Search (133 results, page 1 of 7)

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Abstract

In der vorliegenden Arbeit soll einen Ansatz zur Implementation einer Wissensrepräsentation mit den in Abschnitt 1.1. skizzierten Eigenschaften und dem Semantic Web als Anwendungsbereich vorgestellt werden. Die Arbeit ist im Wesentlichen in zwei Bereiche gegliedert: dem Untersuchungsbereich (Kapitel 2-5), in dem ich die in Abschnitt 1.1. eingeführte Terminologie definiert und ein umfassender Überblick über die zugrundeliegenden Konzepte gegeben werden soll, und dem Implementationsbereich (Kapitel 6), in dem aufbauend auf dem im Untersuchungsbereich erarbeiteten Wissen einen semantischen Suchdienst entwickeln werden soll. In Kapitel 2 soll zunächst das Konzept der semantischen Interpretation erläutert und in diesem Kontext hauptsächlich zwischen Daten, Information und Wissen unterschieden werden. In Kapitel 3 soll Wissensrepräsentation aus einer kognitiven Perspektive betrachtet und in diesem Zusammenhang das Konzept der Unschärfe beschrieben werden. In Kapitel 4 sollen sowohl aus historischer als auch aktueller Sicht die Ansätze zur Wissensrepräsentation und -auffindung beschrieben und in diesem Zusammenhang das Konzept der Unschärfe diskutiert werden. In Kapitel 5 sollen die aktuell im WWW eingesetzten Modelle und deren Einschränkungen erläutert werden. Anschließend sollen im Kontext der Entscheidungsfindung die Anforderungen beschrieben werden, die das WWW an eine adäquate Wissensrepräsentation stellt, und anhand der Technologien des Semantic Web die Repräsentationsparadigmen erläutert werden, die diese Anforderungen erfüllen. Schließlich soll das Topic Map-Paradigma erläutert werden. In Kapitel 6 soll aufbauend auf die im Untersuchtungsbereich gewonnenen Erkenntnisse ein Prototyp entwickelt werden. Dieser besteht im Wesentlichen aus Softwarewerkzeugen, die das automatisierte und computergestützte Extrahieren von Informationen, das unscharfe Modellieren, sowie das Auffinden von Wissen unterstützen. Die Implementation der Werkzeuge erfolgt in der Programmiersprache Java, und zur unscharfen Wissensrepräsentation werden Topic Maps eingesetzt. Die Implementation wird dabei schrittweise vorgestellt. Schließlich soll der Prototyp evaluiert und ein Ausblick auf zukünftige Erweiterungsmöglichkeiten gegeben werden. Und schließlich soll in Kapitel 7 eine Synthese formuliert werden.

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Content

"Swoogle, the Semantic web search engine, is a research project carried out by the ebiquity research group in the Computer Science and Electrical Engineering Department at the University of Maryland. It's an engine tailored towards finding documents on the semantic web. The whole research paper is available here. Semantic web is touted as the next generation of online content representation where the web documents are represented in a language that is not only easy for humans but is machine readable (easing the integration of data as never thought possible) as well. And the main elements of the semantic web include data model description formats such as Resource Description Framework (RDF), a variety of data interchange formats (e.g. RDF/XML, Turtle, N-Triples), and notations such as RDF Schema (RDFS), the Web Ontology Language (OWL), all of which are intended to provide a formal description of concepts, terms, and relationships within a given knowledge domain (Wikipedia). And Swoogle is an attempt to mine and index this new set of web documents. The engine performs crawling of semantic documents like most web search engines and the search is available as web service too. The engine is primarily written in Java with the PHP used for the front-end and MySQL for database. Swoogle is capable of searching over 10,000 ontologies and indexes more that 1.3 million web documents. It also computes the importance of a Semantic Web document. The techniques used for indexing are the more google-type page ranking and also mining the documents for inter-relationships that are the basis for the semantic web. For more information on how the RDF framework can be used to relate documents, read the link here. Being a research project, and with a non-commercial motive, there is not much hype around Swoogle. However, the approach to indexing of Semantic web documents is an approach that most engines will have to take at some point of time. When the Internet debuted, there were no specific engines available for indexing or searching. The Search domain only picked up as more and more content became available. One fundamental question that I've always wondered about it is - provided that the search engines return very relevant results for a query - how to ascertain that the documents are indeed the most relevant ones available. There is always an inherent delay in indexing of document. Its here that the new semantic documents search engines can close delay. Experimenting with the concept of Search in the semantic web can only bore well for the future of search technology."

