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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 using Resource Description Framework (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 work.

Building Information Modelling (BIM) is a key enabler to support integration of building data within the buildings life cycle and is an important aspect to support a wide range of use cases, related to building navigation, control, sustainability, etc. Open BIM 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 BIM models. In Ireland, the Ordnance Survey Ireland (OSi) has a substantial dataset which includes not only GIS data (polygon footprint, geodetic coordinate), but also additional building specific data (form and function). In this paper we demonstrate the use of an applied and tested methodology for uplifting GIS data (relational data) into RDF (GeoSPARQL and OSi ontology) and demonstrate how this data is used for interlinking to other building data with an initial, simple exploratory example, taken from DBpedia. By interlinking building data and making it available, new insights about buildings in Ireland can be made, currently not possible due to lack of availability of data. This is an important step towards the iterative integration of ever more complex BIM models into the wider web of data to support the aforementioned use cases.

The concept of "location" provides one a useful dimension to explore, align, combine, and analyze data. Though one can rely on bespoke GIS systems to conduct their data analyses, we aim to investigate the feasibility of using Semantic Web technologies to leverage the exploration and enrichment of data in CSV files with the vast amount of geographic and geospatial data that are available on the Linked Data Web. In this paper, we propose a lightweight method and set of tools for: uplift - transforming non-RDF resources into RDF documents; creating links between RDF datasets; client-side processing of geospatial functions; and downlift - transforming (enriched) RDF documents back into a non-RDF format. With this approach, people who wish to avail of the spatial dimension in data can do so from their client (e.g., in a browser) without the need to rely on bespoke technology. This could be of great utility for decision makers and scholars, amongst others. We applied our approach on datasets that are hosted on the Irish open data portal, and combined it with authoritative geospatial data made available by Ordnance Survey Ireland (OSi). Albeit aware that our approach cannot compete with specialist tools, we do demonstrate its feasibility. Though currently conducted for enriching datasets hosted on the Irish open data portal, future work will look into broader governance and provenance aspects of geospatial data enriched dataset management.

Data.geohive.ie aims to provide an authoritative service for serving Ireland?s national geospatial data as Linked Data. The service currently provides information on Irish administrative boundaries and the boundaries used for the Irish 2011 census. The service is designed to support two use cases: serving boundary data of geographic features at various level of detail and capturing the evolution of administrative boundaries. In this paper, we report on the development of the service and elaborate on some of the informed decisions concerned with the URI strategy and use of named graphs for the support of aforementioned use cases ? relating those with similar initiatives. While clear insights on how the data is being used are still being gathered, we provide examples of how and where this geospatial Linked Data dataset is used.