Talks and Poster Presentations (with Proceedings-Entry):
"Data Quality Ontology: An Ontology for Imperfect Knowledge";
Talk: COSIT 2007,
- 2007-09-23; in: "Spatial Information Theory 8th International Conference, COSIT 2007",
S. Winter, M. Duckham, L. Kulik, B. Kuipers (ed.);
Data quality and ontology are two of the dominating research topics in GIS, influencing many others. Research so far investigated them in isolation. Ontology is concerned with perfect knowledge of the world and ignores so far imperfections in our knowledge. An ontology for imperfect knowledge leads to a consistent classification of imperfections of data (i.e., data quality), and a formalizable description of the influence of data quality on decisions. If we want to deal with data quality with ontological methods, then reality and the information model stored in the GIS must be represented in the same model. This allows to use closed loops sematics to define "fitness for use" as leading to correct, executable decisions. The approach covers knowledge of physical reality as well as personal (subjective) and social constructions. It lists systematically influences leading to imperfections in data in logical succession.
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.