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Abstract

Ontology is an interdisciplinary field that involves both the use of philosophical principles and the development of computational artifacts. As artifacts, ontologies can have diverse applications in knowledge management, information retrieval, and information systems, to mention a few. They have been largely applied to organize information in complex fields like Biomedicine. In this article, we present the OntoNeo Ontology, an initiative to build a formal ontology in the obstetrics and neonatal domain. OntoNeo is a resource that has been designed to serve as a comprehensive infrastructure providing scientific research and healthcare professionals with access to relevant information. The goal of OntoNeo is twofold: (a) to organize specialized medical knowledge, and (b) to provide a potential consensual representation of the medical information found in electronic health records and medical information systems. To describe our initiative, we first provide background information about distinct theories underlying ontology, top-level computational ontologies and their applications in Biomedicine. Then, we present the methodology employed in the development of OntoNeo and the results obtained to date. Finally, we discuss the applicability of OntoNeo by presenting a proof of concept that illustrates its potential usefulness in the realm of healthcare information systems.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.11, S.2529-2542

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Abstract

We discuss the needs of a knowledge organization scheme for supporting Web-based software applications. We show how it differs from traditional knowledge organization schemes due to the virtual, dynamic, ad-hoc, userspecific and application-specific nature of Web-based knowledge. The sheer size of Web resources also adds to the complexity of organizing knowledge on the Web. As such, a standard, global scheme such as a single ontology for classifying and organizing all Web-based content is unrealistic. There is nevertheless a strong and immediate need for effective knowledge organization schemes to improve the efficiency and effectiveness of Web-based applications. In this context, we propose a novel knowledge organization scheme wherein concepts in the ontology of a domain are semantically interlinked with specific pieces of Web-based content using a rich hyper-linking structure known as Superlinks with well-defined semantic roles. We illustrate how such a knowledge organization scheme improves the efficiency and effectiveness of a Web-based e-commerce retail store.

Source

Categories, contexts and relations in knowledge organization: Proceedings of the Twelfth International ISKO Conference 6-9 August 2012, Mysore, India. Eds.: Neelameghan, A. u. K.S. Raghavan

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Abstract

The ontology middleware discussed in this chapter can be seen as 'administrative' software infrastructure that makes the rest of the modules in a knowledge management toolset easier to integrate into real-world applications. The central issue is to make the methodology and modules available to society as a self-sufficient platform with mature support for development, management, maintenance, and use of middle-size and large knowledge bases. This chapter starts with an explanation of the required features of ontology middleware in the context of our knowledge management architecture and the terminology used In Section 11.2 the problem of versioning and tracking change is discussed. Section 11.3 presents the versioning model and its implementation that is developed in the project, and Section 11.4 describes the functionality of the instance reasoning module.

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Abstract

This article introduces the Simple Knowledge Organisation System (SKOS), a Semantic Web language for representing controlled structured vocabularies, including thesauri, classification schemes, subject heading systems and taxonomies. SKOS provides a framework for publishing thesauri, classification schemes, and subject indexes on the Web, and for applying these systems to resource collections that are part of the SemanticWeb. SemanticWeb applications may harvest and merge SKOS data, to integrate and enhances retrieval service across multiple collections (e.g. libraries). This article also describes some alternatives for integrating Semantic Web services based on the Resource Description Framework (RDF) and SKOS into a distributed enterprise architecture.

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Abstract

Classification schemes, such as the DMoZ web directory, provide a convenient and intuitive way for humans to access classified contents. While being easy to be dealt with for humans, classification schemes remain hard to be reasoned about by automated software agents. Among other things, this hardness is conditioned by the ambiguous na- ture of the natural language used to describe classification categories. In this paper we describe how classification schemes can be converted into OWL ontologies, thus enabling reasoning on them by Semantic Web applications. The proposed solution is based on a two phase approach in which category names are first encoded in a concept language and then, together with the structure of the classification scheme, are converted into an OWL ontology. We demonstrate the practical applicability of our approach by showing how the results of reasoning on these OWL ontologies can help improve the organization and use of web directories.

