1.
Bridging perceived and actual data quality : automating the framework for governance reliabilityTomaž Podobnikar, 2025, izvirni znanstveni članek
Opis: The discrepancy between perceived and actual data quality, shaped by stakeholders’ interpretations of technical specifications, poses significant challenges in governance, impacting decision-making and stakeholder trust. To address this, we introduce an automated data quality management (DQM) framework, implemented through the NRPvalid toolkit, as a standalone solution incorporating over 100 assessment tools. This framework strengthens data quality evaluation and stakeholder collaboration by systematically bridging subjective perceptions with objective quality metrics. Unlike traditional producer–user models, it accounts for complex, multi-stakeholder interactions to improve data governance. Applied to planned land use (PLU) data, the framework significantly reduces discrepancy, as quantified by error score metrics, and directly enhances building permit issuance by streamlining interactions among administrative units, municipalities, and investors. By evaluating, refining, and seamlessly integrating spatial data into the enterprise spatial information system, this scalable, automated solution supports constant data quality improvement. The DQM and its toolkit have been widely adopted, promoting transparent, reliable, and efficient geospatial data governance.
Ključne besede: perceived and actual data quality, data quality management, DQM, quality assurance/quality control, QA/QC, spatial data quality, data quality standards, data governance, planned land use, automation, uncertainty management, geospatial
Objavljeno v ReVIS: 14.04.2025; Ogledov: 65; Prenosov: 0
Celotno besedilo (9,08 MB)
