Search (110 results, page 1 of 6)

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Abstract

Digital libraries have become commodity in the current world of Internet. More and more information is produced, and more and more non-digital information is being rendered available. The new, more user friendly, community-oriented technologies used throughout the Internet are raising the bar of expectations. Digital libraries cannot stand still with their technologies; if not for the sake of handling rapidly growing amount and diversity of information, they must provide for better user experience matching and overgrowing standards set by the industry. The next generation of digital libraries combine technological solutions, such as P2P, SOA, or Grid, with recent research on semantics and social networks. These solutions are put into practice to answer a variety of requirements imposed on digital libraries.

Theme

Information Gateway

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Abstract

Innovative research institutes rely on the availability of complete and accurate information about new research and development, and it is the business of information providers such as Elsevier to provide the required information in a cost-effective way. It is very likely that the semantic web will make an important contribution to this effort, since it facilitates access to an unprecedented quantity of data. However, with the unremitting growth of scientific information, integrating access to all this information remains a significant problem, not least because of the heterogeneity of the information sources involved - sources which may use different syntactic standards (syntactic heterogeneity), organize information in very different ways (structural heterogeneity) and even use different terminologies to refer to the same information (semantic heterogeneity). The ability to address these different kinds of heterogeneity is the key to integrated access. Thesauri have already proven to be a core technology to effective information access as they provide controlled vocabularies for indexing information, and thereby help to overcome some of the problems of free-text search by relating and grouping relevant terms in a specific domain. However, currently there is no open architecture which supports the use of these thesauri for querying other data sources. For example, when we move from the centralized and controlled use of EMTREE within EMBASE.com to a distributed setting, it becomes crucial to improve access to the thesaurus by means of a standardized representation using open data standards that allow for semantic qualifications. In general, mental models and keywords for accessing data diverge between subject areas and communities, and so many different ontologies have been developed. An ideal architecture must therefore support the disclosure of distributed and heterogeneous data sources through different ontologies. The aim of the DOPE project (Drug Ontology Project for Elsevier) is to investigate the possibility of providing access to multiple information sources in the area of life science through a single interface.

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Abstract

Topic Maps are a standardized modelling approach for the semantic annotation and description of WWW resources. They enable an improved search and navigational access on information objects stored in semi-structured information spaces like the WWW. However, the according standards ISO 13250 and XTM (XML Topic Maps) lack formal semantics, several questions concerning e.g. subclassing, inheritance or merging of topics are left open. The proposed TMUML meta model, directly derived from the well known UML meta model, is a meta model for Topic Maps which enables semantic constraints to be formulated in OCL (object constraint language) in order to answer such open questions and overcome possible inconsistencies in Topic Map repositories. We will examine the XTM merging conditions and show, in several examples, how the TMUML meta model enables semantic constraints for Topic Map merging to be formulated in OCL. Finally, we will show how the TM validation process, i.e., checking if a Topic Map is well formed, includes our merging conditions.

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Abstract

This thesaurus-based search system uses automatic indexing, RDF-based querying, and concept-based visualization of results to support exploration of large online document repositories. Innovative research institutes rely on the availability of complete and accurate information about new research and development. Information providers such as Elsevier make it their business to provide the required information in a cost-effective way. The Semantic Web will likely contribute significantly to this effort because it facilitates access to an unprecedented quantity of data. The DOPE project (Drug Ontology Project for Elsevier) explores ways to provide access to multiple lifescience information sources through a single interface. With the unremitting growth of scientific information, integrating access to all this information remains an important problem, primarily because the information sources involved are so heterogeneous. Sources might use different syntactic standards (syntactic heterogeneity), organize information in different ways (structural heterogeneity), and even use different terminologies to refer to the same information (semantic heterogeneity). Integrated access hinges on the ability to address these different kinds of heterogeneity. Also, mental models and keywords for accessing data generally diverge between subject areas and communities; hence, many different ontologies have emerged. An ideal architecture must therefore support the disclosure of distributed and heterogeneous data sources through different ontologies. To serve this need, we've developed a thesaurus-based search system that uses automatic indexing, RDF-based querying, and concept-based visualization. We describe here the conversion of an existing proprietary thesaurus to an open standard format, a generic architecture for thesaurus-based information access, an innovative user interface, and results of initial user studies with the resulting DOPE system.