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Abstract

Domain ontologies facilitate the organization, sharing and reuse of domain knowledge, and enable various vertical domain applications to operate successfully. Most methods for automatically constructing ontologies focus on taxonomic relations, such as is-kind-of and is- part-of relations. However, much of the domain-specific semantics is ignored. This work proposes a semi-unsupervised approach for extracting semantic relations from domain-specific text documents. The approach effectively utilizes text mining and existing taxonomic relations in domain ontologies to discover candidate keywords that can represent semantic relations. A preliminary experiment on the natural science domain (Taiwan K9 education) indicates that the proposed method yields valuable recommendations. This work enriches domain ontologies by adding distilled semantics.

Source

Journal of Intelligent Information Systems

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Abstract

Smart applications behave intelligently because they understand at least partially the context where they operate. To do this, they need not only a formal domain model but also formal descriptions of the data they process and their own operational behaviour. Interoperability of smart applications is based on formalised definitions of all their data and processes. This paper studies the semantic interoperability of data in the case of eLearning and describes an experiment and its assessment. New content is imported into a knowledge-based learning environment without real updates of the original domain model, which is encoded as a knowledge base of conceptual graphs. A component called mediator enables the import by assigning dummy metadata annotations for the imported items. However, some functionality of the original system is lost, when processing the imported content, due to the lack of proper metadata annotation which cannot be associated fully automatically. So the paper presents an interoperability scenario when appropriate content items are viewed from the perspective of the original world and can be (partially) reused there.

Source

Conceptual structures: knowledge architectures for smart applications: 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield, UK, July 22 - 27, 2007 ; proceedings. Eds.: U. Priss u.a

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Abstract

Research in ontology has in recent years become widespread in the field of information systems, in distinct areas of sciences, in business, in economy, and in industry. The importance of ontologies is increasingly recognized in fields diverse as in e-commerce, semantic web, enterprise, information integration, qualitative modelling of physical systems, natural language processing, knowledge engineering, and databases. Ontologies provide formal specifications and harmonized definitions of concepts used to represent knowledge of specific domains. An ontology supplies a unifying framework for communication and establishes the basis of the knowledge about a specific domain. The term ontology has two meanings, it denotes, on the one hand, a research area, on the other hand, a system of organized knowledge. A system of knowledge may exhibit various degrees of formality; in the strongest sense it is an axiomatized and formally represented theory. which is denoted throughout this paper by the term axiomatized ontology. We use the term formal ontology to name an area of research which is becoming a science similar as formal or mathematical logic. Formal ontology is an evolving science which is concerned with the systematic development of axiomatic theories describing forms, modes, and views of being of the world at different levels of abstraction and granularity. Formal ontology combines the methods of mathematical logic with principles of philosophy, but also with the methods of artificial intelligence and linguistics. At themost general level of abstraction, formal ontology is concerned with those categories that apply to every area of the world. The application of formal ontology to domains at different levels of generality yields knowledge systems which are called, according to the level of abstraction, Top Level Ontologies or Foundational Ontologies, Core Domain or Domain Ontologies. Top level or foundational ontologies apply to every area of the world, in contrast to the various Generic, Domain Core or Domain Ontologies, which are associated to more restricted fields of interest. A foundational ontology can serve as a unifying framework for representation and integration of knowledge and may support the communication and harmonisation of conceptual systems. The current paper presents an overview about the current stage of the foundational ontology GFO.

Source

Theory and applications of ontology: vol.2: computer applications. Eds.: R. Poli et al

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Abstract

Knowledge Organization Systems denotes formally represented knowledge that is used within the context of Digital Libraries to improve data sharing and information retrieval. To increase their use, and to reuse them when possible, it is vital to manage them adequately and to provide them in a standard interchange format. Simple Knowledge Organization Systems (SKOS) seems to be the most promising representation for the type of knowledge models used in digital libraries, but there is a lack of tools that are able to properly manage it. This work presents a tool that fills this gap, facilitating their use in different environments and using SKOS as an interchange format.

Content

Vgl. Software-Download unter: http://thmanager.sourceforge.net/.

