Showing papers on "Ontology-based data integration published in 2006"

A survey on ontology mapping

Abstract: Ontology is increasingly seen as a key factor for enabling interoperability across heterogeneous systems and semantic web applications. Ontology mapping is required for combining distributed and heterogeneous ontologies. Developing such ontology mapping has been a core issue of recent ontology research. This paper presents ontology mapping categories, describes the characteristics of each category, compares these characteristics, and surveys tools, systems, and related work based on each category of ontology mapping. We believe this paper provides readers with a comprehensive understanding of ontology mapping and points to various research topics about the specific roles of ontology mapping.

Ontology Learning and Population from Text: Algorithms, Evaluation and Applications

Abstract: In the last decade, ontologies have received much attention within computer science and related disciplines, most often as the semantic web. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications discusses ontologies for the semantic web, as well as knowledge management, information retrieval, text clustering and classification, as well as natural language processing. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications is structured for research scientists and practitioners in industry. This book is also suitable for graduate-level students in computer science.

Bio-ontologies: current trends and future directions

Abstract: In recent years, as a knowledge-based discipline, bioinformatics has been made more computationally amenable. After its beginnings as a technology advocated by computer scientists to overcome problems of heterogeneity, ontology has been taken up by biologists themselves as a means to consistently annotate features from genotype to phenotype. In medical informatics, artifacts called ontologies have been used for a longer period of time to produce controlled lexicons for coding schemes. In this article, we review the current position in ontologies and how they have become institutionalized within biomedicine. As the field has matured, the much older philosophical aspects of ontology have come into play. With this and the institutionalization of ontology has come greater formality. We review this trend and what benefits it might bring to ontologies and their use within biomedicine.

Automatic fuzzy ontology generation for semantic Web

Abstract: Ontology is an effective conceptualism commonly used for the semantic Web. Fuzzy logic can be incorporated to ontology to represent uncertainty information. Typically, fuzzy ontology is generated from a predefined concept hierarchy. However, to construct a concept hierarchy for a certain domain can be a difficult and tedious task. To tackle this problem, this paper proposes the FOGA (fuzzy ontology generation framework) for automatic generation of fuzzy ontology on uncertainty information. The FOGA framework comprises the following components: fuzzy formal concept analysis, concept hierarchy generation, and fuzzy ontology generation. We also discuss approximating reasoning for incremental enrichment of the ontology with new upcoming data. Finally, a fuzzy-based technique for integrating other attributes of database to the ontology is proposed

Inducing Ontology from Flickr Tags

Abstract: paper, we describe some promising initial results in inducing ontology from the Flickr tag vocabulary, using a subsumption-based model. We describe the utility of faceted ontology as a supplement to a tagging system and present our model and results. We propose a revised, probabilistic model using seed ontologies to induce faceted ontology, and describe how the model can integrate into the logistics of tagging communities.

Modelling ontology evaluation and validation

Abstract: We present a comprehensive approach to ontology evaluation and validation, which have become a crucial problem for the development of semantic technologies. Existing evaluation methods are integrated into one sigle framework by means of a formal model. This model consists, firstly, of a meta-ontology called O2, that characterises ontologies as semiotic objects. Based on O2 and an analysis of existing methodologies, we identify three main types of measures for evaluation: structural measures, that are typical of ontologies represented as graphs; functional measures, that are related to the intended use of an ontology and of its components; and usability-profiling measures, that depend on the level of annotation of the considered ontology. The meta-ontology is then complemented with an ontology of ontology validation called oQual, which provides the means to devise the best set of criteria for choosing an ontology over others in the context of a given project. Finally, we provide a small example of how to apply oQual-derived criteria to a validation case.

MASON: A Proposal For An Ontology Of Manufacturing Domain

Abstract: This paper presents a proposal for a manufacturing upper ontology, aimed to draft a common semantic net in manufacturing domain. Usefulness of ontologies for data formalization and sharing, especially in a manufacturing environment, are first discussed. Details are given about the Web Ontology Language (OWL) and its adequation for ontologies in the manufacturing systems is shown. A concrete proposal named MASON (MAnufacturing’s Semantics ONtology) is presented and two applications of this ontology are exposed: automatic cost estimation and semantic-aware multiagent system for manufacturing.