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Abstract

In the area of digital library services, the access to subject-specific metadata of scholarly publications is of utmost interest. One of the most prevalent approaches for metadata exchange is the XML-based Open Archive Initiative (OAI) Protocol for Metadata Harvesting (OAI-PMH). However, due to its loose requirements regarding metadata content there is no strict standard for consistent subject indexing specified, which is furthermore needed in the digital library domain. This contribution addresses the problem of automatic enhancement of OAI metadata by means of the most widely used universal classification schemes in libraries-the Dewey Decimal Classification (DDC). To be more specific, we automatically classify scientific documents according to the DDC taxonomy within three levels using a machine learning-based classifier that relies solely on OAI metadata records as the document representation. The results show an asymmetric distribution of documents across the hierarchical structure of the DDC taxonomy and issues of data sparseness. However, the performance of the classifier shows promising results on all three levels of the DDC.

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Abstract

With the advance of the semantic Web, increasing amounts of data are available in a structured and machine-understandable form. This opens opportunities for users to employ semantic queries instead of simple keyword-based ones to accurately express the information need. However, constructing semantic queries is a demanding task for human users [11]. To compose a valid semantic query, a user has to (1) master a query language (e.g., SPARQL) and (2) acquire sufficient knowledge about the ontology or the schema of the data source. While there are systems which support this task with visual tools [21, 26] or natural language interfaces [3, 13, 14, 18], the process of query construction can still be complex and time consuming. According to [24], users prefer keyword search, and struggle with the construction of semantic queries although being supported with a natural language interface. Several keyword search approaches have already been proposed to ease information seeking on semantic data [16, 32, 35] or databases [1, 31]. However, keyword queries lack the expressivity to precisely describe the user's intent. As a result, ranking can at best put query intentions of the majority on top, making it impossible to take the intentions of all users into consideration.

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Abstract

Library catalogues contain an enormous amount of structured, high-quality data, however, this data is generally not made available to semantic web applications. In this paper we describe the tools and techniques used to make the Swedish Union Catalogue (LIBRIS) part of the Semantic Web and Linked Data. The focus is on links to and between resources and the mechanisms used to make data available, rather than perfect description of the individual resources. We also present a method of creating links between records of the same work.

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Abstract

Given that semantic Web realization is based on the critical mass of metadata accessibility and the representation of data with formal knowledge, it needs to generate metadata that is specific, easy to understand and well-defined. However, semantic annotation of the web documents is the successful way to make the Semantic Web vision a reality. This paper introduces the Semantic Web and its vision (stack layers) with regard to some concept definitions that helps the understanding of semantic annotation. Additionally, this paper introduces the semantic annotation categories, tools, domains and models.

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Abstract

XML will have a profound impact on the way data is exchanged on the Internet. An important feature of this language is the separation of content from presentation, which makes it easier to select and/or reformat the data. However, due to the likelihood of numerous industry and domain specific DTDs, those who wish to integrate information will still be faced with the problem of semantic interoperability. In this paper we discuss why this problem is not solved by XML, and then discuss why the Resource Description Framework is only a partial solution. We then present the SHOE language, which we feel has many of the features necessary to enable a semantic web, and describe an existing set of tools that make it easy to use the language.

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Abstract

Der Artikel führt in semantische Technologien ein und gewährt Einblick in unterschiedliche Entwicklungsrichtungen. Insbesondere werden Business Semantics vorgestellt und vom Semantic Web abgegrenzt. Die Stärken von Business Semantics werden speziell an den Praxisbeispielen des Knowledge Portals und dem Projekt "Knowledge Base" der Wienerberger AG veranschaulicht. So werden die Anforderungen - was brauchen Anwendungen in Unternehmen heute - und die Leistungsfähigkeit von Systemen - was bieten Business Semantics - konkretisiert und gegenübergestellt.