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Abstract

In recent years, knowledge structuring is assuming important roles in several real world applications such as decision support, cooperative problem solving, e-commerce, Semantic Web and, even in planning systems. Ontologies play an important role in supporting automated processes to access information and are at the core of new strategies for the development of knowledge-based systems. Yet, developing an ontology is a time-consuming task which often needs an accurate domain expertise to tackle structural and logical difficulties in the definition of concepts as well as conceivable relationships. This work presents an ontology-based retrieval approach, that supports data organization and visualization and provides a friendly navigation model. It exploits the fuzzy extension of the Formal Concept Analysis theory to elicit conceptualizations from datasets and generate a hierarchy-based representation of extracted knowledge. An intuitive graphical interface provides a multi-facets view of the built ontology. Through a transparent query-based retrieval, final users navigate across concepts, relations and population.

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Abstract

The Semantic Web has attracted much attention, both from academia and industry. An important role in research towards the Semantic Web is played by formalisms and technologies for handling uncertainty and/or vagueness. In this paper, I first provide some motivating examples for handling uncertainty and/or vagueness in the Semantic Web. I then give an overview of some own formalisms for handling uncertainty and/or vagueness in the Semantic Web.

Series

Lecture Notes in Computer Scienc;10370) (Information Systems and Applications, incl. Internet/Web, and HCI

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Abstract

Concept-based information retrieval and knowledge representation are in need of a theory of concepts and semantic relations. Guidelines for the construction and maintenance of knowledge organization systems (KOS) (such as ANSI/NISO Z39.19-2005 in the U.S.A. or DIN 2331:1980 in Germany) do not consider results of concept theory and theory of relations to the full extent. They are not able to unify the currently different worlds of traditional controlled vocabularies, of the social web (tagging and folksonomies) and of the semantic web (ontologies). Concept definitions as well as semantic relations are based on epistemological theories (empiricism, rationalism, hermeneutics, pragmatism, and critical theory). A concept is determined via its intension and extension as well as by definition. We will meet the problem of vagueness by introducing prototypes. Some important definitions are concept explanations (after Aristotle) and the definition of family resemblances (in the sense of Wittgenstein). We will model concepts as frames (according to Barsalou). The most important paradigmatic relation in KOS is hierarchy, which must be arranged into different classes: Hyponymy consists of taxonomy and simple hyponymy, meronymy consists of many different part-whole-relations. For practical application purposes, the transitivity of the given relation is very important. Unspecific associative relations are of little help to our focused applications and should be replaced by generalizable and domain-specific relations. We will discuss the reflexivity, symmetry, and transitivity of paradigmatic relations as well as the appearance of specific semantic relations in the different kinds of KOS (folksonomies, nomenclatures, classification systems, thesauri, and ontologies). Finally, we will pick out KOS as a central theme of the Semantic Web.

Source

Journal of the American Society for Information Science and Technology. 61(2010) no.10, S.1951-1969

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Abstract

Industries have adopted a standardized set of practices for developing their products. In the automotive domain, the provision of safety-compliant systems is guided by ISO 26262, a standard that specifies a set of requirements and recommendations for developing automotive safety-critical systems. For being in compliance with ISO 26262, the safety lifecycle proposed by the standard must be included in the development process of a vehicle. Besides, a safety case that shows that the system is acceptably safe has to be provided. The provision of a safety case implies the execution of a precise documentation process. This process makes sure that the work products are available and traceable. Further, the documentation management is defined in the standard as a mandatory activity and guidelines are proposed/imposed for its elaboration. It would be appropriate to point out that a well-documented safety lifecycle will provide the necessary inputs for the generation of an ISO 26262-compliant safety case. The OSLC (Open Services for Lifecycle Collaboration) standard and the maturing stack of semantic web technologies represent a promising integration platform for enabling semantic interoperability between the tools involved in the safety lifecycle. Tools for requirements, architecture, development management, among others, are expected to interact and shared data with the help of domains specifications created in OSLC. This thesis proposes the creation of an OSLC tool-chain infrastructure for sharing safety-related information, where fragments of safety information can be generated. The steps carried out during the elaboration of this master thesis consist in the identification, representation, and shaping of the RDF resources needed for the creation of a safety case. The focus of the thesis is limited to a tiny portion of the ISO 26262 left-hand side of the V-model, more exactly part 6 clause 8 of the standard: Software unit design and implementation. Regardless of the use of a restricted portion of the standard during the execution of this thesis, the findings can be extended to other parts, and the conclusions can be generalize. This master thesis is considered one of the first steps towards the provision of an OSLC-based and ISO 26262-compliant methodological approach for representing and shaping the work products resulting from the execution of the safety lifecycle, documentation required in the conformation of an ISO-compliant safety case.

