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  1. Bittner, T.; Donnelly, M.; Winter, S.: Ontology and semantic interoperability (2006) 0.14 
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    Abstract
    One of the major problems facing systems for Computer Aided Design (CAD), Architecture Engineering and Construction (AEC) and Geographic Information Systems (GIS) applications today is the lack of interoperability among the various systems. When integrating software applications, substantial di culties can arise in translating information from one application to the other. In this paper, we focus on semantic di culties that arise in software integration. Applications may use di erent terminologies to describe the same domain. Even when appli-cations use the same terminology, they often associate di erent semantics with the terms. This obstructs information exchange among applications. To cir-cumvent this obstacle, we need some way of explicitly specifying the semantics for each terminology in an unambiguous fashion. Ontologies can provide such specification. It will be the task of this paper to explain what ontologies are and how they can be used to facilitate interoperability between software systems used in computer aided design, architecture engineering and construction, and geographic information processing.
    Date
    3.12.2016 18:39:22
  2. Assem, M. van: Converting and integrating vocabularies for the Semantic Web (2010) 0.06 
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    Abstract
    This thesis focuses on conversion of vocabularies for representation and integration of collections on the Semantic Web. A secondary focus is how to represent metadata schemas (RDF Schemas representing metadata element sets) such that they interoperate with vocabularies. The primary domain in which we operate is that of cultural heritage collections. The background worldview in which a solution is sought is that of the Semantic Web research paradigmwith its associated theories, methods, tools and use cases. In other words, we assume the SemanticWeb is in principle able to provide the context to realize interoperable collections. Interoperability is dependent on the interplay between representations and the applications that use them. We mean applications in the widest sense, such as "search" and "annotation". These applications or tasks are often present in software applications, such as the E-Culture application. It is therefore necessary that applications requirements on the vocabulary representation are met. This leads us to formulate the following problem statement: HOW CAN EXISTING VOCABULARIES BE MADE AVAILABLE TO SEMANTIC WEB APPLICATIONS?
    We refine the problem statement into three research questions. The first two focus on the problem of conversion of a vocabulary to a Semantic Web representation from its original format. Conversion of a vocabulary to a representation in a Semantic Web language is necessary to make the vocabulary available to SemanticWeb applications. In the last question we focus on integration of collection metadata schemas in a way that allows for vocabulary representations as produced by our methods. Academisch proefschrift ter verkrijging van de graad Doctor aan de Vrije Universiteit Amsterdam, Dutch Research School for Information and Knowledge Systems.
  3. Resource Description Framework (RDF) (2004) 0.06 
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    Abstract
    The Resource Description Framework (RDF) integrates a variety of applications from library catalogs and world-wide directories to syndication and aggregation of news, software, and content to personal collections of music, photos, and events using XML as an interchange syntax. The RDF specifications provide a lightweight ontology system to support the exchange of knowledge on the Web. The W3C Semantic Web Activity Statement explains W3C's plans for RDF, including the RDF Core WG, Web Ontology and the RDF Interest Group.
    Content
    Specifications - Bookmarks (Intro * Articles) - Projects and Applications - Developer tools - Schemas - Related Technologies - Timeline
  4. SKOS Simple Knowledge Organization System Reference : W3C Recommendation 18 August 2009 (2009) 0.05 
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    Abstract
    This document defines the Simple Knowledge Organization System (SKOS), a common data model for sharing and linking knowledge organization systems via the Web. Many knowledge organization systems, such as thesauri, taxonomies, classification schemes and subject heading systems, share a similar structure, and are used in similar applications. SKOS captures much of this similarity and makes it explicit, to enable data and technology sharing across diverse applications. The SKOS data model provides a standard, low-cost migration path for porting existing knowledge organization systems to the Semantic Web. SKOS also provides a lightweight, intuitive language for developing and sharing new knowledge organization systems. It may be used on its own, or in combination with formal knowledge representation languages such as the Web Ontology language (OWL). This document is the normative specification of the Simple Knowledge Organization System. It is intended for readers who are involved in the design and implementation of information systems, and who already have a good understanding of Semantic Web technology, especially RDF and OWL. For an informative guide to using SKOS, see the [SKOS-PRIMER].
