How ontologies provide the semantics, as explained here with the help of Harry Potter and his owl Hedwig.

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Ontologies and the semantic web

This introduction presents the main motivations for the development of Description Logics (DLs) as a formalism for representing knowledge, as well as some important basic notions underlying all systems that have been created in the DL tradition. In addition, we provide the reader with an overview of the entire book and some guidelines for reading it.We first address the relationship between Description Logics and earlier semantic network and frame systems, which represent the original heritage of the field. We delve into some of the key problems encountered with the older efforts. Subsequently, we introduce the basic features of DL languages and related reasoning techniques.DL languages are then viewed as the core of knowledge representation systems. considering both the structure of a DL knowledge base and its associated reasoning services. The development of some implemented knowledge representation systems based on Description Logics and the first applications built with such systems are then reviewed.Finally, we address the relationship of Description Logics to other fields of Computer Science. We also discuss some extensions of the basic representation language machinery; these include features proposed for incorporation in the formalism that originally arose in implemented systems, and features proposed to cope with the needs of certain application domains.

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An Introduction to Description Logic

Description logics (DLs) and rules are formalisms that emphasize different aspects of knowledge representation: whereas DLs are focused on specifying and reasoning about conceptual knowledge, rules are focused on nonmonotonic inference. Many applications, however, require features of both DLs and rules. Developing a formalism that integrates DLs and rules would be a natural outcome of a large body of research in knowledge representation and reasoning of the last two decades; however, achieving this goal is very challenging and the approaches proposed thus far have not fully reached it. In this paper, we present a hybrid formalism of MKNFpknowledge bases, which integrates DLs and rules in a coherent semantic framework. Achieving seamless integration is nontrivial, since DLs use an open-world assumption, while the rules are based on a closed-world assumption. We overcome this discrepancy by basing the semantics of our formalism on the logic of minimal knowledge and negation as failure (MKNF) by Lifschitz. We present several algorithms for reasoning with MKNFp knowledge bases, each suitable to different kinds of rules, and establish tight complexity bounds.

https://www.cs.ox.ac.uk/people/boris.motik/pubs/mr10mknf-rules.pdf

Reconciling description logics and rules

Publisher Summary This chapter discusses description logics (DLs), which are a family of logic-based knowledge representation languages that can be used to represent the terminological knowledge of an application domain in a structured and formally well-structured way. It discusses their provenience and history and explains the way the field has developed. It describes the basic DL ALC in some detail, including definitions of syntax, semantics, and basic reasoning services, and discusses important extensions such as inverse roles, number restrictions, and concrete domains. It discusses (1) the relationship between DLs and other formalisms, in particular first order and modal logics, (2) the most commonly used reasoning techniques, in particular tableau, resolution, and automata based techniques, and (3) the computational complexity of basic reasoning problems. After reviewing some of the most prominent applications of DLs, in particular ontology language applications, the chapter discusses other aspects of DL research.

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Chapter 3 Description Logics

In the current literature of knowledge management and artificial intelligence, several different approaches to the problem have been carried out of developing domain ontologies from scratch. All these approaches deal fundamentally with three problems: (1) providing a collection of general terms describing classes and relations to be employed in the description of the domain itself; (2) organizing the terms into a taxonomy of the classes by the ISA relation; and (3) expressing in an explicit way the constraints that make the ISA pairs meaningful. Though a number of such approaches can be found, no systematic analysis of them exists which can be used to understand the inspiring motivation, the applicability context, and the structure of the approaches. In this paper, we provide a framework for analyzing the existing methodologies that compares them to a set of general criteria. In particular, we obtain a classification based upon the direction of ontology construction; bottom-up are those methodologies that start with some descriptions of the domain and obtain a classification, while top-down ones start with an abstract view of the domain itself, which is given a priori. The resulting classification is useful not only for theoretical purposes but also in the practice of deployment of ontologies in Information Systems, since it provides a framework for choosing the right methodology to be applied in the specific context, depending also on the needs of the application itself.

