1. 09/22/07Andrew Frank1 Data Quality Ontology: An Ontology for Imperfect Knowledge Andrew U. Frank Geoinformation TU Vienna frank@geoinfo.tuwien.ac.at www.geoinfo.tuwien.ac.at

2. 09/22/07Andrew Frank2 Ontologies describe (perfect) conceptualizations of a (perfect) world Our knowledge of the world is usually imperfect, incomplete, vague, uncertain and with errors. Can we build an ontology of imperfect knowledge?

3. 09/22/07 Motivation: I have heard (and probably said myself): “All human knowledge is imperfect.”

4. 09/22/07 Counterexample: A bill of $50 is exactly 50 Australian dollars, not 49.99 or 50 with an error (normally distributed) of 2 cents. The knowledge is accurate. I will show in this talk that the types of imperfections are related to ontological tier.

5. 09/22/07 Structure of this presentation 1. Tiers of ontology 2. Ontological Commitments for an ontology of imperfect knowledge 3. What can an ontology of imperfection be used for?

6. 09/22/07 Tiers of ontology: 0. Physical reality 1. Point property values 2. Object properties 3. Socially or subjectively constructed objects

7. 09/22/07 Ontologies are described through the ontological commitments they imply. Ontological commitments state the obvious. It is useful to write them down to investigate what they entail. Considering the negation of a commitment demonstrates often its validity.

8. 09/22/07 Commitments for a Geographic Ontology a single world the world exists in space and evolves in time actors can observe some states of the world actors can change states of the world Example of an entailment: Commitments (3) and (4) allow communication between agents.

9. 09/22/07 Commitments for a GIS information models reality information causation is different from physical causation

10. 09/22/07 Partial Knowledge: only part of the world is known not all states of the world are observable

11. 09/22/07 Limited Capacity of Biological Agents for Observation and Information Processing: concentration on discontinuity object boundary location is uncertain multiple ways to cut reality in objects objects formed with respect to interactions preferred objects endure in time object properties derived from observable states

12. 09/22/07 Mental Classification of Objects Classification reduces the information processing load. membership of an object in a class is based on object properties reasoning uses default values

13. 09/22/07 Social or Subjective Construction X counts as Y in context Z. (John Searle) ‏ Example: This piece of paper counts as 50 Australian dollars here (i.e., in the context of the Australian regulation for commerce) ‏

14. 09/22/07 Commitments for Constructions: all constructions are physically grounded in an object or an action (no “freestanding Y terms”). the context is a set of rules connecting to other constructions: - personal history - social conventions - legal, scientific rules

15. 09/22/07 What use is an Ontology of Imperfection? 1) process based definition of (top level) ontology 2) theory for imperfection in knowledge 3) definition of data quality terms (vague, precise, accurate,..) ‏

16. 09/22/07 Imperfections in the data must be linked to the ontology An ontology can be formally modeled through the processes which produce the knowledge. The conceptualization of the imperfections in the data must be linked to information processes in the ontology.

17. 09/22/07 Information processes between the ontological tiers: 0. Physical reality observations of phys. properties at points -> 1. Point property values object formation (granulation) and determination of object properties -> 2. Object with properties social construction -> 3. Socially or subjectively constructed objects

18. 09/22/07 Basic observations of physical properties This is the only source of knowledge about the physical reality of the world. Imperfect realizations as physical process (scale, random error).

19. 09/22/07 Physical object formation (Granulation) ‏ Objects as regions with uniform properties -> threshold -> boundary Object property as integration of some observable value over object region. Modeling of propagation of imperfections from observations is possible. Example: Where is the boundary of the mountain?

20. 09/22/07 Classification of objects by use: What use do the physical properties of the object permit? Typically a fuzzy classification! Example: Is region x a mountain?

21. 09/22/07 Imperfections of constructed facts: Is this $50 note a fake? Who makes authoritative decision? by what process? What are the physical properties determining the constructed fact? What is the context? (space and time dependent). Possible theories: - supervaluation - f-theories of Zadeh

22. 09/22/07 Information processes cause the imperfections in the data The processes which produce our knowledge about the world are responsible for the imperfections in our knowledge. All knowledge based on observation of the physical world is imperfect (but not knowledge about socially constructed facts!) ‏

23. 09/22/07 Conclusion: An ontology must explain how we construct knowledge from observing reality including the imperfections in the observations and other information processes used. Imperfections in the data are caused by imperfection in the information processes.

24. 09/22/07 Metaconclusion: Are the attempts to discuss ontology and data quality separately comparable to the attempts to capture geographic space and time separately in the 1990s?