Assessing the quality of geospatial linked data – experiences from Ordnance Survey Ireland (OSi)

Ordnance Survey Ireland (OSi) is Ireland’s national mapping agency that is responsible for the digitisation of the island’s infrastructure in terms of mapping. Generating data from various sensors (e.g. spatial sensors), OSi build its knowledge in the Prime2 framework, a subset of which is transformed into geo-Linked Data. In this paper we discuss how the quality of the generated sematic data fares against datasets in the LOD cloud. We set up Luzzu, a scalable Linked Data quality assessment framework, in the OSi pipeline to continuously assess produced data in order to tackle any quality problems prior to publishing

Assessing the quality of geospatial linked data – experiences from Ordnance Survey Ireland (OSi)

Ordnance Survey Ireland (OSi) is Ireland’s national mapping agency that is responsible for the digitisation of the island’s infrastructure in terms of mapping. Generating data from various sensors (e.g. spatial sensors), OSi build its knowledge in the Prime2 framework, a subset of which is transformed into geo-Linked Data. In this paper we discuss how the quality of the generated sematic data fares against datasets in the LOD cloud. We set up Luzzu, a scalable Linked Data quality assessment framework, in the OSi pipeline to continuously assess produced data in order to tackle any quality problems prior to publishing

Innovazioni nello spazio di culto fra basso Medioevo e Cinquecento: La perdita dell’orientamento liturgico e la liberazione della navata

Geoff, the geospatial form and function vocabulary, is a comprehensive RDF-based spatial object classification scheme based on a separation of the concepts of form and function. Geoff is based on our analysis of the extensive (over 50 million spatial object instances) Digital Landscape Model (DLM) Core model maintained by Ordnance Survey Ireland (OSi). We propose Geoff as there are currently no open geospatial form and function classification systems that cover the full range of geospatial objects (from buildings and roads to lakes and other natural features) modelled as Linked Data or in any other formalism. Geoff is a generalization of the DLM Core schema and adopts the GeoSPARQL ontology. Geoff was initially developed to make these classifications available for OSi’s geospatial Linked Data as they facilitate the publications of more expressive models of spatial features. For example, to state that a church building (form) is now used as apartments (function). Geoff is now presented to the wider community for reuse and extension to meet their own needs. Geoff supports geospatial queries based on form and function and interlinking of geo-information datasets using different form and function code lists. The Geoff ontology follows Linked Data publishing best practice in terms of available metadata, documentation, and quality assurance

Publishing Authoritative Geospatial Data to Support Interlinking of Building Information Models

Building Information Modelling (BIM) is a key enabler to support integration of building data within the buildings life cycle (BLC) and is an important aspect to support a wide range of use cases, related to intelligent automation, navigation, energy efficiency, sustainability and so forth. Open building data faces several challenges related to standardization, data interdependency, data access, and security. In addition to these technical challenges, there remains the barrier among BIM developers who wish to protect their intellectual property, as full 3D BIM development requires expertise and effort. This means that there is often limited availability of building data. However, a Linked Data approach to BIM, combined with a supporting national geospatial identifier infrastructure makes interlinking and controlled sharing of BIM models possible. In Ireland, the Ordnance Survey Ireland (OSi) maintains a substantial data set, called Prime2, which includes not only building GIS data (polygon footprint, geodetic coordinate), but also additional building specific data (e.g. form, function and status). The data set also includes change information, recording when changes took place and who captured and validated those changes. This paper presents the development of a national geospatial identifier infrastructure based on an OSi building ontology that supports capturing OSi building data as RDF. The paper details the different steps required to generate the ontology and publish the data. First, an initial analysis of the data set to generate the ontology is discussed. This includes identification of mappings to existing standards, e.g. GeoSPARQL to handle geometries and PROV-O to handle provenance, to the development of R2RML mappings to generate the RDF and the method for deploying the ontology and the building graphs. This data is then made available dependent on different licensing agreements handled by an access control approach. Methods are then presented to support the interlinking of the authoritative data with other building data standards and data sets using geolocation, followed finally by discussion and future wor