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.

Ontology versioning in an ontology management framework

Abstract: Ontologies have become ubiquitous in information systems. They constitute the semantic Web's backbone, facilitate e-commerce, and serve such diverse application fields as bioinformatics and medicine. As ontology development becomes increasingly widespread and collaborative, developers are creating ontologies using different tools and different languages. These ontologies cover unrelated or overlapping domains at different levels of detail and granularity. A uniform framework, which we present here, helps users manage multiple ontologies by leveraging data and algorithms developed for one tool in another. For example, by using an algorithm we developed for structural evaluation of ontology versions, this framework lets developers compare different ontologies and map similarities and differences among them. Multiple-ontology management includes these tasks: maintain ontology libraries, import and reuse ontologies, translate ontologies from one formalism to another, support ontology versioning, specify transformation rules between different ontologies and version, merge ontologies, align and map between ontologies, extract an ontology's self-contained parts, support inference across multiple ontologies, support query across multiple ontologies.

Debugging and repair of owl ontologies

Abstract: With the advent of Semantic Web languages such as OWL (Web Ontology Language), the expressive Description Logic SHOIN is exposed to a wider audience of ontology users and developers. As an increasingly large number of OWL ontologies become available on the Semantic Web and the descriptions in the ontologies become more complicated, finding the cause of errors becomes an extremely hard task even for experts. The problem is worse for newcomers to OWL who have little or no experience with DL-based knowledge representation. Existing ontology development environments, in conjunction with a reasoner, provide some limited debugging support, however this is restricted to merely reporting errors in the ontology, whereas bug diagnosis and resolution is usually left to the user. In this thesis, I present a complete end-to-end framework for explaining, pinpointing and repairing semantic defects in OWL-DL ontologies (or in other words, SHOIN a knowledge base). Semantic defects are logical contradictions that manifest as either inconsistent ontologies or unsatisfiable concepts. Where possible, I show extensions to handle related defects such as unsatisfiable roles, unintended entailments and non-entailments, or defects in OWL ontologies that fall outside the DL scope (OWL-Full). The main contributions of the thesis include: (1) Definition of three novel OWL-DL debugging/repair services: Axiom Pinpointing, Root Error Pinpointing and Ontology Repair. This includes formalizing the notion of precise justifications for arbitrary OWL entailments (used to identify the cause of the error), root/derived unsatisfiable concepts (used to prune the error space) and semantic/syntactic relevance of axioms (used to rank erroneous axioms). (2) Design and Analysis of decision procedures (both glass-box or reasoner dependent, and black-box or reasoner independent) for implementing the services. (3) Performance and Usability evaluation of the services on realistic OWL-DL ontologies, which demonstrate its practical use and significance for OWL ontology modelers and users.

Towards Linguistically Grounded Ontologies

Abstract: In this paper we argue why it is necessary to associate linguistic information with ontologies and why more expressive models, beyond RDFS, OWL and SKOS, are needed to capture the relation between natural language constructs on the one hand and ontological entities on the other. We argue that in the light of tasks such as ontology-based information extraction, ontology learning and population from text and natural language generation from ontologies, currently available datamodels are not sufficient as they only allow to associate atomic terms without linguistic grounding or structure to ontology elements. Towards realizing a more expressive model for associating linguistic information to ontology elements, we base our work presented here on previously developed models (LingInfo, LexOnto, LMF ) and present a new joint model for linguistic grounding of ontologies called LexInfo . LexInfo combines essential design aspects of LingInfo and LexOnto and builds on a sound model for representing computational lexica called LMF which has been recently approved as a standard under ISO.

Modeling Computer Attacks: An Ontology for Intrusion Detection

Abstract: We state the benefits of transitioning from taxonomies to ontologies and ontology specification languages, which are able to simultaneously serve as recognition, reporting and correlation languages. We have produced an ontology specifying a model of computer attack using the DARPA Agent Markup Language+Ontology Inference Layer, a descriptive logic language. The ontology’s logic is implemented using DAMLJessKB. We compare and contrast the IETF’s IDMEF, an emerging standard that uses XML to define its data model, with a data model constructed using DAML+OIL. In our research we focus on low level kernel attributes at the process, system and network levels, to serve as those taxonomic characteristics. We illustrate the benefits of utilizing an ontology by presenting use case scenarios within a distributed intrusion detection system.

Managing multiple and distributed ontologies on the Semantic Web

Abstract: In traditional software systems, significant attention is devoted to keeping modules well separated and coherent with respect to functionality, thus ensuring that changes in the system are localized to a handful of modules. Reuse is seen as the key method in reaching that goal. Ontology-based systems on the Semantic Web are just a special class of software systems, so the same principles apply. In this article, we present an integrated framework for managing multiple and distributed ontologies on the Semant ic Web. It is based on the representation model for ontologies, trading off between expressivity and tractability. In our framework, we provide features for reusing existing ontologies and for evolving them while retaining the consistency. The approach is implemented within KAON, the Karlsruhe Ontology and Semantic Web tool suite.