Web ontology segmentation: analysis, classification and use

Abstract: Ontologies are at the heart of the semantic web. They define the concepts and relationships that make global interoperability possible. However, as these ontologies grow in size they become more and more difficult to create, use, understand, maintain, transform and classify. We present and evaluate several algorithms for extracting relevant segments out of large description logic ontologies for the purposes of increasing tractability for both humans and computers. The segments are not mere fragments, but stand alone as ontologies in their own right. This technique takes advantage of the detailed semantics captured within an OWL ontology to produce highly relevant segments. The research was evaluated using the GALEN ontology of medical terms and procedures.

Ontology Alignment: Bridging the Semantic Gap

Abstract: This book introduces novel methods and approaches for semantic integration. In addition to developing ground-breaking new methods for ontology alignment, the author provides extensive explanations of up-to-date case studies. It includes a thorough investigation of the foundations and provides pointers to future steps in ontology alignment with conclusion linking this work to the knowledge society.

OWL: Representing Information Using the Web Ontology Language

Abstract: Owl Representing Information Using The Web Ontology Language Pdf Book Download hosted by Zachary Baker on October 21 2018. It is a file download of Owl Representing Information Using The Web Ontology Language that you could be downloaded this with no cost on wa-cop.org. For your information, we do not host book downloadable Owl Representing Information Using The Web Ontology Language at wa-cop.org, this is only PDF generator result for the preview.

A framework for ontology evolution in collaborative environments

Abstract: With the wider use of ontologies in the Semantic Web and as part of production systems, multiple scenarios for ontology maintenance and evolution are emerging. For example, successive ontology versions can be posted on the (Semantic) Web, with users discovering the new versions serendipitously; ontology-development in a collaborative environment can be synchronous or asynchronous; managers of projects may exercise quality control, examining changes from previous baseline versions and accepting or rejecting them before a new baseline is published, and so on. In this paper, we present different scenarios for ontology maintenance and evolution that we have encountered in our own projects and in those of our collaborators. We define several features that categorize these scenarios. For each scenario, we discuss the high-level tasks that an editing environment must support. We then present a unified comprehensive set of tools to support different scenarios in a single framework, allowing users to switch between different modes easily.

Did I damage my ontology? A case for conservative extensions in description logic

Abstract: In computer science, ontologies are dynamic entities: to adapt them to new and evolving applications, it is necessary to frequently perform modifications such as the extension with new axioms and merging with other ontologies. We argue that, after performing such modifications, it is important to know whether the resulting ontology is a conservative extension of the original one. If this is not the case, then there may be unexpected consequences when using the modified ontology in place of the original one in applications. In this paper, we propose and investigate new reasoning problems based on the notion of conservative extension, assuming that ontologies are formulated as TBoxes in the description logic ALC. We show that the fundamental such reasoning problems are decidable and 2EXPTIME-complete. Additionally, we perform a finer-grained analysis that distinguishes between the size of the original ontology and the size of the additional axioms. In particular, we show that there are algorithms whose runtime is 'only' exponential in the size of the original ontology, but double exponential in the size of the added axioms. If the size of the new axioms is small compared to the size of the ontology, these algorithms are thus not significantly more complex than the standard reasoning services implemented in modern description logic reasoners. If the extension of an ontology is not conservative, our algorithm is capable of computing a concept that witnesses non-conservativeness. We show that the computed concepts are of (worst-case) minimal size.

An ontology of scientific experiments

Abstract: The formal description of experiments for efficient analysis, annotation and sharing of results is a fundamental part of the practice of science. Ontologies are required to achieve this objective. A few subject-specific ontologies of experiments currently exist. However, despite the unity of scientific experimentation, no general ontology of experiments exists. We propose the ontology EXPO to meet this need. EXPO links the SUMO (the Suggested Upper Merged Ontology) with subject-specific ontologies of experiments by formalizing the generic concepts of experimental design, methodology and results representation. EXPO is expressed in the W3C standard ontology language OWL-DL. We demonstrate the utility of EXPO and its ability to describe different experimental domains, by applying it to two experiments: one in high-energy physics and the other in phylogenetics. The use of EXPO made the goals and structure of these experiments more explicit, revealed ambiguities, and highlighted an unexpected similarity. We conclude that, EXPO is of general value in describing experiments and a step towards the formalization of science.

On how to perform a gold standard based evaluation of ontology learning

Abstract: In recent years several measures for the gold standard based evaluation of ontology learning were proposed. They can be distinguished by the layers of an ontology (e.g. lexical term layer and concept hierarchy) they evaluate. Judging those measures with a list of criteria we show that there exist some measures sufficient for evaluating the lexical term layer. However, existing measures for the evaluation of concept hierarchies fail to meet basic criteria. This paper presents a new taxonomic measure which overcomes the problems of current approaches.