Source

Information - Wissenschaft und Praxis. 57(2006) H.6/7, S.359-366

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Abstract

The Web of Data keeps growing rapidly. However, the full exploitation of this large amount of structured data faces numerous challenges like usability, scalability, imprecise information needs and data change. We present Semplore, an IR-based system that aims at addressing these issues. Semplore supports intuitive faceted search and complex queries both on text and structured data. It combines imprecise keyword search and precise structured query in a unified ranking scheme. Scalable query processing is supported by leveraging inverted indexes traditionally used in IR systems. This is combined with a novel block-based index structure to support efficient index update when data changes. The experimental results show that Semplore is an efficient and effective system for searching the Web of Data and can be used as a basic infrastructure for Web-scale Semantic Web search engines.

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Abstract

This paper poses three questions regarding the planned development of the Simple Knowledge Organisation System (SKOS) towards W3C Recommendation status. Firstly, what is the fundamental purpose and therefore scope of SKOS? Secondly, which key software components depend on SKOS, and how do they interact? Thirdly, what is the wider technological and social context in which SKOS is likely to be applied and how might this influence design goals? Some tentative conclusions are drawn and in particular it is suggested that the scope of SKOS be restricted to the formal representation of controlled structured vocabularies intended for use within retrieval applications. However, the main purpose of this paper is to articulate the assumptions that have motivated the design of SKOS, so that these may be reviewed prior to a rigorous standardization initiative.

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Abstract

Wikis are established means for the collaborative authoring, versioning and publishing of textual articles. The Wikipedia project, for example, succeeded in creating the by far largest encyclopedia just on the basis of a wiki. Recently, several approaches have been proposed on how to extend wikis to allow the creation of structured and semantically enriched content. However, the means for creating semantically enriched structured content are already available and are, although unconsciously, even used by Wikipedia authors. In this article, we present a method for revealing this structured content by extracting information from template instances. We suggest ways to efficiently query the vast amount of extracted information (e.g. more than 8 million RDF statements for the English Wikipedia version alone), leading to astonishing query answering possibilities (such as for the title question). We analyze the quality of the extracted content, and propose strategies for quality improvements with just minor modifications of the wiki systems being currently used.

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Abstract

Metadata applications have evolved in time into highly structured "islands of information" about digital resources, often bearing a strong semantic interpretation. Scarcely however are these semantics being communicated in machine readable and understandable ways. At the same time, the process for transforming the implied metadata knowledge into explicit Semantic Web descriptions can be problematic and is not always evident. In this article we take upon the well-established Dublin Core metadata standard as well as other metadata schemata, which often appear in digital repositories set-ups, and suggest a proper Semantic Web OWL ontology. In this process the authors cope with discrepancies and incompatibilities, indicative of such attempts, in novel ways. Moreover, we show the potential and necessity of this approach by demonstrating inferences on the resulting ontology, instantiated with actual metadata records. The authors conclude by presenting a working prototype that provides for inference-based querying on top of digital repositories.

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Abstract

How do we test Semantic Web tools? How can we know that they perform better than current technologies for knowledge management? What does 'better' precisely mean? How can we operationalize and measure this? Some of these questions may be partially answered by simulations in lab experiments that for example look at the speed or scalability of algorithms. However, it is not clear in advance to what extent such laboratory results carry over to the real world. Quality is in the eye of the beholder, and so the quality of Semantic Web methods will very much depend on the perception of their usefulness as seen by tool users. This can only be tested by carefully designed field experiments. In this chapter, we discuss the design considerations and set-up of field experiments with Semantic Web tools, and illustrate these with case examples from a virtual organization in industrial research.

