Using Insights from Psychology and Language to Improve How People Reason with Description Logics

Inspired by insights from theories of human reasoning and language, we propose additions to the Manchester OWL Syntax to improve comprehensibility. These additions cover: functional and inverse functional properties, negated conjunction, the definition of exceptions, and existential and universal restrictions. By means of an empirical study, we demonstrate the effectiveness of a number of these additions, in particular: the use of solely to clarify the uniqueness of the object in a functional property; the replacement of and with intersection in conjunction, which was particularly beneficial in negated conjunction; the use of except as a substitute for and not; and the replacement of some with including and only with noneOrOnly, which helped in certain situations to clarify the nature of these restrictions

Improving comprehension of Knowledge Representation languages: a case study with Description Logics

Knowledge representation languages are frequently difficult to understand, particularly for those not trained in formal logic. This is the case for Description Logics, which have been adopted for knowledge representation on the Web and in a number of application areas. This work looks at the difficulties experienced with Description Logics; and in particular with the widely-used Manchester OWL Syntax, which employs natural language keywords. The work comprises three studies. The first two identify a number of difficulties which users experience, e.g. with negated intersection, functional properties, the use of subproperties and restrictions. Insights from cognitive psychology and the study of language are applied to understand these difficulties. Whilst these difficulties are in part inherent in reasoning about logic, and Description Logics in particular, they are made worse by the syntax. In the third study, alternative syntactic constructs are proposed which demonstrate some improvement in accuracy and efficiency of comprehension. In addition to proposing alternative syntactic constructs, the work makes some suggestions regarding training and support systems for Description Logics

Human Reasoning and Description Logics: Applying Psychological Theory to Understand and Improve the Usability of Description Logics

Description Logics (DLs) are now the most commonly used ontology languages, in part because of the development of the Web Ontology Language (OWL) standards. Yet it is accepted that DLs are difficult to comprehend and work with, particularly for ontology users who are not computer scientists. The Manchester OWL Syntax (MOS) was developed to make DLs more accessible, by using English keywords in place of logic symbols or formal language. Nevertheless, DLs continue to present difficulties, even when represented in MOS. There has been some investigation of what features cause difficulties, specifically in the context of understanding how an entailment (i.e. an inference) follows from a justification (i.e. a minimal subset of the ontology that is sufficient for the entailment to hold), as is required when debugging an ontology. However, there has been little attempt to relate these difficulties to how people naturally reason and use language. This dissertation draws on theories of reasoning from cognitive psychology, and also insights from the philosophy of language, to understand the difficulties experienced with DLs and to make suggestions to mitigate those difficulties. The language features investigated were those known to be commonly used, both on the basis of analyses reported in the literature and after a survey of ontology users. Two experimental studies investigated participants’ ability to reason with DL statements. These studies demonstrate that insights from psychology and the philosophy of language can be used both to understand the difficulties experienced and to make proposals to mitigate those difficulties. The studies suggest that people reason using both the manipulation of syntax and the representation of semantics with mental models; both approaches can lead to errors. Particular difficulties were associated with: functional object properties; negated conjunction; the interaction of negation and the existential or universal restrictions; and nested restrictions. Proposals to mitigate these difficulties include the adoption of new language keywords; tool enhancement, e.g. to provide syntactically alternative expressions; and the introduction during training both of De Morgan’s Laws for conjunction and disjunction, and their analogues for existential and universal restrictions. A third study then investigated the effectiveness of the proposed new keywords; finding that these keywords could mitigate some of the difficulties experienced. Apart from the immediate applicability of these results to DLs, the approach taken in this dissertation could be extended widely to computer languages, including languages for interacting with databases and with Linked Data. Additionally, based on the experience of the three studies, the dissertation makes some methodological recommendations which are relevant to a range of human-computer interaction studies

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