Using Domain Ontology as Domain Knowledge for Requirements Elicitation

Abstract: Domain knowledge is one of crucial factors to get a great success in requirements elicitation of high quality, and only domain experts, not requirements analysts, have it. We propose a new requirements elicitation method ORE (Ontology based Requirements Elicitation), where a domain ontology can be used as domain knowledge. In our method, a domain ontology plays a role on semantic domain which gives meanings to requirements statements by using a semantic function. By using inference rules on the ontology and a quality metrics on the semantic function, an analyst can be navigated which requirements should be added for improving completeness of the current version of the requirements and/or which requirements should be deleted from the current version for keeping consistency. We define this process as a method and evaluate it by an experimental case study of software music players.

Human-centered ontology engineering: The HCOME methodology

Abstract: The fast emergent and continuously evolving areas of the Semantic Web and Knowledge Management make the incorporation of ontology engineering tasks in knowledge-empowered organizations and in the World Wide Web more than necessary. In such environments, the development and evolution of ontologies must be seen as a dynamic process that has to be supported through the entire ontology life cycle, resulting to living ontologies. The aim of this paper is to present the Human-Centered Ontology Engineering Methodology (HCOME) for the development and evaluation of living ontologies in the context of communities of knowledge workers. The methodology aims to empower knowledge workers to continuously manage their formal conceptualizations in their day-to-day activities and shape their information space by being actively involved in the ontology life cycle. The paper also demonstrates the Human Centered ONtology Engineering Environment, HCONE, which can effectively support this methodology.

Towards a reference ontology for business models

Abstract: Ontologies are viewed as increasingly important tools for structuring domains of interests. In this paper we propose a reference ontology of business models using concepts from three established business model ontologies; the REA, BMO, and e3-value. The basic concepts in the reference ontology concern actors, resources, and the transfer of resources between actors. Most of the concepts in the reference ontology are taken from one of the original ontologies, but we have also introduced a number of additional concepts, primarily related to resource transfers between business actors. The purpose of the proposed ontology is to increase the understanding of the original ontologies as well as the relationships between them, and also to seek opportunities to complement and improve on them.

Matching unstructured vocabularies using a background ontology

Abstract: Existing ontology matching algorithms use a combination of lexical and structural correspondence between source and target ontologies. We present a realistic case-study where both types of overlap are low: matching two unstructured lists of vocabulary used to describe patients at Intensive Care Units in two different hospitals. We show that indeed existing matchers fail on our data. We then discuss the use of background knowledge in ontology matching problems. In particular, we discuss the case where the source and the target ontology are of poor semantics, such as flat lists, and where the background knowledge is of rich semantics, providing extensive descriptions of the properties of the concepts involved. We evaluate our results against a Gold Standard set of matches that we obtained from human experts.

PR-OWL: A Framework for Probabilistic Ontologies

Abstract: Across a wide range of domains, there is an urgent need for a well-founded approach to incorporating uncertain and incomplete knowledge into formal domain ontologies. Although this subject is receiving increasing attention from ontology researchers, there is as yet no broad consensus on the definition of a probabilistic ontology and on the most suitable approach to extending current ontology languages to support uncertainty. This paper presents two contributions to developing a coherent framework for probabilistic ontologies: (1) a formal definition of a probabilistic ontology, and (2) an extension of the OWL Web Ontology Language that is consistent with our formal definition. This extension, PR-OWL, is based on Multi-Entity Bayesian Networks (MEBN), a first-order Bayesian logic that unifies Bayesian probability with First-Order Logic. As such, PR-OWL combines the full representation power of OWL with the flexibility and inferential power of Bayesian logic.

General Formal Ontology (GFO) - A Foundational Ontology Integrating Objects and Processes [Version 1.0]

Abstract: This report is a living document of the Research Group Ontologies in Medicine (Onto-Med) which represents work in progress towards a proposal for an integrated system of foundational ontologies. It will be applied to several fields of medicine, biomedicine, and biology, and a number of applications are carried out in collaboration with the Center for Clinical Trials at the University of Leipzig, with the MaxPlanck-Institute for Evolutionary Anthropology, and with the ICCAS at the University of Leipzig. The General Formal Ontology (GFO) is a component of the Integrated System of Foundational Ontologies (ISFO), and ISFO is a part of the Integrated Framework for the Development and Application of Ontologies (IFDAO). The predecessor of IFDAO was the GOL project which was launched in 1999 as a collaborative research effort of the Institute of Medical Informatics, Statistics and Epidemiology (IMISE) and the Institute of Informatics (IfI) at the University of Leipzig.