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Abstract

Semantic similarity is vital to many areas, such as information retrieval. Various methods have been proposed with a focus on comparing unstructured text documents. Several of these have been enhanced with ontology; however, they have not been applied to ontology instances. With the growth in ontology instance data published online through, for example, Linked Open Data, there is an increasing need to apply semantic similarity to ontology instances. Drawing on ontology-supported polarity mining (OSPM), we propose an algorithm that enhances the computation of semantic similarity with polarity mining techniques. The algorithm is evaluated with online customer review data. The experimental results show that the proposed algorithm outperforms the baseline algorithm in multiple settings.

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Abstract

The concept of Linked Data has made its entrance in the cultural heritage sector due to its potential use for the integration of heterogeneous collections and deriving additional value out of existing metadata. However, practitioners and researchers alike need a better understanding of what outcome they can reasonably expect of the reconciliation process between their local metadata and established controlled vocabularies which are already a part of the Linked Data cloud. This paper offers an in-depth analysis of how a locally developed vocabulary can be successfully reconciled with the Library of Congress Subject Headings (LCSH) and the Arts and Architecture Thesaurus (AAT) through the help of a general-purpose tool for interactive data transformation (OpenRefine). Issues negatively affecting the reconciliation process are identified and solutions are proposed in order to derive maximum value from existing metadata and controlled vocabularies in an automated manner.

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Abstract

Die schnelle Entwicklung der Internet- und Web-Technologie verändert den Stand der Technik in der Kommunikation von Wissen oder Forschungsergebnissen. Insbesondere werden semantische Technologien, verknüpfte und offene Daten zu entscheidenden Faktoren für einen erfolgreichen und effizienten Forschungsfortschritt. Zuerst definiere ich den Research Data Service (RDS) und diskutiere typische aktuelle und mögliche zukünftige Nutzungsszenarien mit RDS. Darüber hinaus bespreche ich den Stand der Technik in den Bereichen semantische Dienstleistung und Datenanmerkung und API-Konstruktion sowie infrastrukturelle Lösungen, die für die RDS-Realisierung anwendbar sind. Zum Schluss werden noch innovative Methoden der Online-Verbreitung, Förderung und effizienten Kommunikation der Forschung diskutiert.

Source

Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare. 70(2017) H.2, S.157-169

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Content

Semantic Web - Taxonomie und Thesaurus - SKOS - Historie - Klassen und Eigenschaften - Beispiele - Generierung - automatisiert - per Folksonomie - Fazit und Ausblick

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Abstract

Semantic Web ist Vision, Konzept und Programm für die nächste Generation des Internets. Semantik ist dabei ein wesentliches Element in der Transformation von Information in Wissen, sei es um eine effizientere Maschine-Maschine-Kommunikation zu ermöglichen oder um Geschäftsprozess-Management, Wissensmanagement und innerbetriebliche Kooperation durch Modellierung zu verbessern. Der Band richtet sich gleichermaßen an ein praxisorientiertes und wissenschaftliches Publikum, das nicht nur aus der technischen Perspektive einen Zugang zum Thema sucht. Der praktische Nutzen wird in der Fülle von Anwendungsbeispielen offensichtlich, in denen semantische Technologien zum Einsatz kommen. Praxisorientierung ist auch das Leitthema der Semantic Web School, die sich zum Ziel gesetzt hat, den Wissenstransfer zu semantischen Technologien anzukurbeln und den interdisziplinären Diskurs über deren Nutzen und Folgen zu intensivieren. Der vorliegende Band vereinigt 33 Beiträge von 57 Autoren aus 35 Institutionen zu einem virulenten und multidisziplinären Thema. Der Band richtet sich gleichermaßen an interessierte Laien und fachfremde Experten, die nicht nur aus der technischen Perspektive einen Zugang zum Thema suchen. Denn obwohl das Thema Semantic Web zu überwiegendem Maße ein technisches ist, sollen hier bewusst jene Aspekte angesprochen werden. die außerhalb einer ingenieurswissenschaftlichen Perspektive von Relevanz sind und vor allem die praktischen Aspekte semantischer Technologien adressieren. Dieser Anforderung wird durch die vielen Praxisbezüge und Anwendungsbeispiele innerhalb der einzelnen Beiträge Rechnung getragen. Hierbei ist es den Herausgebern jedoch wichtig darauf hinzuweisen, das Semantic Web und semantische Technologien nicht als verheißungsvolles Allheilmittel der durch Informationstechnologien heraufbeschworenen Probleme und Herausforderungen zu betrachten. Ganz im Gegenteil plädieren die Herausgeber für eine verstärkte Auseinandersetzung mit dem Thema unter Einbeziehung einer großen Vielfalt an Experten aus den unterschiedlichsten Fachbereichen, die einen reflektierten und kritischen Beitrag zu den positiven und negativen Effekten semantischer Technologien beitragen sollen.

