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  1. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.20 
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    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  2. Deokattey, S.; Neelameghan, A.; Kumar, V.: ¬A method for developing a domain ontology : a case study for a multidisciplinary subject (2010) 0.03 
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    Abstract
    A method to develop a prototype domain ontology has been described. The domain selected for the study is Accelerator Driven Systems. This is a multidisciplinary and interdisciplinary subject comprising Nuclear Physics, Nuclear and Reactor Engineering, Reactor Fuels and Radioactive Waste Management. Since Accelerator Driven Systems is a vast topic, select areas in it were singled out for the study. Both qualitative and quantitative methods such as Content analysis, Facet analysis and Clustering were used, to develop the web-based model.
    Date
    22. 7.2010 19:41:16
  3. Kruk, S.R.; Kruk, E.; Stankiewicz, K.: Evaluation of semantic and social technologies for digital libraries (2009) 0.02 
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    Abstract
    Libraries are the tools we use to learn and to answer our questions. The quality of our work depends, among others, on the quality of the tools we use. Recent research in digital libraries is focused, on one hand on improving the infrastructure of the digital library management systems (DLMS), and on the other on improving the metadata models used to annotate collections of objects maintained by DLMS. The latter includes, among others, the semantic web and social networking technologies. Recently, the semantic web and social networking technologies are being introduced to the digital libraries domain. The expected outcome is that the overall quality of information discovery in digital libraries can be improved by employing social and semantic technologies. In this chapter we present the results of an evaluation of social and semantic end-user information discovery services for the digital libraries.
    Date
    1. 8.2010 12:35:22
  4. Kiren, T.; Shoaib, M.: ¬A novel ontology matching approach using key concepts (2016) 0.02 
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    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 68(2016) no.1, S.99-111
  5. Zhitomirsky-Geffet, M.; Bar-Ilan, J.: Towards maximal unification of semantically diverse ontologies for controversial domains (2014) 0.02 
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    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 66(2014) no.5, S.494-518
  6. Hocker, J.; Schindler, C.; Rittberger, M.: Participatory design for ontologies : a case study of an open science ontology for qualitative coding schemas (2020) 0.02 
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    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 72(2020) no.4, S.671-685
  7. Davies, J.; Fensel, D.; Harmelen, F. van: Conclusions: ontology-driven knowledge management : towards the Semantic Web? (2004) 0.02 
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    Abstract
    The global economy is rapidly becoming more and more knowledge intensive. Knowledge is now widely recognized as the fourth production factor, on an equal footing with the traditional production factors of labour, capital and materials. Managing knowledge is as important as the traditional management of labour, capital and materials. In this book, we have shown how Semantic Web technology can make an important contribution to knowledge management.
    Source
    Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a
  8. Thenmalar, S.; Geetha, T.V.: Enhanced ontology-based indexing and searching (2014) 0.01 
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    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 66(2014) no.6, S.678-696
  9. Fensel, D.; Staab, S.; Studer, R.; Harmelen, F. van; Davies, J.: ¬A future perspective : exploiting peer-to-peer and the Semantic Web for knowledge management (2004) 0.01 
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    Abstract
    Over the past few years, we have seen a growing interest in the potential of both peer-to-peer (P2P) computing and the use of more formal approaches to knowledge management, involving the development of ontologies. This penultimate chapter discusses possibilities that both approaches may offer for more effective and efficient knowledge management. In particular, we investigate how the two paradigms may be combined. In this chapter, we describe our vision in terms of a set of future steps that need to be taken to bring the results described in earlier chapters to their full potential.
    Source
    Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a
  10. Kiryakov, A.; Simov, K.; Ognyanov, D.: Ontology middleware and reasoning (2004) 0.01 
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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.
    Source
    Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a
  11. Schmitz-Esser, W.: Language of general communication and concept compatibility (1996) 0.01 
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    Pages
    S.11-22
  12. Sure, Y.; Studer, R.: ¬A methodology for ontology-based knowledge management (2004) 0.01 
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    Abstract
    Ontologies are a core element of the knowledge management architecture described in Chapter 1. In this chapter we describe a methodology for application driven ontology development, covering the whole project lifecycle from the kick off phase to the maintenance phase. Existing methodologies and practical ontology development experiences have in common that they start from the identification of the purpose of the ontology and the need for domain knowledge acquisition. They differ in their foci and following steps to be taken. In our approach of the ontology development process, we integrate aspects from existing methodologies and lessons learned from practical experience (as described in the Section 3.7). We put ontology development into a wider organizational context by performing an a priori feasibility study. The feasibility study is based on CommonKADS. We modified certain aspects of CommonKADS for a tight integration of the feasibility study into our methodology.
