The SFI ADAPT Centre and Tailtie Éireann, formerly Ordnance Survey Ireland (OSi), recently published new research into the creation of improved end-to-end data quality governance within Tailtie Éireann’s data production pipelines. The research marks a first in providing comprehensive formal mappings between semantic models of data quality dimensions defined by the four International Organizations for Standardization (ISO) and World Wide Web Consortium (W3C) data quality standards applied by a variety of tools and stakeholders. The work forms part of a multi-year collaboration between ADAPT and Tailtie Éireann and was published in the Semantic Web Journal, a leading publication for researchers looking to share information across agents and services on the future internet and elsewhere. Titled ‘LinkedDataOps:Quality Oriented End-to-end Geospatial Linked Data Production Governance’ this publication details the work ADAPT researchers and Tailtie Éireann staff took to create improved end-to-end data quality governance within Tailtie Éireann’s data production pipelines.
With advancements in technology, queries or decision support systems can benefit from the unification of high quality geospatial data. This is especially relevant for architectural, engineering and construction industries. The process of producing and transforming geospatial linked data is prone to errors and high demands are placed on data quality. Therefore effective data governance mechanisms are required for the management and tracking of data quality during data production processes. As the national mapping agency of Ireland, OSi provided the perfect use case for demonstrating data quality governance based on establishing a unified knowledge graph for data quality measurements across a complex, heterogeneous, quality-centric data production pipeline.
This publication was written by Dr. Beyza Yaman (ADAPT Centre/TCD), Dr Rob Brennan (ADAPT Centre/UCD), Kevin Thompson (OSi), and Fergus Fahey (OSi).
For more information about this research, you can access the full paper here.