  5. Gómez-Pérez, A.; Corcho, O.: Ontology languages for the Semantic Web (2015) 0.04 
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    Abstract
    Ontologies have proven to be an essential element in many applications. They are used in agent systems, knowledge management systems, and e-commerce platforms. They can also generate natural language, integrate intelligent information, provide semantic-based access to the Internet, and extract information from texts in addition to being used in many other applications to explicitly declare the knowledge embedded in them. However, not only are ontologies useful for applications in which knowledge plays a key role, but they can also trigger a major change in current Web contents. This change is leading to the third generation of the Web-known as the Semantic Web-which has been defined as "the conceptual structuring of the Web in an explicit machine-readable way."1 This definition does not differ too much from the one used for defining an ontology: "An ontology is an explicit, machinereadable specification of a shared conceptualization."2 In fact, new ontology-based applications and knowledge architectures are developing for this new Web. A common claim for all of these approaches is the need for languages to represent the semantic information that this Web requires-solving the heterogeneous data exchange in this heterogeneous environment. Here, we don't decide which language is best of the Semantic Web. Rather, our goal is to help developers find the most suitable language for their representation needs. The authors analyze the most representative ontology languages created for the Web and compare them using a common framework.
    Source
    IEEE intelligent systems 2002, Jan./Feb., S.54-60
  6. Miles, A.: SKOS: requirements for standardization (2006) 0.04 
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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.
    Footnote
    Presented at the International Conference on Dublin Core and Metadata Applications in October 2006
  7. Giunchiglia, F.; Zaihrayeu, I.; Farazi, F.: Converting classifications into OWL ontologies (2009) 0.04 
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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.
  8. Shen, M.; Liu, D.-R.; Huang, Y.-S.: Extracting semantic relations to enrich domain ontologies (2012) 0.03 
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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
  9. Lacasta, J.; Nogueras-Iso, J.; López-Pellicer, F.J.; Muro-Medrano, P.R.; Zarazaga-Soria, F.J.: ThManager : an open source tool for creating and visualizing SKOS (2007) 0.03 
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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/.
  10. Arenas, M.; Cuenca Grau, B.; Kharlamov, E.; Marciuska, S.; Zheleznyakov, D.: Faceted search over ontology-enhanced RDF data (2014) 0.03 
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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.
  11. Mirizzi, R.: Exploratory browsing in the Web of Data (2011) 0.03 
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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.
  12. Jacobs, I.: From chaos, order: W3C standard helps organize knowledge : SKOS Connects Diverse Knowledge Organization Systems to Linked Data (2009) 0.03 
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    Abstract
    18 August 2009 -- Today W3C announces a new standard that builds a bridge between the world of knowledge organization systems - including thesauri, classifications, subject headings, taxonomies, and folksonomies - and the linked data community, bringing benefits to both. Libraries, museums, newspapers, government portals, enterprises, social networking applications, and other communities that manage large collections of books, historical artifacts, news reports, business glossaries, blog entries, and other items can now use Simple Knowledge Organization System (SKOS) to leverage the power of linked data. As different communities with expertise and established vocabularies use SKOS to integrate them into the Semantic Web, they increase the value of the information for everyone.
    Content
    SKOS Adapts to the Diversity of Knowledge Organization Systems A useful starting point for understanding the role of SKOS is the set of subject headings published by the US Library of Congress (LOC) for categorizing books, videos, and other library resources. These headings can be used to broaden or narrow queries for discovering resources. For instance, one can narrow a query about books on "Chinese literature" to "Chinese drama," or further still to "Chinese children's plays." Library of Congress subject headings have evolved within a community of practice over a period of decades. By now publishing these subject headings in SKOS, the Library of Congress has made them available to the linked data community, which benefits from a time-tested set of concepts to re-use in their own data. This re-use adds value ("the network effect") to the collection. When people all over the Web re-use the same LOC concept for "Chinese drama," or a concept from some other vocabulary linked to it, this creates many new routes to the discovery of information, and increases the chances that relevant items will be found. As an example of mapping one vocabulary to another, a combined effort from the STITCH, TELplus and MACS Projects provides links between LOC concepts and RAMEAU, a collection of French subject headings used by the Bibliothèque Nationale de France and other institutions. SKOS can be used for subject headings but also many other approaches to organizing knowledge. Because different communities are comfortable with different organization schemes, SKOS is designed to port diverse knowledge organization systems to the Web. "Active participation from the library and information science community in the development of SKOS over the past seven years has been key to ensuring that SKOS meets a variety of needs," said Thomas Baker, co-chair of the Semantic Web Deployment Working Group, which published SKOS. "One goal in creating SKOS was to provide new uses for well-established knowledge organization systems by providing a bridge to the linked data cloud." SKOS is part of the Semantic Web technology stack. Like the Web Ontology Language (OWL), SKOS can be used to define vocabularies. But the two technologies were designed to meet different needs. SKOS is a simple language with just a few features, tuned for sharing and linking knowledge organization systems such as thesauri and classification schemes. OWL offers a general and powerful framework for knowledge representation, where additional "rigor" can afford additional benefits (for instance, business rule processing). To get started with SKOS, see the SKOS Primer.
