Session 2.4

Wednesday, September 16, 2015 - 14:30 to 16:00
D2 Works. 1
Axel Polleres


Making Sense of Description Logics

Description Logics are commonly used for the development of ontologies. Yet they are well-known to present difficulties of comprehension, e.g. when confronted with the justification for a particular entailment during the debugging process. This paper describes a study into the problems experienced in understanding and reasoning with Description Logics. In particular the study looked at: functionality in object properties; negation, disjunction and conjunction in Propositional Logic; negation and quantification; and the combination of two quantifiers. The difficulties experienced are related to theories of reasoning developed by cognitive psychologists, specifically the mental model and relational complexity theories. The study confirmed that problems are experienced with functional object properties and investigated the extent to which these difficulties can be explained by relational complexity theory. Mental model theory was used to explain performance with negation and quantifiers. This suggests that Boolean logic is easier to assimilate in Disjunctive Normal Form than in other forms and that particular difficulties arise when it is necessary to backtrack to form a mental model. On the other hand in certain cases syntactic clues seemed to contribute to reasoning strategies.

The Role of Reasoning for RDF Validation

For data practitioners embracing the world of RDF and Linked Data, the openness and flexibility is a mixed blessing. For them, data validation according to predefined constraints is a much sought-after feature, particularly as this is taken for granted in the XML world. Based on our work in the DCMI RDF Application Profiles Task Group and in cooperation with the W3C Data Shapes Working Group, we published by today 81 types of constraints that are required by various stakeholders for data applications. These constraint types form the basis to investigate the role that reasoning and different semantics play in practical data validation, why reasoning is beneficial for RDF validation, and how to overcome the major shortcomings when validating RDF data by performing reasoning prior to validation. For each constraint type, we examine (1) if reasoning may improve data quality, (2) how efficient in terms of runtime validation is performed with and without reasoning, and (3) if validation results depend on underlying semantics which differs between reasoning and validation. Using these findings, we determine for the most common constraint languages which constraint types they enable to express and give directions for the further development of constraint languages.

Accessing and Reasoning with Data from Disparate Data Sources Using Modular Ontologies and OBDA

This paper proposes a distributed framework for accessing, integrating and reasoning with data from heterogeneous, disparate data sources. The proposed solution combines the E-SHIQ modular ontology representation framework with the Ontop ontology-based data access (OBDA) technology. Distribution of knowledge allows the treatment of data from disparate sources in an autonomous manner, parallelization of operations, while it allows more efficient reasoning with the data.