Modularity and web ontologies

Abstract: Modularity in ontologies is key both for large scale ontology development and for distributed ontology reuse on the Web. However, the problems of formally characterizing a modular representation, on the one hand, and of automatically identifying modules within an OWL ontology, on the other, has not been satisfactorily addressed, although their relevance has been widely accepted by the Ontology Engineering and Semantic Web communities. In this paper, we provide a notion of modularity grounded on the semantics of OWL-DL. We present an algorithm for automatically identifying and extracting modules from OWL-DL ontologies, an implementation and some promising empirical results on real-world ontologies.

X-Similarity: Computing Semantic Similarity between Concepts from Different Ontologies

Abstract: Semantic Similarity relates to computing the similarity between concepts (terms) which are not necessarily lexically similar. We investigate approaches for computing semantic similarity by mapping terms to an ontology and by examining their relationships in that ontology. More specifically, we investigate approaches to computing the semantic similarity between natural language terms (using WordNet as the underlying reference ontology) and between medical terms (using the MeSH ontology of medical and biomedical terms). The most popular semantic similarity methods are implemented and evaluated using WordNet and MeSH. The focus of this work is also on cross ontology methods which are capable of computing the semantic similarity between terms stemming from different ontologies (WordNet and MeSH in this work). This is a far more difficult problem (than the single ontology one referred to above) which has not been investigated adequately in the literature. X-Similarity, a novel cross-ontology similarity method is also a contribution of this work. All methods examined in this work are integrated into a semantic similarity system which is accessible on the Web.

Geospatial Ontology Development and Semantic Analytics

Abstract: Geospatial ontology development and semantic knowledge discovery addresses the need for modeling, analyzing and visualizing multimodal information, and is unique in offering integrated analytics that encompasses spatial, temporal and thematic dimensions of information and knowledge. The comprehensive ability to provide integrated analysis from multiple forms of information and use of explicit knowledge make this approach unique. This also involves specification of spatiotemporal thematic ontologies and populating such ontologies with high quality knowledge. Such ontologies form the basis for defining the meaning of important relations terms, such as near or surrounded by, and enable computation of spatiotemporal thematic proximity measures we define. SWETO (Semantic Web Technology Evaluation Ontology) and geospatial extension SWETO-GS are examples of these ontologies. The Geospatial Semantics Analytics (GSA) framework incorporates: (1) the ability to automatically and semi-automatically tract metadata from syntactically (including unstructured, semi-structured and structured data) and semantically heterogeneous and multimodal data from diverse sources; and (2) analytical processing that exploits these ontologies and associated knowledge bases, with integral support for what we term spatiotemporal thematic proximity (STTP) reasoning and interactive visualization capabilities. This paper discusses the results of our geospatial ontology development efforts as well as some new semantic analytics methods on this ontology such as STTP.

Products and Services Ontologies: A Methodology for Deriving OWL Ontologies from Industrial Categorization Standards

Abstract: Using Semantic Web technologies for e-business tasks, like product search or content integration, requires ontologies for products and services. Their manual creation is problematic due to (1) the high specificity, resulting in a large number of concepts, and (2) the need for timely ontology maintenance due to product innovation; and due to cost, since building such ontologies from scratch requires significant resources. At the same time, industrial categorization standards, like UNSPSC, eCl@ss, eOTD, or the RosettaNet Technical Dictionary, reflect some degree of consensus and contain a wealth of concept definitions plus a hierarchy. They can thus be valuable input for creating domain ontologies. However, the transformation of existing standards, originally developed for some purpose other than ontology engineering, into useful ontologies is not as straightforward as it appears. In this paper, (1) we argue that deriving products and services ontologies from industrial taxonomies is more feasible than manual ontology engineering; (2) show that the representation of the original semantics of the input standard, especially the taxonomic relationship, is an important modeling decision that determines the usefulness of the resulting ontology; (3) illustrate the problem by analyzing existing ontologies derived from UNSPCS and eCl@ss; (4) present a methodology for creating ontologies in OWL based on the reuse of existing standards; and (5) demonstrate this approach by transforming eCl@ss 5.1 into a practically useful products and services ontology.