<p><strong>Abstract.</strong> Governmental agencies, companies and other organisations benefit from sharing data effectively using a harmonised data specification. In asset management, data standards exist from the construction phase through to the operation of the building. A gap exists within transport agencies in Australia and New Zealand for the road asset information exchange. The expectation is that by transferring road asset data from one system to another using a commonly accepted data standard, annual cost savings are predicted to be achieved within these countries of between $65 and $130<span class="thinspace"></span>million. Current developments are investigating standardising road asset data. This research provides a critical review of data standards for vertical and horizontal infrastructure, namely buildings and roads, and reviews current approaches that deal with the challenge of information exchange for the road network.</p>

<p><strong>Abstract.</strong> Data harmonisation improves the coherence between data sets within and across themes and is, therefore, a very helpful tool for governmental agencies, companies and other organisations that share their data. This research focuses on horizontal infrastructures, namely roads, and proposes a new strategy to apply Semantic Web Technologies. The aim is to understand if their application is efficient and effective in filling the gap of data harmonisation in Australia’s and New Zealand’s road asset management systems within the definition of location. The proposed strategy has three stages. First, available international data standards for road assets will be analysed to identify the gaps within these standards and create recommendations towards an improved standard. The second stage is for the location aspect within each stage of the life cycle of asset management with respect to existing road asset data standards. Finally, in a third stage Semantic Web Technologies, ontologies and semantic rules will be used to build a prototype solution for road asset data conflation by merging multiple data sources that share no common lineage. The application of these technologies will allow for easier search and discovery of this data as well as facilitate the automated processing and updating of this data over the Web.</p>

<p><strong>Abstract.</strong> Road network asset management is a challenging task as many data sources with different road asset location accuracies are available. In Australia and New Zealand transport agencies are investigating into harmonisation of road asset data, whereby two or more data sets are merged to create a new data set. Currently, identifying relations between road assets of the same meaning is not always possible, as road authorities of these countries use their own data structures and standards. This paper employs SemanticWeb Technologies, such as RDF/Turtle ontologies and semantic rules to enable road network conflation (merge multiple data sets without creating a new data set) as a first step towards data harmonisation by means of information exchange, and shifts road network data from intersections and road nodes to data sets considering the accuracy of the data sets in the selected area. The data integration from <i>GeoJSON</i> into RDF/Turtle files is processed with <i>Python</i>. A geographic coordinates shifting algorithm reads unique data entries that have been extracted from RDF/Turtle into JSON-LD and saves the processed data in their origin file format, so that a closed data flow can be approached.</p>