A Richer Notation for the Representation of Ontological Knowledge

Acta Cybernetica, 2007

We work on a method for giving a formal semantic representation of natural language texts. The semantic representation is generated in an ontology, on the basis of morphological and syntactic information. The task of the semantic analysis is to create instances in the ontology that contains the world model, i.e. to create those individuals and relations that correspond to the situation described by the text. The knowledge base of the semantic analyser is stored in an OWL ontology. This paper gives an overview of the system, and we discuss those questions of ontology design that require special attention in the context of meaning representation. We also present a software prototype that is based on the method and generates electronic medical records from free-form medical texts.

Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2018

Ontologies are a common and generally accepted instrument for the documentation of knowledge in a formalised machine readable form. This paper focuses on ontologies encoded in Web Ontology Language (OWL). OWL is description-logic based and can be extended by using Semantic Web Rule Language (SWRL) to express Horn clause like rules that allow the ontology to go beyond the scope of the more object-centric description logic propositions. The combination of OWL and SWRL has proved to be highly useful in practical applications. However, SWRL rules soon become complex and confusing in mere textual representations. This particular issue becomes obvious when ontologies grow in size and the number of rules increases. A solution for this problem can be an appropriate graphical representation of the rules. This paper proposes a graphical visualisation concept for SWRL rules that we call Aided OWL Notation (AOWLN). Additionally, we present a prototypical Protégé plugin that automatically visualises rules. 1 See http://protege-project.136.n4.nabble.com/ Visualisation-tool-for-OWL-and-SWRL-rules-td4667578.html-(accessed on 06/01/2018

We present Graphol, a novel language for the diagrammatic representation of ontologies. Graphol is designed to offer a completely visual representation to the users, thus helping the understanding of people not skilled in logic. At the same time, it provides designers with simple mechanisms for ontology editing, which free them from having to write down complex textual syntax. Through Graphol we can specify SROIQ(D) ontologies, thus our language essentially captures the OWL 2 standard. In this respect, we developed a basic software tool to translate Graphol ontologies realized with the yEd graph editor into OWL 2 functional syntax specifications.

2011

Cognitive assistance in knowledge engineering is a growing concern and information visualization is a very useful means to address this. This paper identifies some requirements for ontology visualization tools offering cognitive assistance and presents solutions with simple knowledge representations. This paper also identifies some of its features and describes areas need to be improved for effective visualization.

Proc. of WebNet, 2000

2016

This paper presents our work on development of OWL-driven systems for formal representation and reasoning about terminological knowledge and facts in petrology. The long-term aim of our project is to provide solid foundations for a large-scale integration of various kinds of knowledge, including basic terms, rock classification algorithms, findings and reports. We describe three steps we have taken towards that goal here. First, we develop a semi-automated procedure for transforming a database of igneous rock samples to texts in a controlled natural language (CNL), and then a collection of OWL ontologies. Second, we create an OWL ontology of important petrology terms currently described in natural language thesauri. We describe a prototype of a tool for collecting definitions from domain experts. Third, we present an approach to formalization of current industrial standards for classification of rock samples, which requires linear equations in OWL 2. In conclusion, we discuss a range of opportunities arising from the use of semantic technologies in petrology and outline the future work in this area.

Intuitive ontology visualization is a key for their learning, exchange, as well as their usage in conceptual modeling. OWLGrEd is a visual tool for compact graphical UML-style rendering and editing of OWL 2.0 ontologies. Here we introduce into OWLGrEd visualization annotations that allow defining custom visual presentations of ontology entities on the basis of annotations attached to these entities. The introduced mechanism of attaching visual annotations to annotation properties used in the ontology, besides being convenient for attaching graphical shape to user-defined annotations, appears to be powerful enough to cover visualization of e.g. UML stereotypes and other UML constructs that do not have direct counterpart in the "logic" part of OWL.

Databases and Information Systems, 2016

Ontologies are one of the core foundations of the Semantic Web. To participate in Semantic Web projects, domain experts need to be able to understand the ontologies involved. Visual notations can provide an overview of the ontology and help users to understand the connections among entities. However, the users first need to learn the visual notation before they can interpret it correctly. Controlled natural language representation would be readable right away and might be preferred in case of complex axioms, however, the structure of the ontology would remain less apparent. We propose to combine ontology visualizations with contextual ontology verbalizations of selected ontology (diagram) elements, displaying controlled natural language (CNL) explanations of OWL axioms corresponding to the selected visual notation elements. Thus, the domain experts will benefit from both the high-level overview provided by the graphical notation and the detailed textual explanations of particular elements in the diagram.

2000

In this article we discuss approaches of presenting formalized knowledge. We focus on knowledge represented by ontology. Ontologies are powerful for knowledge representation but are comprehensible for experts mostly, thus they need to be transformed to a human-understandable form. We discuss different alternatives such as trees, graphs or semantic web activities based on markup languages. We also describe our approach used within the scope of the Pellucid project. Our approach is based on OWL ontology, commercial standards and technologies such as XML, RDF, XSLT. The key idea is to transform knowledge in OWL to plain XML, which is then transformed to HTML by XSLT templates