Content

Inhalt: Im ersten Teil wird neben der begrifflichen Klärung eine Reihe von Einstiegspunkten angeboten, ohne dass der Leser das Semantic Web in seiner Systematik und Funktionsweise kennen muss. Im Beitrag von Andreas Blumauer und Tassilo Pellegrini werden die zentralen Begriffe rund um semantische Technologien vorgestellt und zentrale Konzepte überblicksartig dargestellt. Die Arbeitsgruppe um Bernardi et al. leitet über in den Themenbereich der Arbeitsorganisation und diskutieret die Bedingungen für den Einsatz semantischer Technologien aus der Perspektive der Wissensarbeit. Dem Thema Normen und Standards wurden sogar zwei Beiträge gewidmet. Während Christian Galinski die grundsätzliche Notwendigkeit von Normen zu Zwecken der Interoperabilität aus einer Top-DownPerspektive beleuchtet, eröffnet Klaus Birkenbihl einen Einblick in die technischen Standards des Semantic Web aus der Bottom-Up-Perspektive des World Wide Web Consortiums (W3C). Mit einem Beitrag zum Innovationsgrad semantischer Technologien in der ökonomischen Koordination betreten Michael Weber und Karl Fröschl weitgehend theoretisches Neuland und legen ein Fundament für weiterführende Auseinandersetzungen. Abgerundet wird der erste Teil noch mit einem Beitrag von Bernd Wohlkinger und Tassilo Pellegrini über die technologiepolitischen Dimensionen der Semantic Web Forschung in der europäischen Union.
Im zweiten Teil steht der Anwender des Semantic Web im Mittelpunkt, womit auch die erste Ebene der systematischen Auseinandersetzung mit semantischen Technologien angesprochen wird. Nicola Henze zeigt auf, welchen Beitrag semantische Technologien für die Personalisierung von Informationssystemen leisten. Stefanie Lindstaedt und Armin Ulbrich diskutieren die Möglichkeiten der Zusammenführung von Arbeiten und Lernen zu Zwecken der Kompetenzentwicklung in Arbeitsprozessen. Leo Sauermann stellt daraufhin mit der Metapher des "Semantic Desktop" ein innovatives Konzept für den Arbeitsplatz der Zukunft vor und fragt - nicht ohne eine gewisse Ironie -, ob dieser Arbeitsplatz tatsächlich auf einen physischen Ort begrenzt ist. Mark Buzinkay zeigt aus einer historischen Perspektive, wie semantische Strukturen die Navigation sowohl im Web als auch auf einzelnen Webseiten verändert haben und noch werden. Michael Schuster und Dieter Rappold adressieren die Konvergenz von Social Software und Semantic Web entlang der persönlichen Aneignung von Informationstechnologien zu Zwecken der sozialen Vernetzung. Remo Burkhard plädiert dafür, Wissensvisualisierung als Brückenfunktion zwischen technischer Infrastruktur und Nutzer wahrzunehmen und demonstriert das Potential der Wissensvisualisierung zur zielgruppengerechten Kommunikation komplexer Zusammenhänge. Abschließend zeigt Gabriele Sauberer, welche Informationskompetenzen und Schlüsselqualifikationen in der modernen Informationsgesellschaft von Bedeutung sein werden, in der der Einsatz semantische Technologien zur täglichen Wissensarbeit gehören wird.
Der dritte Teil des Bandes thematisiert die organisationalen Dimensionen des Semantic Web und demonstriert unter dem Stichwort "Wissensmanagement" eine Reihe von Konzepten und Anwendungen im betrieblichen und kollaborativen Umgang mit Information. Der Beitrag von Andreas Blumauer und Thomas Fundneider bietet einen Überblick über den Einsatz semantischer Technologien am Beispiel eines integrierten Wissensmanagement-Systems. Michael John und Jörg Drescher zeichnen den historischen Entwicklungsprozess des IT-Einsatzes für das Management von Informations- und Wissensprozessen im betrieblichen Kontext. Vor dem Hintergrund der betrieblichen Veränderungen durch Globalisierung und angeheizten Wettbewerb zeigt