A Survey on Ontology Creation Methodologies

Existing classification schemes and thesauri are lacking in well-defined semantics and structural consistency. Empowering end users in searching collections of ever increasing magnitudes with performance far exceeding plain free-text searching (as used in many Web search engines), and developing systems that not only find but also process information for action, requires far more powerful and complex knowledge organization systems (KOSs). The paper presents a conceptual structure and transition procedure to support the shift from a traditional KOS towards a full-fledged and semantically rich KOS. The proposed structure also complies with other interoperability approaches like RDFS and XML in the Web environment. AGROVOC, a traditional thesaurus developed and maintained by the Food and Agriculture Organization (FAO) of the United Nations, serves as a case study for exploring the reengineering of a traditional thesaurus into a fully-fledged ontology. We start the process of developing an inventory of specific relationship types with well-defined semantics for the agricultural domain and explore the rules-as-you-go approach to streamlining the reengineering process.

Reengineering Thesauri for New Applications: the AGROVOC Example

This paper presents our ongoing work in establishing a multilingual domain ontology for a biosecurity portal. As a prototypical approach, this project is embedded into the bigger context of the Agricultural Ontology Service (AOS) project of the Food and Agriculture Organization (FAO) of the UN. The AOS will act as a reference tool for ontology creation assistance and herewith enable the transfer of the agricultural domain towards the Semantic Web. The paper focuses on introducing a comprehensive, reusable framework for the process of semi-automatically supported ontology evolvement, which aims to be used in follow-up projects and can eventually be applied to any other domain. Within the multinational context of the FAO, multilingual aspects play a crucial role and therefore an extendable layered ontology modelling approach will be described within the framework. The paper will present the project milestones achieved so far: the creation of a core ontology, the semiautomatic extension of this ontology using a heuristic toolset, and the representation of the resulting ontology in a multilingual web portal. The reader will be provided with a practical example for the creation of a specific domain ontology, which can be applied to any possible domain. Future projects, including automatic text classification, and ontology facilitated search opportunities, will be addressed at the end of the paper.

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A comprehensive framework for building multilingual domain ontologies: creating a prototype biosecurity ontology

Ontology creation and document indexing are well-known, critical bottlenecks for integrating semantic services and in general for bootstrapping the Semantic Web. For certain domains or communities, legacy terminologies and indexing methods exist which can be reused effectively. In the Fishery Ontology Project (FOS), we have reengineered and aligned legacy thesauri by using formal ontological methods, and we are deploying the resulting ontology library (currently including more than 35,000 classes and about 10,000 individuals) for services dedicated to fishery document repositories and databases. Alignment, reengineering, and modularization of the library leverage on the Core Ontology for Fishery developed in FOS. Its structure and use are described in this paper

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A core ontology of fishery and its use in the fishery ontology service project

This paper outlines a project (involving FAO, SIFAR, and CNR) aiming at building a formal ontology in the fishery domain. The ontology will support semantic interoperability among existing fishery information systems and will enhance information extraction and text marking, envisaging a fishery semantic web. The ontology is being built through the conceptual integration of existing fishery terminologies, thesauri, reference tables, and topic trees.

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Building An Integrated Formal Ontology for Semantic Interoperability in the Fishery Domain

"Knowledge management is vital for effective decision-making.....It is therefore essential to maintain and improve the coverage, quantity, utility, timeliness and accessibility of the information collected and disseminated." (citation from the Strategic Framework for FAO). FAO is a huge content provider for the World Wide Web. The FAO website has more than 6 gigabytes of information that contains knowledge created by more than 4000 FAO staff working in the world to combat hunger and to help people create a better life.

Frehiwot Fisseha

Papers

Reengineering Thesauri for New Applications: the AGROVOC Example

A comprehensive framework for building multilingual domain ontologies: creating a prototype biosecurity ontology

A core ontology of fishery and its use in the fishery ontology service project

Building An Integrated Formal Ontology for Semantic Interoperability in the Fishery Domain

Creating the Semantic Web: the Role of an Agricultural Ontology Server (AOS)