    Source
    Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a
  13. Uren, V.; Cimiano, P.; Iria, J.; Handschuh, S.; Vargas-Vera, M.; Motta, E.; Ciravegnac, F.: Semantic annotation for knowledge management : requirements and a survey of the state of the art (2006) 0.01 
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    Abstract
    While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. In the emerging Semantic Web, search, interpretation and aggregation can be addressed by ontology-based semantic mark-up. In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. This analysis shows that, while there is still some way to go before semantic annotation tools will be able to address fully all the knowledge management needs, research in the area is active and making good progress.
  14. Klein, M.; Ding, Y.; Fensel, D.; Omelayenko, B.: Ontology management : storing, aligning and maintaining ontologies (2004) 0.01 
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    Abstract
    Ontologies need to be stored, sometimes aligned and their evolution needs to be managed. All these tasks together are called ontology management. Alignment is a central task in ontology re-use. Re-use of existing ontologies often requires considerable effort: the ontologies either need to be integrated, which means that they are merged into one new ontology, or the ontologies can be kept separate. In both cases, the ontologies have to be aligned, which means that they have to be brought into mutual agreement. The problems that underlie the difficulties in integrating and aligning are the mismatches that may exist between separate ontologies. Ontologies can differ at the language level, which can mean that they are represented in a different syntax, or that the expressiveness of the ontology language is dissimilar. Ontologies also can have mismatches at the model level, for example, in the paradigm, or modelling style. Ontology alignment is very relevant in a Semantic Web context. The Semantic Web will provide us with a lot of freely accessible domain specific ontologies. To form a real web of semantics - which will allow computers to combine and infer implicit knowledge - those separate ontologies should be aligned and linked.
    Support for evolving ontologies is required in almost all situations where ontologies are used in real-world applications. In those cases, ontologies are often developed by several persons and will continue to evolve over time, because of changes in the real world, adaptations to different tasks, or alignments to other ontologies. To prevent that such changes will invalidate existing usage, a change management methodology is needed. This involves advanced versioning methods for the development and the maintenance of ontologies, but also configuration management, that takes care of the identification, relations and interpretation of ontology versions. All these aspects come together in integrated ontology library systems. When the number of different ontologies is increasing, the task of storing, maintaining and re-organizing them to secure the successful re-use of ontologies is challenging. Ontology library systems can help in the grouping and reorganizing ontologies for further re-use, integration, maintenance, mapping and versioning. Basically, a library system offers various functions for managing, adapting and standardizing groups of ontologies. Such integrated systems are a requirement for the Semantic Web to grow further and scale up. In this chapter, we describe a number of results with respect to the above mentioned areas. We start with a description of the alignment task and show a meta-ontology that is developed to specify the mappings. Then, we discuss the problems that are caused by evolving ontologies and describe two important elements of a change management methodology. Finally, in Section 4.4 we survey existing library systems and formulate a wish-list of features of an ontology library system.
    Source
    Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a
  15. Reimer, U.; Brockhausen, P.; Lau, T.; Reich, J.R.: Ontology-based knowledge management at work : the Swiss life case studies (2004) 0.01 
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    Abstract
    This chapter describes two case studies conducted by the Swiss Life insurance group with the objective of proving the practical applicability and superiority of ontology-based knowledge management over classical approaches based on text retrieval technologies. The first case study in the domain of skills management uses manually constructed ontologies about skills, job functions and education. The purpose of the system is to give support for finding employees with certain skills. The ontologies are used to ensure that the user description of skills and the machine-held index of skills and people use the same vocabulary. The use of a shared vocabulary increases the performance of such a system significantly. The second case study aims at improving content-oriented access to passages of a 1000 page document about the International Accounting Standard on the corporate intranet. To this end, an ontology was automatically extracted from the document. It can be used to reformulate queries that turned out not to deliver the intended results. Since the ontology was automatically built, it is of a rather simple structure, consisting of weighted semantic associations between the relevant concepts in the document. We therefore call it a 'lightweight ontology'. The two case studies cover quite different aspects of using ontologies in knowledge management applications. Whereas in the second case study an ontology was automatically derived from a search space to improve information retrieval, in the first skills management case study the ontology itself introduces a structured search space. In one case study we gathered experience in building an ontology manually, while the challenge of the other case study was automatic ontology creation. A number of the novel Semantic Web-based tools described elsewhere in this book were used to build the two systems and both case studies described have led to projects to deploy live systems within Swiss Life.
