Data Quality—What Can an Ontological Analysis Contribute?
Andrew U. Frank
Department of Geoinformation Technical University Vienna Gusshausstrasse 27-29/E127-1 A-1040 Vienna, Austria
Abstract. Progress in research on data quality is slow and relevance of results for practice is low. Can an ontological analysis make significant contributions? The “road block” in data quality research seems to be an ontological one. Approaching “data quality” with an ordinary language philosophy method reveals the inherent contradiction in the concept. The ontological analysis reveals the necessity to separate the ontology (reality) proper from the epistemology (data). Data quality reveals itself when data is used, which focuses our attention on the double linkage between reality and data: (1) the observation that reflects reality into the data and (2) the decision that links the plan to the changes in reality. The analysis of the processes leading from raw observations to decisions leads to operational definitions for “fitness for use” and an effective method to assess the fitness of data for a decision. Novel is the consideration of data quality as transformation through the whole process from data collection to decision.
Keywords: ontology, fitness for use
In: Wan, Y. et al. (eds) Proceeding of the 8th international symposium on spatial accuracy assessment in natural resources and environmental sciences, World Academic Union (Press).