ELITE-S Marie Skłodowska-Curie Research Project

LinkedDataOps:Linked Data Operations Based on Quality Process Cycle

Data Quality for Geospatial Linked Data

Image Credits: Ordnance Survey Ireland via data.geohive.ie

Geospatial data is vital for many application scenarios, such as navigation, logistics, and tourism. Large number of currently available datasets contain geospatial aspect (e.g., DBpedia, Wikidata) and, integrating them into public and private organizations has immense advantages on the social, economic and scientific areas. The upsurge in Linked data related presentations in recent Eurogeographics data quality workshop shows the big interest in Geospatial Linked Data (GLD) in national mapping agencies. This is due to GLD, allowing discovery and access using the standard mechanisms of the Web, simplifies the process of generating interoperable geospatial infrastructure which currently requires huge effort from each independent party. This is especially relevant to delivering the promise of the INSPIRE directive in Europe. Moreover, geospatial information systems benefit from Linked Data principles in building the next generation of spatial data applications e.g. federated smart buildings, self-piloted vehicles. Moreover, Linked Data has a life-cycle and data quality issues in Linked Open Data (LOD) are the result of a combination of data and process-related factors in this life-cycle. This dynamic process requires continuous improvement, in contrast to the static releases that typify most LOD datasets. In particular, geospatial data suffers from high demands on quality and if not met these can cause major problems in real life. Thus, it has a high importance to meet the dynamic quality needs by providing new continuous data quality tools and methodologies.

LinkedDataOps Project Members


Dr. Beyza Yaman

Dublin City University, Ireland

Asst. Prof. Dr. Rob Brennan

Dublin City University, Ireland