland, lidar, marine, northern, observatory, orthophotography, post, storm
Organization: OpenDataNI
September 2022 - North Coast Post-Storm Recovery Survey - LiDAR Point Cloud

<div style='text-align:Left; font-size:12pt;'><p>Fugro were commissioned to undertake a post storm LiDAR survey of the soft sedimentary areas along the north coast of Northern Ireland in March 2022. This survey was to cover the following areas: Curran Strand, Portrush East Strand, Portstewart Strand and Downhill Beach to Magilligan.</p><div style='text-align:Left; font-size:12pt;'><p>This project was commissioned following the successive storm events during February and March 2022 (Storm Dudley, Storm Eunice and Storm Franklin) which did considerable damage to the sandy beaches along the North Coast. The objective of this survey was to ascertain change which has occurred along these soft sediment coastlines at the north coast since the baseline survey, which was acquired in 2021.</p><div style='text-align:Left; font-size:12pt;'><p>Data was provided in the same format as the topographic LiDAR data collected in the Northern Ireland 3-Dimensional Coastal Survey to allow changes between these two datasets to be ascertained.</p><div style='text-align:Left; font-size:12pt;'><p>Later in the year Fugro were commissioned to undertake a second LiDAR survey of the north coast from White Rocks to Magilligan in September 2022. The aim of this repeat survey was to ascertain the levels of recovery along the soft sediment coastlines since March 2022.</p><div style='text-align:Left; font-size:12pt;'><p>As with the initial survey undertaken by Fugro this topographic LiDAR survey collected data from the intertidal area to 10m inland for the same soft sediment areas along the north coast, with data being acquired at 0.5m resolution. The survey was quite restrictive when it could be flown: it had to be 2 hours either side of Low Water, during clear conditions below 6000ft, sun had to be at a suitable angle to capture imagery and as photography was being captured the survey could only be flown during day light hours. </p><div style='text-align:Left; font-size:12pt;'><p>All data collected was to be directly comparable with the data collected in the initial post storm Survey undertaken, as this would help us to understand and accurately quantify how our soft, sedimentary coastlines respond and recover from extreme storm events.</p><div style='text-align:Left; font-size:12pt;'><p>This is the LiDAR point cloud created from the post-storm recovery LiDAR data.<br /></p></div></div></div></div></div></div></div>

Tags: 3d, cloud, coastal, ireland, lidar, northern, observatory, point, post-storm
Organization: OpenDataNI
Boundary

Orthophotography is aerial imagery that has been geometrically corrected. An orthophoto is an image that is free of distortion, and which is characterised by a uniform scale over its entire surface - it has been ortho-rectified. <div><br /></div><div>Orthophotography was captured as part of the 2021 NI 3D Coastal Survey. Coverage extends across the entire Northern Ireland coastline, including the intertidal area, and extending approximately 200 meters landward of the high water mark. </div><div><br /></div><div>Natural Colour orthophotography imagery was captured with a 10cm resolution.</div>

Tags: 3d, coastal, marine, observatory, ortho, orthophotography, survey
Organization: OpenDataNI
Mercury Potential Project

<div style='background-color:rgb(255, 255, 255); color:rgb(76, 76, 76); font-family:&quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size:15px; font-style:normal; font-variant-caps:normal; font-variant-ligatures:normal; font-weight:400; letter-spacing:normal; text-align:start; text-decoration-color:initial; text-decoration-style:initial; text-indent:0px; text-transform:none; word-spacing:0px;'><span style='font-size:15px;'>In 2022 DAERA contracted Tetra Tech to provide a report on a high level assessment of historic land uses in NI that may have resulted in mercury contamination.&nbsp; EU Regulation 2017/852&nbsp; requires member states to identify and assess sites contaminated with Mercury and this project is part of Ni's response to that.&nbsp; This dataset goes with that report.&nbsp; DoE Industrial Profiles (claire.co.uk) were used to assess the potential of Mercury with a particular historical industrial land use and hence come up with a 4-tier risk rating based on that.&nbsp; The NIEA Historical Land Use database provides the basis for much of the analysis contained in the report.</span></div><p><span style='background-color:rgb(255,255,255); color:rgb(76,76,76); font-family:&quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size:15px;'><span style='font-style:normal; font-variant-caps:normal; font-variant-ligatures:normal; font-weight:400; letter-spacing:normal; text-align:start; text-decoration-color:initial; text-decoration-style:initial; text-indent:0px; text-transform:none; word-spacing:0px;'>This dataset shows the locations of Historical Industrial Land Use in Northern Ireland, with a risk rating for the potential of the site to contain Mercury.&nbsp; No ground truthing or soil analysis was carried out as part of this project, so potential is the key word here.</span></span></p>

Tags: contanimated-land, historical-land-use, industry-profiles, mercury-northern-ireland, uk
Organization: OpenDataNI
Boundary

<div style='text-align:Left; font-size:12pt;'><p>In 2021 a high resolution (minimum 10 meters) satellite-derived bathymetry survey was complete for the full extent of the Northern Ireland marine area to a maximum depth of 8-11 meters. This was undertaken as part of the NI 3D Coastal Survey.</p><div style='text-align:Left; font-size:12pt;'><p>Images which were used date from 2012 but the majority were captured from 2018 onwards.  Data was acquired from two sources: </p><p>•	Sentinel 2 sensors which produces a 10m spatial resolution bathymetric grid and </p><p>•	Commercial satellite data, which allow for a higher 2m spatial resolution.
</p><div style='text-align:Left; font-size:12pt;'><p>This is the Digital Terrain Model that was created from the satellite-derived bathymetry dataset.</p><div style='text-align:Left; font-size:12pt;'></div></div></div></div>

Tags: 3d, bathymetry, coastal, derived, marine, observatory, satellite, survey
Organization: OpenDataNI