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Abstract

In order to transfer the Chinese Classified Thesaurus (CCT) into a machine-processable format and provide CCT-based Web services, a pilot study has been conducted in which a variety of selected CCT classes and mapped thesaurus entries are encoded with SKOS. OWL and RDFS are also used to encode the same contents for the purposes of feasibility and cost-benefit comparison. CCT is a collected effort led by the National Library of China. It is an integration of the national standards Chinese Library Classification (CLC) 4th edition and Chinese Thesaurus (CT). As a manually created mapping product, CCT provides for each of the classes the corresponding thesaurus terms, and vice versa. The coverage of CCT includes four major clusters: philosophy, social sciences and humanities, natural sciences and technologies, and general works. There are 22 main-classes, 52,992 sub-classes and divisions, 110,837 preferred thesaurus terms, 35,690 entry terms (non-preferred terms), and 59,738 pre-coordinated headings (Chinese Classified Thesaurus, 2005) Major challenges of encoding this large vocabulary comes from its integrated structure. CCT is a result of the combination of two structures (illustrated in Figure 1): a thesaurus that uses ISO-2788 standardized structure and a classification scheme that is basically enumerative, but provides some flexibility for several kinds of synthetic mechanisms Other challenges include the complex relationships caused by differences of granularities of two original schemes and their presentation with various levels of SKOS elements; as well as the diverse coordination of entries due to the use of auxiliary tables and pre-coordinated headings derived from combining classes, subdivisions, and thesaurus terms, which do not correspond to existing unique identifiers. The poster reports the progress, shares the sample SKOS entries, and summarizes problems identified during the SKOS encoding process. Although OWL Lite and OWL Full provide richer expressiveness, the cost-benefit issues and the final purposes of encoding CCT raise questions of using such approaches.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Abstract

This paper present an alternative approach to knowledge organization based on semiotic reasoning. The semantic distance between domain specific terminology and KOS is analyzed by means of their different sign systems. It is argued that a faceted approach may provide the means needed to minimize the gap between knowledge domains and KOS.

Series

Advances in knowledge organization; vol.10

Source

Knowledge organization for a global learning society: Proceedings of the 9th International ISKO Conference, 4-7 July 2006, Vienna, Austria. Hrsg.: G. Budin, C. Swertz u. K. Mitgutsch

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Abstract

As information becomes richer and more complex, alternative information-organization methods are needed to more effectively and efficiently retrieve information from various systems, including the Web. The objective of this study is to explore how a Topic Maps-based ontology approach affects users' searching performance. Forty participants participated in a task-based evaluation where two dependent variables, recall and search time, were measured. The results of this study indicate that a Topic Maps-based ontology information retrieval (TOIR) system has a significant and positive effect on both recall and search time, compared to a thesaurus-based information retrieval (TIR) system. These results suggest that the inclusion of a Topic Maps-based ontology is a beneficial approach to take when designing information retrieval systems.

Source

Journal of the American Society for Information Science and Technology. 59(2008) no.12, S.1898-1911

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Abstract

It is proposed that sufficient research into ontology design has not been achieved and that this deficiency has led to the insufficiency of ontology in reinforcing its communications frameworks, knowledge sharing and re-use applications. In order to diagnose the problems of ontology research, I first survey the notion of ontology in the context of ontology design, based on a Means-Ends tool provided by a Cognitive Work Analysis. The potential contributions of knowledge organization in library and information sciences that can be used to improve the limitations of ontology research are demonstrated. I propose a context-centered view as an approach for ontology design, and present faceted classification as an appropriate method for structuring ontology. In addition, I also provides a case study of wine ontology in order to demonstrate how knowledge organization approaches in library and information science can improve ontology design.

Source

Knowledge organization. 35(2008) no.4, S.209-221

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Abstract

The task of an information architect is to create web sites where users can actually find the information they are looking for. As the ocean of information rises and leaves what we seek ever more deeply buried in what we don't seek, this discipline becomes ever more relevant. Information architecture involves many different aspects of web site creation and organization, but its principal tools are information organization techniques developed in other disciplines. Most of these techniques come from library science, such as thesauri, taxonomies, and faceted classification. Topic maps are a relative newcomer to this area and bring with them the promise of better-organized web sites, compared to what is possible with existing techniques. However, it is not generally understood how topic maps relate to the traditional techniques, and what advantages and disadvantages they have, compared to these techniques. The aim of this paper is to help build a better understanding of these issues.

Source

Journal of information science. 30(2005) no.4, S.378-391

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Abstract

Ontologies have become an important issue in research communities across several disciplines. This paper discusses some of the innovative techniques involving automatic terminology resources acquisition are briefly discussed. Suggests that NLP-based ontologies are useful in reducing the cost of ontology engineering. Emphasizes that linguistic ontologies covering both ontological and lexical information can offer solutions since they can be more easily updated by the resources of NLP products.