    Source
    Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a
  16. Davies, J.; Duke, A.; Stonkus, A.: OntoShare: evolving ontologies in a knowledge sharing system (2004) 0.01 
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    Abstract
    We saw in the introduction how the Semantic Web makes possible a new generation of knowledge management tools. We now turn our attention more specifically to Semantic Web based support for virtual communities of practice. The notion of communities of practice has attracted much attention in the field of knowledge management. Communities of practice are groups within (or sometimes across) organizations who share a common set of information needs or problems. They are typically not a formal organizational unit but an informal network, each sharing in part a common agenda and shared interests or issues. In one example it was found that a lot of knowledge sharing among copier engineers took place through informal exchanges, often around a water cooler. As well as local, geographically based communities, trends towards flexible working and globalisation have led to interest in supporting dispersed communities using Internet technology. The challenge for organizations is to support such communities and make them effective. Provided with an ontology meeting the needs of a particular community of practice, knowledge management tools can arrange knowledge assets into the predefined conceptual classes of the ontology, allowing more natural and intuitive access to knowledge. Knowledge management tools must give users the ability to organize information into a controllable asset. Building an intranet-based store of information is not sufficient for knowledge management; the relationships within the stored information are vital. These relationships cover such diverse issues as relative importance, context, sequence, significance, causality and association. The potential for knowledge management tools is vast; not only can they make better use of the raw information already available, but they can sift, abstract and help to share new information, and present it to users in new and compelling ways.
    Source
    Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a
  17. Naskar, D.; Das, S.: HNS ontology using faceted approach (2019) 0.01 
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    Abstract
    The purpose of this research is to develop an ontology with subsequent testing and evaluation, for identifying utility and value. The domain that has been chosen is human nervous system (HNS) disorders. It is hypothesized here that an ontology-based patient records management system is more effective in meeting and addressing complex information needs of health-care personnel. Therefore, this study has been based on the premise that developing an ontology and using it as a component of the search interface in hospital records management systems will lead to more efficient and effective management of health-care.It is proposed here to develop an ontology of the domain of HNS disorders using a standard vocabulary such as MeSH or SNOMED CT. The principal classes of an ontology include facet analysis for arranging concepts based on their common characteristics to build mutually exclusive classes. We combine faceted theory with description logic, which helps us to better query and retrieve data by implementing an ontological model. Protégé 5.2.0 was used as ontology editor. The use of ontologies for domain modelling will be of acute help to doctors for searching patient records. In this paper we show how the faceted approach helps us to build a flexible model and retrieve better information. We use the medical domain as a case study to show examples and implementation.
  18. Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009) 0.01 
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    Date
    31. 7.2010 16:58:22
  19. Giunchiglia, F.; Villafiorita, A.; Walsh, T.: Theories of abstraction (1997) 0.01 
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    Date
    1.10.2018 14:13:22
  20. Kruk, S.R.; Westerki, A.; Kruk, E.: Architecture of semantic digital libraries (2009) 0.01 
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    Abstract
    The main motivation of this chapter was to gather existing requirements and solutions, and to present a generic architectural design of semantic digital libraries. This design is meant to answer a number of requirements, such as interoperability or ability to exchange resources and solutions, and set up the foundations for the best practices in the new domain of semantic digital libraries. We start by presenting the library from different high-level perspectives, i.e., user (see Sect. 2) and metadata (see Sect. 1) perspective; this overview narrows the scope and puts emphasis on certain aspects related to the system perspective, i.e., the architecture of the actual digital library management system. We conclude by presenting the system architecture from three perspectives: top-down layered architecture (see Sect. 3), vertical architecture of core services (see Sect. 4), and stack of enabling infrastructures (see Sect. 5); based upon the observations and evaluation of the contemporary state of the art presented in the previous sections, these last three subsections will describe an in-depth model of the digital library management system.

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