Category Theory in Ontology Research: Concrete Gain from an Abstract Approach
From International Center for Computational Logic
Category Theory in Ontology Research: Concrete Gain from an Abstract Approach
Markus KrötzschMarkus Krötzsch, Pascal HitzlerPascal Hitzler, Marc EhrigMarc Ehrig, York SureYork Sure
Markus Krötzsch, Pascal Hitzler, Marc Ehrig, York Sure
Category Theory in Ontology Research: Concrete Gain from an Abstract Approach
Technical Report, AIFB, Universität Karlsruhe, volume 893, March 2005
Category Theory in Ontology Research: Concrete Gain from an Abstract Approach
Technical Report, AIFB, Universität Karlsruhe, volume 893, March 2005
- KurzfassungAbstract
The focus of research on representing and reasoning with knowledge traditionally has been on single specifications and appropriate inference paradigms to draw conclusions from such data. Accordingly, this is also an essential aspect of ontology research which has received much attention in recent years. But ontologies introduce another new challenge based on the distributed nature of most of their applications, which requires to relate heterogeneous ontological specifications and to integrate information from multiple sources. These problems have of course been recognized, but many current approaches still lack the deep formal backgrounds on which todays reasoning paradigms are already founded. Here we propose category theory as a well-explored and very extensive mathematical foundation for modelling distributed knowledge. A particular prospect is to derive conclusions from the structure of those distributed knowledge bases, as it is for example needed when merging ontologies. - Projekt:Project: SEKT, KnowledgeWeb, SmartWeb
- Forschungsgruppe:Research Group: Wissensbasierte SystemeKnowledge-Based Systems
@techreport{KHES2005,
author = {Markus Kr{\"{o}}tzsch and Pascal Hitzler and Marc Ehrig and
York Sure},
title = {Category Theory in Ontology Research: Concrete Gain from an
Abstract Approach},
institution = {AIFB, Universit{\"{a}}t Karlsruhe},
year = {2005},
month = {March}
}