Source

Knowledge organization, information systems and other essays: Professor A. Neelameghan Festschrift. Ed. by K.S. Raghavan and K.N. Prasad

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Abstract

Topic Maps is an international standard technology for describing knowledge structures and using them to improve the findability of information. It is based on a formal model that subsumes those of traditional finding aids such as indexes, glossaries, and thesauri, and extends them to cater for the additional complexities of digital information. Topic Maps is increasingly used in enterprise information integration, knowledge management, e-learning, and digital libraries, and as the foundation for Web-based information delivery solutions. This entry provides a comprehensive treatment of the core concepts, as well as describing the background and current status of the standard and its relationship to traditional knowledge organization techniques.

Source

Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates

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Abstract

This paper discusses an axiomatic approach for the semantic integration of ontologies, an approach that extends to first order logic, a previous approach based on information flow. This axiomatic approach is represented in the Information Flow Framework (IFF), a metalevel framework for organizing the information that appears in digital libraries, distributed databases and ontologies. The paper argues that the semantic integration of ontologies is the two-step process of alignment and unification. Ontological alignment consists of the sharing of common terminology and semantics through a mediating ontology. Ontological unification, concentrated in a virtual ontology of community connections, is fusion of the alignment diagram of participant community ontologies-the quotient of the sum of the participant portals modulo the ontological alignment structure.

Content

Beitrag eines Themenheftes "Knowledge organization and classification in international information retrieval"

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Content

This article reports an applied research on the construction and implementation of a semantically structured conceptual prototype to help in the organization and representation of human knowledge in hypertextual systems, based on four references: the Facet Analysis Theory (FAT), the Conceptual Map Theory, semantic structure of hypertext links and the technical guidelines of the Associacao Brasileira de Normas Técnicas (ABNT). This prototype, called Modelo Hipertextual para Organizacao de Documentos (MHTX) - Model For Hypertext Organization of Documents HTXM - is formed by a semantic structure called Conceptual Map (CM) and Expanded Summary (ES), the latter based on the summary of a selected doctoral thesis to which access points were designed. In the future, this prototype maybe used to implement a digital libraty called BTDECI - UFMG (Biblioteca de Teses e Dissertacöes do Programa de Pós-Graduacao da Escola de Ciência da Informacao da UFMG - Library of Theses and Dissertations of the Graduate Program of School of Information Science of Universidade Federal de Minas Gerais).

Series

Advances in knowledge organization; vol.11

Source

Culture and identity in knowledge organization: Proceedings of the Tenth International ISKO Conference 5-8 August 2008, Montreal, Canada. Ed. by Clément Arsenault and Joseph T. Tennis

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Abstract

Classical knowledge representation methods have been successfully working for years with established - but in a way restricted and vague - relations such as synonymy, hierarchy (meronymy, hyponymy) and unspecified associations. Recent developments like ontologies and folksonomies show new forms of collaboration, indexing and knowledge representation and encourage the reconsideration of standard knowledge relationships for practical use. In a summarizing overview we show which relations are currently used in knowledge organization systems (controlled vocabularies, ontologies and folksonomies) and which relations are expressed explicitly or which may be inherently hidden in them.

Source

Information - Wissenschaft und Praxis. 59(2008) H.2, S.100-107

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Abstract

Purpose - The purpose of this paper is to present descriptive characteristics of the historical development of concept networks. The linguistic principles, mechanisms and motivations behind the evolution of concept networks are discussed. Implications emanating from the idea of the historical development of concept networks are discussed in relation to knowledge representation and organization schemes. Design/methodology/approach - Natural language data including both speech and text are analyzed by examining discourse contexts in which a linguistic element such as a polysemy or homonym occurs. Linguistic literature on the historical development of concept networks is reviewed and analyzed. Findings - Semantic sense relations in concept networks can be captured in a systematic and regular manner. The mechanism and impetus behind the process of concept network development suggest that semantic senses in concept networks are closely intertwined with pragmatic contexts and discourse structure. The interrelation and permeability of the semantic senses of concept networks are captured on a continuum scale based on three linguistic parameters: concrete shared semantic sense; discourse and text structure; and contextualized pragmatic information. Research limitations/implications - Research findings signify the critical need for linking discourse structure and contextualized pragmatic information to knowledge representation and organization schemes. Originality/value - The idea of linguistic characteristics, principles, motivation and mechanisms underlying the evolution of concept networks provides theoretical ground for developing a model for integrating knowledge representation and organization schemes with discourse structure and contextualized pragmatic information.