Footnote

Thesis for: Master of Computer Science with Specialization in Software Engineering. Advisor: Barbara Gallina.

Imprint

Västeras : Mälardalen University, School of Innovation Design and Engineering

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Abstract

An ontology is a description (like a formal specification of a program) of concepts and relationships that can exist for an agent or a community of agents. The concept is important for the purpose of enabling knowledge sharing and reuse. The Handbook on Ontologies provides a comprehensive overview of the current status and future prospectives of the field of ontologies. The handbook demonstrates standards that have been created recently, it surveys methods that have been developed and it shows how to bring both into practice of ontology infrastructures and applications that are the best of their kind.

LCSH

Expert systems (Computer science)

Series

International handbook on information systems

Subject

Expert systems (Computer science)

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Abstract

The paper describes the OntoNotes, a multilingual (English, Chinese and Arabic) corpus with large-scale semantic annotations, including predicate-argument structure, word senses, ontology linking, and coreference. The underlying semantic model of OntoNotes involves word senses that are grouped into so-called sense pools, i.e., sets of near-synonymous senses of words. Such information is useful for many applications, including query expansion for information retrieval (IR) systems, (near-)duplicate detection for text summarization systems, and alternative word selection for writing support systems. Although a sense pool provides a set of near-synonymous senses of words, there is still no knowledge about whether two words in a pool are interchangeable in practical use. Therefore, this paper devises an unsupervised algorithm that incorporates Google n-grams and a statistical test to determine whether a word in a pool can be substituted by other words in the same pool. The n-gram features are used to measure the degree of context mismatch for a substitution. The statistical test is then applied to determine whether the substitution is adequate based on the degree of mismatch. The proposed method is compared with a supervised method, namely Linear Discriminant Analysis (LDA). Experimental results show that the proposed unsupervised method can achieve comparable performance with the supervised method.

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Abstract

The aim of this book is to highlight the relationship between knowledge representation and language in artificial intelligence, and in particular on the way in which the choice of representation influences the language used to discuss a problem - and vice versa. Opening with a discussion of knowledge representation methods, and following this with a look at reasoning methods, the author begins to make his case for the intimate relationship between language and representation. He shows how each representation method fits particularly well with some reasoning methods and less so with others, using specific languages as examples. The question of representation change, an important and complex issue about which very little is known, is addressed. Dr Hodgson gathers together recent work on problem solving, showing how, in some cases, it has been possible to use representation changes to recast problems into a language that makes them easier to solve. The author maintains throughout that the relationships that this book explores lie at the heart of the construction of large systems, examining a number of the current large AI systems from the viewpoint of representation and language to prove his point.

Classification

ST 285 Informatik / Monographien / Software und -entwicklung / Computer supported cooperative work (CSCW), Groupware

RVK

ST 285 Informatik / Monographien / Software und -entwicklung / Computer supported cooperative work (CSCW), Groupware

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Abstract

Linked Data provides access to huge, continuously growing amounts of open data and ontologies in RDF format that describe entities, links and properties on those entities. Equipping Linked Data with inference paves the way to make the Semantic Web a reality. In this survey, we describe a unifying framework for RDF ontologies and databases that we call deductive RDF triplestores. It consists in equipping RDF triplestores with Datalog inference rules. This rule language allows to capture in a uniform manner OWL constraints that are useful in practice, such as property transitivity or symmetry, but also domain-specific rules with practical relevance for users in many domains of interest. The expressivity and the genericity of this framework is illustrated for modeling Linked Data applications and for developing inference algorithms. In particular, we show how it allows to model the problem of data linkage in Linked Data as a reasoning problem on possibly decentralized data. We also explain how it makes possible to efficiently extract expressive modules from Semantic Web ontologies and databases with formal guarantees, whilst effectively controlling their succinctness. Experiments conducted on real-world datasets have demonstrated the feasibility of this approach and its usefulness in practice for data integration and information extraction.