Heiko Beier, welche Rollen, Prozesse und Instrumente in wissensbasierten Organisationen die effiziente Nutzung von Wissen unterstützen. Mit dem Konzept des kollaborativen Wissensmanagement präsentiert das Autorenteam Schmitz et al. einen innovativen WissensmanagementAnsatz auf Peer-to-Peer-Basis mit dem Ziel der kollaborativen Einbindung und Pflege von dezentralisierten Wissensbasen. York Sure und Christoph Tempich demonstrieren anhand der Modellierungsmethode DILIGENT, welchen Beitrag Ontologien bei der Wissensvernetzung in Organisationen leisten können. Hannes Werthner und Michael Borovicka adressieren die Bedeutung semantischer Technologien für eCommerce und demonstrieren am Beispiel HARMONISE deren Einsatz im Bereich des eTourismus. Erweitert wird diese Perspektive durch den Beitrag von Fill et al., in dem das Zusammenspiel zwischen Web-Services und Geschäftsprozessen aus der Perspektive der Wirtschaftsinformatik analysiert wird. Abschließend präsentiert das Autorenteam Angele et al. eine Reihe von realisierten Anwendungen auf Basis semantischer Technologien und identifiziert kritische Faktoren für deren Einsatz.
Im vierten Teil des Bandes stehen die technischen und infrastrukturellen Aspekte im Mittelpunkt des Interesses, die für den Aufbau und Betrieb semantischer Systeme von Relevanz sind. Wolfgang Kienreich und Markus Strohmaier identifizieren die Wissensmodellierung als Basis für den Einsatz semantischer Technologien für das Knowledge Engineering und stellen zwei grundlegende Modellierungsparadigmen vor. Andreas Koller argumentiert, dass die strukturierte Ablage von Content in Content Management Systemen den Lift-Off des Semantic Web stützen wird und zeigt eine Reihe von einfachen Maßnahmen auf, wie CMS Semantic Web tauglich gemacht werden können. Alois Reitbauer gibt einen leicht verständlichen Überblick über technische Fragestellungen der IT-Integration und demonstriert anhand von Beispielen die Vorteile semantischer Technologien gegenüber konventionellen Methoden. Gerald Reif veranschaulicht die Einsatzgebiete und Leistungsfähigkeit der semantischen Annotation und stellt Tools vor, die den Nutzer bei der Dokumentenverschlagwortung unterstützen. Robert Baumgartner stellt die Funktionsweise von Wrappertechnologien zur Extraktion von Daten aus unstrukturierten Dokumenten vor und demonstriert den Nutzen am Beispiel eines B2B-Szenarios. Michael Granitzer bietet einen Überblick über statistische Verfahren der Textanalyse und zeigt, welchen Beitrag diese zur Wartung von Ontologien leisten können.
Gerhard Budin geht auf die zentrale Rolle des Terminologiemanagements bei der Ordnung und Intersubjektivierung komplexer Wissensstrukturen ein und gibt Anleitung für die Entwicklung von terminologischen Metamodellen. Marc Ehrig und Rudi Studer thematisieren Prinzipien und Herausforderungen der semantischen Integration von Ontologien zu Zwecken der Herstellung von Interoperabilität von Web Services. Wolfgang May gibt eine Einführung in das Thema Reasoning im und für das Semantic Web und zeigt auf, welche Mechanismen und Konzepte in naher Zukunft für das Semantic Web relevant werden. Abschließend führt die Autorengruppe um Polleres et al. in das junge Thema der semantischen Beschreibung von Web Services ein und adressiert Fragestellungen der Service Komposition und Automatisierung von Geschäftsprozessen. In einem Nachwort widmet sich Rafael Capurro der Frage, wie es in Zeiten eines auftauchenden semantischen Web um die philosophische Hermeneutik bestellt ist. Und er kommt zu dem Schluss, dass das Semantic Web als ein weltpolitisches Projekt verstanden werden sollte, das zu wichtig ist, um es alleine den Technikern oder den Politikern zu überlassen.