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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.

Source

Information technology and libraries. 26(2007) no.3, S.39-51

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Abstract

This chapter describes not so much what digital libraries are but what digital libraries with semantic support could and should be. It discusses the nature of Knowledge Organization Systems (KOS) and how KOS can support digital library users. It projects a vision for designers to make and for users to demand better digital libraries. What is a digital library? The term \Digital Library" (DL) is used to refer to a range of systems, from digital object and metadata repositories, reference-linking systems, archives, and content management systems to complex systems that integrate advanced digital library services and support for research and practice communities. A DL may offer many technology-enabled functions and services that support users, both as information producers and as information users. Many of these functions appear in information systems that would not normally be considered digital libraries, making boundaries even more blurry. Instead of pursuing the hopeless quest of coming up with the definition of digital library, we present a framework that allows a clear and somewhat standardized description of any information system so that users can select the system(s) that best meet their requirements. Section 2 gives a broad outline for more detail see the DELOS DL Reference Model.

Theme

Information Gateway

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Abstract

Purpose - To propose a comprehensive and semi-automatic method for constructing or updating knowledge organization tools such as thesauri. Design/methodology/approach - The paper proposes a comprehensive methodology for thesaurus construction and maintenance combining shallow NLP with a clustering algorithm and an information visualization interface. The resulting system TermWatch, extracts terms from a text collection, mines semantic relations between them using complementary linguistic approaches and clusters terms using these semantic relations. The clusters are mapped onto a 2D using an integrated visualization tool. Findings - The clusters formed exhibit the different relations necessary to populate a thesaurus or ontology: synonymy, generic/specific and relatedness. The clusters represent, for a given term, its closest neighbours in terms of semantic relations. Practical implications - This could change the way in which information professionals (librarians and documentalists) undertake knowledge organization tasks. TermWatch can be useful either as a starting point for grasping the conceptual organization of knowledge in a huge text collection without having to read the texts, then actually serving as a suggestive tool for populating different hierarchies of a thesaurus or an ontology because its clusters are based on semantic relations. Originality/value - This lies in several points: combined use of linguistic relations with an adapted clustering algorithm, which is scalable and can handle sparse data. The paper proposes a comprehensive approach to semantic relations acquisition whereas existing studies often use one or two approaches. The domain knowledge maps produced by the system represents an added advantage over existing approaches to automatic thesaurus construction in that clusters are formed using semantic relations between domain terms. Thus while offering a meaningful synthesis of the information contained in the original corpus through clustering, the results can be used for knowledge organization tasks (thesaurus building and ontology population) The system also constitutes a platform for performing several knowledge-oriented tasks like science and technology watch, textmining, query refinement.

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Abstract

Ontologies improve IR systems regarding its retrieval and presentation of information, which make the task of finding information more effective, efficient, and interactive. In this paper we argue that ontologies also greatly improve the engineering of such systems. We created a framework that uses ontology to drive the process of engineering an IR system. We developed a prototype that shows how a domain specialist without knowledge in the IR field can build an IR system with interactive components. The resulting system provides support for users not only to find their information needs but also to extend their state of knowledge. This way, our approach to ontology-enabled information retrieval addresses both the engineering aspect described here and also the usability aspect described elsewhere.

Date

28.11.2016 12:43:22

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Abstract

The aim of this chapter is to demonstrate that semantic issues underlie all research questions within Library and Information Science (LIS, or, as hereafter, IS) and, in particular, the subfield known as Knowledge Organization (KO). Further, it seeks to show that semantics is a field influenced by conflicting views and discusses why it is important to argue for the most fruitful one of these. Moreover, the chapter demonstrates that IS has not yet addressed semantic problems in systematic fashion and examines why the field is very fragmented and without a proper theoretical basis. The focus here is on broad interdisciplinary issues and the long-term perspective. The theoretical problems involving semantics and concepts are very complicated. Therefore, this chapter starts by considering tools developed in KO for information retrieval (IR) as basically semantic tools. In this way, it establishes a specific IS focus on the relation between KO and semantics. It is well known that thesauri consist of a selection of concepts supplemented with information about their semantic relations (such as generic relations or "associative relations"). Some words in thesauri are "preferred terms" (descriptors), whereas others are "lead-in terms." The descriptors represent concepts. The difference between "a word" and "a concept" is that different words may have the same meaning and similar words may have different meanings, whereas one concept expresses one meaning.

Source

Annual review of information science and technology. 41(2007), S.367-405