Series

Lecture Notes in Computer Scienc;10370) (Information Systems and Applications, incl. Internet/Web, and HCI

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Abstract

This article comprises a literature review and conceptual analysis of Topic Maps-the ISO standard for representing information about the structure of information resources-according to the principles of Knowledge Organization (KO). Using the main principles from this discipline, the study shows how Topic Maps is proposed as an ontology model independent of technology. Topic Maps constitutes a 'bibliographic' meta-language able to represent, extend, and integrate almost all existing Knowledge Organization Systems (KOS) in a standards-based generic model applicable to digital content and to the Web. This report also presents an inventory of the current applications of Topic Maps in Libraries, Archives, and Museums (LAM), as well as in the Digital Humanities. Finally, some directions for further research are suggested, which relate Topic Maps to the main research trends in KO.

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Abstract

An increasing number of applications rely on RDF, OWL2, and SPARQL for storing and querying data. SPARQL, however, is not targeted towards end-users, and suitable query interfaces are needed. Faceted search is a prominent approach for end-user data access, and several RDF-based faceted search systems have been developed. There is, however, a lack of rigorous theoretical underpinning for faceted search in the context of RDF and OWL2. In this paper, we provide such solid foundations. We formalise faceted interfaces for this context, identify a fragment of first-order logic capturing the underlying queries, and study the complexity of answering such queries for RDF and OWL2 profiles. We then study interface generation and update, and devise efficiently implementable algorithms. Finally, we have implemented and tested our faceted search algorithms for scalability, with encouraging results.

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Abstract

Thanks to the recent Linked Data initiative, the foundations of the Semantic Web have been built. Shared, open and linked RDF datasets give us the possibility to exploit both the strong theoretical results and the robust technologies and tools developed since the seminal paper in the Semantic Web appeared in 2001. In a simplistic way, we may think at the Semantic Web as a ultra large distributed database we can query to get information coming from different sources. In fact, every dataset exposes a SPARQL endpoint to make the data accessible through exact queries. If we know the URI of the famous actress Nicole Kidman in DBpedia we may retrieve all the movies she acted with a simple SPARQL query. Eventually we may aggregate this information with users ratings and genres from IMDB. Even though these are very exciting results and applications, there is much more behind the curtains. Datasets come with the description of their schema structured in an ontological way. Resources refer to classes which are in turn organized in well structured and rich ontologies. Exploiting also this further feature we go beyond the notion of a distributed database and we can refer to the Semantic Web as a distributed knowledge base. If in our knowledge base we have that Paris is located in France (ontological level) and that Moulin Rouge! is set in Paris (data level) we may query the Semantic Web (interpreted as a set of interconnected datasets and related ontologies) to return all the movies starred by Nicole Kidman set in France and Moulin Rouge! will be in the final result set. The ontological level makes possible to infer new relations among data.
The Linked Data initiative and the state of the art in semantic technologies led off all brand new search and mash-up applications. The basic idea is to have smarter lookup services for a huge, distributed and social knowledge base. All these applications catch and (re)propose, under a semantic data perspective, the view of the classical Web as a distributed collection of documents to retrieve. The interlinked nature of the Web, and consequently of the Semantic Web, is exploited (just) to collect and aggregate data coming from different sources. Of course, this is a big step forward in search and Web technologies, but if we limit our investi- gation to retrieval tasks, we miss another important feature of the current Web: browsing and in particular exploratory browsing (a.k.a. exploratory search). Thanks to its hyperlinked nature, the Web defined a new way of browsing documents and knowledge: selection by lookup, navigation and trial-and-error tactics were, and still are, exploited by users to search for relevant information satisfying some initial requirements. The basic assumptions behind a lookup search, typical of Information Retrieval (IR) systems, are no more valid in an exploratory browsing context. An IR system, such as a search engine, assumes that: the user has a clear picture of what she is looking for ; she knows the terminology of the specific knowledge space. On the other side, as argued in, the main challenges in exploratory search can be summarized as: support querying and rapid query refinement; other facets and metadata-based result filtering; leverage search context; support learning and understanding; other visualization to support insight/decision making; facilitate collaboration. In Section 3 we will show two applications for exploratory search in the Semantic Web addressing some of the above challenges.