@prefix adms: . @prefix dcatap: . @prefix owl: . @prefix skos: . @prefix rdfs: . @prefix vcard: . @prefix dct: . @prefix rdf: . @prefix ns14: . @prefix locn: . @prefix dcat: . @prefix prov: . @prefix foaf: . @prefix dc: . a dcat:CatalogRecord, foaf:Document; dct:identifier "e4ca40d4-a6bb-399b-e053-0937940aef71"; dct:created "2025-04-03T00:00:00Z"; dct:modified "2026-10-05T00:00:00Z"; dct:language ; foaf:primaryTopic ; dct:title "Property Subsidence Assessment dataset 2022" . a skos:Concept, dct:LinguisticSystem; skos:prefLabel "eng" . a dcat:Dataset; dct:title "Property Subsidence Assessment dataset 2022"; dct:description "The BGS Property Subsidence Assessment (PSA) dataset provides insurers and homeowners access to a better understanding of the shrink-swell hazard at both the individual property and/or postcode level for England and Wales. It builds upon the GeoSure shrink-swell data by mapping the hazard to the individual building polygon and considering the other susceptibility factors of building type, foundation depth, and drainage and tree proximity. The user receives GIS building polygons with an overall susceptibility to subsidence score between 1-100. Scores are also classified from non-plastic to very high. Each building polygon is also scored from 1-10 for each subsidence factor (geology, foundation, drainage, building type, building storey and tree proximity). Postcode data is also available as a table showing the ‘average’ PSA score for all buildings within the postcode. The identification of shrink-swell related subsidence prone areas, alongside the inclusion of potential sources to exacerbate this phenomena, can better inform insurers and homeowners and form the basis to make decisions concerning prevention and remediation. The product enhances geological information obtained from GIP and GeoSure via the inclusion of the crucial shrink-swell susceptibility factors (proximity to trees and foundation depth). This therefore allows the derivation of a risk element for the housing stock at Building level, which is then generalised to Postcode level."; dct:identifier "http://data.bgs.ac.uk/id/dataHolding/13607951"; dct:created "2022-01-01T00:00:00Z"; dct:modified "2026-10-05T00:00:00Z"; dct:language ; dcat:contactPoint _:node1k4bdo1kax52822, _:node1k4bdo1kax52823, _:node1k4bdo1kax52824, _:node1k4bdo1kax52825; dcat:theme _:node1k4bdo1kax52826, _:node1k4bdo1kax52827, _:node1k4bdo1kax52828, _:node1k4bdo1kax52829, _:node1k4bdo1kax52830, _:node1k4bdo1kax52831, _:node1k4bdo1kax52832, _:node1k4bdo1kax52833, _:node1k4bdo1kax52834; dct:type _:node1k4bdo1kax52835; dcat:landingPage ; dct:spatial _:node1k4bdo1kax52836; dct:temporal _:node1k4bdo1kax52837; prov:wasUsedBy _:node1k4bdo1kax52838, _:node1k4bdo1kax52841; dcat:distribution _:node1k4bdo1kax52844; dct:accrualPeriodicity ; dct:provenance _:node1k4bdo1kax52846 . _:node1k4bdo1kax52822 a vcard:Kind; vcard:title "British Geological Survey"; vcard:role "distributor"; vcard:hasEmail "enquiries@bgs.ac.uk" . _:node1k4bdo1kax52823 a vcard:Kind; vcard:title "British Geological Survey"; vcard:role "pointOfContact"; vcard:hasEmail "enquiries@bgs.ac.uk" . _:node1k4bdo1kax52824 a vcard:Kind; vcard:title "British Geological Survey"; vcard:role "distributor"; vcard:hasEmail "not available" . _:node1k4bdo1kax52825 a vcard:Kind; vcard:title "British Geological Survey"; vcard:role "pointOfContact"; vcard:hasEmail "not available" . _:node1k4bdo1kax52826 a skos:Concept; skos:prefLabel "NERC_DDC" . _:node1k4bdo1kax52827 a skos:Concept; skos:prefLabel "UK Location (INSPIRE)" . _:node1k4bdo1kax52828 a skos:Concept; skos:prefLabel "Citable Data" . _:node1k4bdo1kax52829 a skos:Concept; skos:prefLabel "Subsidence" . _:node1k4bdo1kax52830 a skos:Concept; skos:prefLabel "Foundations" . _:node1k4bdo1kax52831 a skos:Concept; skos:prefLabel "Property damage" . _:node1k4bdo1kax52832 a skos:Concept; skos:prefLabel "Geology" . _:node1k4bdo1kax52833 a skos:Concept; skos:prefLabel "EAW" . _:node1k4bdo1kax52834 a skos:Concept; skos:prefLabel "ENGLAND & WALES [id=149000]" . _:node1k4bdo1kax52835 a skos:Concept; skos:prefLabel "Dataset" . _:node1k4bdo1kax52836 a dct:Location; locn:geometry "{\"type\":\"Polygon\",\"coordinates\":[[[-5.8,49.9],[2.0,49.9],[2.0,55.8],[-5.8,55.8],[-5.8,49.9]]]}" . _:node1k4bdo1kax52837 a dct:PeriodOfTime; dcat:startDate "2011-01-01T00:00:00Z"; dcat:endDate "2022-01-01T00:00:00Z" . _:node1k4bdo1kax52838 a prov:Activity; prov:used ; prov:qualifiedAssociation _:node1k4bdo1kax52839; prov:generated . _:node1k4bdo1kax52839 a prov:hadPlan; prov:wasDerivedFrom _:node1k4bdo1kax52840 . _:node1k4bdo1kax52840 dct:title "INSPIRE Implementing rules laying down technical arrangements for the interoperability and harmonisation of Geology" . a rdf:type . _:node1k4bdo1kax52841 a prov:Activity; prov:used ; prov:qualifiedAssociation _:node1k4bdo1kax52842; prov:generated . _:node1k4bdo1kax52842 a prov:hadPlan; prov:wasDerivedFrom _:node1k4bdo1kax52843 . _:node1k4bdo1kax52843 dct:title "Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services" . _:node1k4bdo1kax52844 a dcat:Distribution; dcat:accessURL ; dct:title "Citation Information - Digital Object Identifier (DOI)"; dct:description "British Geological Survey. (2022). Property Subsidence Assessment dataset 2022. British Geological Survey. (Dataset). https://doi.org/10.5285/4265b377-0220-44a8-9496-eb2d2c0eb561"; adms:representationTechnique _:node1k4bdo1kax52845 . _:node1k4bdo1kax52845 a skos:Concept; skos:prefLabel "WWW:LINK-1.0-http--related" . a skos:Concept, dct:Frequency . _:node1k4bdo1kax52846 a dct:ProvenanceStatement; rdfs:label "Input data: OS OpenMap Local building polygons GeoSure shrink-swell National Tree Map (Bluesky) Office for National Statistics (UK property build period) Office for National Statistics (UK property type) OS Code Point open Process: GeoSure and the other input datasets are mapped to the OS Open building polygons. Each building is then scored for each input factor. Input factors are then combined via a weighted algorithm to derive the PSA score for each building, this score is then classified into the PSA classes. Building polygon scores are aggregated to produce the postcode score. Processing was carried out using python scripts in ARCGIS." .