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Abstract

Search is the preferred method to access information in today's computing systems. The Web, accessed through search engines, is universally recognized as the source for answering users' information needs. However, offering a link to a Web page does not cover all information needs. Even simple problems, such as "Which theater offers an at least three-stars action movie in London close to a good Italian restaurant," can only be solved by searching the Web multiple times, e.g., by extracting a list of the recent action movies filtered by ranking, then looking for movie theaters, then looking for Italian restaurants close to them. While search engines hint to useful information, the user's brain is the fundamental platform for information integration. An important trend is the availability of new, specialized data sources-the so-called "long tail" of the Web of data. Such carefully collected and curated data sources can be much more valuable than information currently available in Web pages; however, many sources remain hidden or insulated, in the lack of software solutions for bringing them to surface and making them usable in the search context. A new class of tailor-made systems, designed to satisfy the needs of users with specific aims, will support the publishing and integration of data sources for vertical domains; the user will be able to select sources based on individual or collective trust, and systems will be able to route queries to such sources and to provide easyto-use interfaces for combining them within search strategies, at the same time, rewarding the data source owners for each contribution to effective search. Efforts such as Google's Fusion Tables show that the technology for bringing hidden data sources to surface is feasible.

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Abstract

Purpose - Ontologies are prone to wide semantic variability due to subjective points of view of their composers. The purpose of this paper is to propose a new approach for maximal unification of diverse ontologies for controversial domains by their relations. Design/methodology/approach - Effective matching or unification of multiple ontologies for a specific domain is crucial for the success of many semantic web applications, such as semantic information retrieval and organization, document tagging, summarization and search. To this end, numerous automatic and semi-automatic techniques were proposed in the past decade that attempt to identify similar entities, mostly classes, in diverse ontologies for similar domains. Apparently, matching individual entities cannot result in full integration of ontologies' semantics without matching their inter-relations with all other-related classes (and instances). However, semantic matching of ontological relations still constitutes a major research challenge. Therefore, in this paper the authors propose a new paradigm for assessment of maximal possible matching and unification of ontological relations. To this end, several unification rules for ontological relations were devised based on ontological reference rules, and lexical and textual entailment. These rules were semi-automatically implemented to extend a given ontology with semantically matching relations from another ontology for a similar domain. Then, the ontologies were unified through these similar pairs of relations. The authors observe that these rules can be also facilitated to reveal the contradictory relations in different ontologies. Findings - To assess the feasibility of the approach two experiments were conducted with different sets of multiple personal ontologies on controversial domains constructed by trained subjects. The results for about 50 distinct ontology pairs demonstrate a good potential of the methodology for increasing inter-ontology agreement. Furthermore, the authors show that the presented methodology can lead to a complete unification of multiple semantically heterogeneous ontologies. Research limitations/implications - This is a conceptual study that presents a new approach for semantic unification of ontologies by a devised set of rules along with the initial experimental evidence of its feasibility and effectiveness. However, this methodology has to be fully automatically implemented and tested on a larger dataset in future research. Practical implications - This result has implication for semantic search, since a richer ontology, comprised of multiple aspects and viewpoints of the domain of knowledge, enhances discoverability and improves search results. Originality/value - To the best of the knowledge, this is the first study to examine and assess the maximal level of semantic relation-based ontology unification.