Upper ontology

About: Upper ontology is a research topic. Over the lifetime, 9767 publications have been published within this topic receiving 220721 citations. The topic is also known as: top-level ontology & foundation ontology.

An analysis of collaborative patterns in large-scale ontology development projects

Abstract: Today, distributed teams collaboratively create and maintain more and more ontologies. To support this type of ontology development, software engineers are introducing a new generation of tools. However, we know relatively little about how existing large-scale collaborative ontology development works and what user workflows the tools must support. In this paper, we analyze our experience in supporting several such projects. We describe a visual and interactive project-management tool that we have developed, which helps ontology developers explore historical ontology change and discussion data. We present the results of qualitative and quantitative studies of the collaborative activity associated with three large-scale ontology-development projects. Based on the analysis, we conclude that domain and ontology experts have different patterns of ontology editing behavior, which has important implications for ontology-development tools.

TermGenie – a web-application for pattern-based ontology class generation

Abstract: Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes. TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 new classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes. TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

Fields of Sense: A New Realist Ontology

Abstract: Presents a new realist ontology based on the concept of fields of sense. Markus Gabriel presents us with an innovative answer to one of the central questions of philosophy: what is the meaning of 'being' - or, rather, 'existence' - and how does that concept relate to the totality of what there is? This ontology hinges on Gabriel's concept of fields of sense, which shows that he fundamentally opposes the idea that mathematics or the natural sciences could ever replace a richer philosophical understanding of what there is and how we know about it. The first contribution to a speculative epistemology on the basis of an ontology first method and develops a new realist ontology as well as outlining a realist epistemology grounded in ontology.

Formalizing the OPAL eBusiness ontology design patterns with OWL

Abstract: Domain ontology building is one of the most critical activities required in Semantic Web applications. The task must be performed by domain experts, who do not (generally) have the background of a knowledge engineer. To ease this task, Ontology Management Systems (such as Kaon, Protege, OntoEdit, Athos) are developing user friendly interfaces. However the problem is mainly of a cognitive nature. Difficulties comes from the fact that the existing ontology languages: (i) are hard to be used by unskilled people, (ii) have very basic constructs (e.g., class, property), (iii) are not domain specific, i.e., they are conceived for very diverse contexts (e.g., from medical sector to high energy physics). OPAL (Object, Process, Actor modelling Language) aims at supporting business experts who need to build an ontology by providing a limited number of high level conceptual templates.

A knowledge acquisition methodology to ontology construction for information retrieval from medical documents

Abstract: Vast amounts of medical information reside within text documents, so that the automatic retrieval of such information would certainly be beneficial for clinical activities. The need for overcoming the bottleneck provoked by the manual construction of ontologies has generated several studies and research on obtaining semi-automatic methods to build ontologies. Most techniques for learning domain ontologies from free text have important limitations. Thus, they can extract concepts so that only taxonomies are generally produced although there are other types of semantic relations relevant in knowledge modelling. This paper presents a language-independent approach for extracting knowledge from medical natural language documents. The knowledge is represented by means of ontologies that can have multiple semantic relationships among concepts.