We review the use on ontologies for the integration of heterogeneous information sources. Based on an in-depth evaluation of existing approaches to this problem we discuss how ontologies are used to support the integration task. We evaluate and compare the languages used to represent the ontologies and the use of mappings between ontologies as well as to connect ontologies with information sources. We also enquire into ontology engineering methods and tools used to develop ontologies for information integration. Based on the results of our analysis we summarize the state-of-the-art in ontology-based information integration and name areas of further research activities.

Much of biology works by applying prior knowledge (`what is known') to an unknown entity, rather than the application of a set of axioms that will elicit knowledge. In addition, the complex biological data stored in bioinformatics databases often requires the addition of knowledge to specify and constrain the values held in that database. One way of capturing knowledge within bioinformatics applications and databases is the use of ontologies. An ontology is the concrete form of a conceptualisation of a community's knowledge of a domain. This paper aims to introduce the reader to the use of ontologies within bioinformatics. A description of the type of knowledge held in an ontology will be given. The paper will be illustrated throughout with examples taken from bioinformatics and molecular biology, and a survey of current biological ontologies will be presented. From this it will be seen that the use to which the ontology is put largely determines the content of the ontology. Finally, t...

Increasingly, effort has been devoted to surveying ontology-related research studies from various aspects. However, no survey is available for the ontology library system. For this reason, we decided to examine existing library systems in this paper. First, we identified the main criteria (management, adaptation, and standardization) for evaluating the functionality of the library systems. Then, based on the further enriched criteria, we surveyed most existing ontology library systems. Finally, we summarized the comparison and proposed various important requirements for structuring ontology library systems. The ontology library systems surveyed include: WebOnto, Ontolingua, DAML Ontology Library System, SHOE, Ontology Server, IEEE Standard Upper Ontology, OntoServer and ONIONS. 1.

Abstract: Skills management has been recently acknowledged as one of the key factors to adequately face the increasing competitiveness between knowledge intensive companies. In this paper we present a formal approach to Ontology-Based Semantic Matchmaking between Skills demand and supply, devised as a virtual marketplace of knowledge. In such a knowledge market metaphor, skills are a peculiar kind of good that has distinguishing characteristics with respect to traditional assets. Buyers are entities that need the skills of people, such as projects, departments and organizations; sellers are workers that offer their own skills. The formal framework supports the semantic match of descriptions provided by demanders and sellers of skills. In particular our approach, based on Description Logics formalization and reasoning, overcomes simple subsumption matching and allows match ranking and categorization. The implementation of the approach in a prototype system, which embeds a NeoClassic reasoner, is also described. 1

KRAFT is an agent architecture for the integration of heterogeneous information systems. The focus in KRAFT is on the integration of knowledge in the form of constraints. In this article we describe the architecture from an ontological perspective. We start by introducing the agent architecture and illustrate its application in the telecommunication-network design. We then describe how we assess the ontological heterogeneity in the domain, which problems the integration of constraint knowledge pose, and how we construct a shared ontology. Also, we describe the mapping functions that are used to translate information between the shared and the local ontologies. Finally, we look at the direction our research is taking hereafter.

High throughput glycoproteomics, similar to genomics and proteomics, involves extremely large volumes of distributed, heterogeneous data as a basis for identification and quantification of a structurally diverse collection of biomolecules. The ability to share, compare, query for and most critically correlate datasets using the native biological relationships are some of the challenges being faced by glycobiology researchers. As a solution for these challenges, we are building a semantic structure, using a suite of ontologies, which supports management of data and information at each step of the experimental lifecycle. This framework will enable researchers to leverage the large scale of glycoproteomics data to their benefit. In this paper, we focus on the design of these biological ontology schemas with an emphasis on relationships between biological concepts, on the use of novel approaches to populate these complex ontologies including integrating extremely large datasets (~500MB) as part of the instance base and on the evaluation of ontologies using OntoQA [38] metrics. The application of these ontologies in providing informatics solutions, for high throughput glycoproteomics experimental domain, is also discussed. We present our experience as a use case of developing two ontologies in one domain, to be part of a set of use cases, which are used in the development of an emergent framework for building and deploying biological ontologies.

Solving queries to support e-commerce transactions can involve retrieving and integrating information from multiple information resources. Often, users don't care which resources are used to answer their query. In such situations, the ideal solution would be to hide from the user the details of the resources involved in solving a particular query. An example would be providing seamless access to a set of heterogeneous electronic product catalogues. There are many problems that must be addressed before such a solution can be provided. In this paper, we discuss a number of these problems, indicate how we have addressed these and go on to describe the proof-of-concept demonstration system we have developed.

We present an ontology (named WaWO - Waste Water Ontology) applied to the domain of wastewater treatment processes. WaWO is built following the ideas of Uschold and Gruninger [14] [13] and is a hierarchically structured set of terms and a set of axioms for describing the real-world domain of wastewater treatment. WaWO is the manifestation of a shared understanding of the wastewater domain that is agreed among a number of agents: mainly, experts in environmental and chemical engineering. The WaWO ontology will be integrated into an existent environmental decision-support system (named DAI-DEPUR ). In the paper we describe the process of building the ontology, the intended uses of the ontology and what we want to obtain by its application.

Early ontological engineering methodologies have necessarily focussed on the managementof the whole ontology development process. There is a corresponding need to provide advice to the ontological engineer on the finer details of ontology construction. Here, we specifically address the representation of hierarchical relationships in an ontology. We identify five types of problem that may be encountered in moving from an informal description of a domain to a formal representation of hierarchical knowledge. Each problem type is discussed from the perspective of knowledge sharing and examples from biological ontologies are used to illustrate each type. Keywords: Ontological engineering; Hierarchical relationships; Knowledge sharing 1. Introduction It is largely accepted that one of the most important aspects of a domain ontology is the organisation of class definitions into inheritance hierarchies. Methodologies that describe processes for developing domain ontologies commonly include ...

According to Gruber’s definition an ontology [1] is “a formal specification of a conceptualization”. A conceptualisation being a simplified, abstract way of perceiving a segment of the world (a piece of reality), for which we agree to recognize the existence of a set of objects and their interrelations, as well as the terms we use to refer to them and their agreed meanings and properties.