  13. Priss, U.: Description logic and faceted knowledge representation (1999) 0.03 
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    Abstract
    The term "facet" was introduced into the field of library classification systems by Ranganathan in the 1930's [Ranganathan, 1962]. A facet is a viewpoint or aspect. In contrast to traditional classification systems, faceted systems are modular in that a domain is analyzed in terms of baseline facets which are then synthesized. In this paper, the term "facet" is used in a broader meaning. Facets can describe different aspects on the same level of abstraction or the same aspect on different levels of abstraction. The notion of facets is related to database views, multicontexts and conceptual scaling in formal concept analysis [Ganter and Wille, 1999], polymorphism in object-oriented design, aspect-oriented programming, views and contexts in description logic and semantic networks. This paper presents a definition of facets in terms of faceted knowledge representation that incorporates the traditional narrower notion of facets and potentially facilitates translation between different knowledge representation formalisms. A goal of this approach is a modular, machine-aided knowledge base design mechanism. A possible application is faceted thesaurus construction for information retrieval and data mining. Reasoning complexity depends on the size of the modules (facets). A more general analysis of complexity will be left for future research.
    Date
    22. 1.2016 17:30:31
  14. OWLED 2009; OWL: Experiences and Directions, Sixth International Workshop, Chantilly, Virginia, USA, 23-24 October 2009, Co-located with ISWC 2009. (2009) 0.02 
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    Abstract
    The W3C OWL Web Ontology Language has been a W3C recommendation since 2004, and specification of its successor OWL 2 is being finalised. OWL plays an important role in an increasing number and range of applications and as experience using the language grows, new ideas for further extending its reach continue to be proposed. The OWL: Experiences and Direction (OWLED) workshop series is a forum for practitioners in industry and academia, tool developers, and others interested in OWL to describe real and potential applications, to share experience, and to discuss requirements for language extensions and modifications. The workshop will bring users, implementors and researchers together to measure the state of need against the state of the art, and to set an agenda for research and deployment in order to incorporate OWL-based technologies into new applications. This year's 2009 OWLED workshop will be co-located with the Eighth International Semantic Web Conference (ISWC), and the Third International Conference on Web Reasoning and Rule Systems (RR2009). It will be held in Chantilly, VA, USA on October 23 - 24, 2009. The workshop will concentrate on issues related to the development and W3C standardization of OWL 2, and beyond, but other issues related to OWL are also of interest, particularly those related to the task forces set up at OWLED 2007. As usual, the workshop will try to encourage participants to work together and will give space for discussions on various topics, to be decided and published at some point in the future. We ask participants to have a look at these topics and the accepted submissions before the workshop, and to prepare single "slides" that can be presented during these discussions. There will also be formal presentation of submissions to the workshop.
    Content
    Long Papers * Suggestions for OWL 3, Pascal Hitzler. * BestMap: Context-Aware SKOS Vocabulary Mappings in OWL 2, Rinke Hoekstra. * Mechanisms for Importing Modules, Bijan Parsia, Ulrike Sattler and Thomas Schneider. * A Syntax for Rules in OWL 2, Birte Glimm, Matthew Horridge, Bijan Parsia and Peter Patel-Schneider. * PelletSpatial: A Hybrid RCC-8 and RDF/OWL Reasoning and Query Engine, Markus Stocker and Evren Sirin. * The OWL API: A Java API for Working with OWL 2 Ontologies, Matthew Horridge and Sean Bechhofer. * From Justifications to Proofs for Entailments in OWL, Matthew Horridge, Bijan Parsia and Ulrike Sattler. * A Solution for the Man-Man Problem in the Family History Knowledge Base, Dmitry Tsarkov, Ulrike Sattler and Robert Stevens. * Towards Integrity Constraints in OWL, Evren Sirin and Jiao Tao. * Processing OWL2 ontologies using Thea: An application of logic programming, Vangelis Vassiliadis, Jan Wielemaker and Chris Mungall. * Reasoning in Metamodeling Enabled Ontologies, Nophadol Jekjantuk, Gerd Gröner and Jeff Z. Pan.
    Short Papers * A Database Backend for OWL, Jörg Henss, Joachim Kleb and Stephan Grimm. * Unifying SysML and OWL, Henson Graves. * The OWLlink Protocol, Thorsten Liebig, Marko Luther and Olaf Noppens. * A Reasoning Broker Framework for OWL, Juergen Bock, Tuvshintur Tserendorj, Yongchun Xu, Jens Wissmann and Stephan Grimm. * Change Representation For OWL 2 Ontologies, Raul Palma, Peter Haase, Oscar Corcho and Asunción Gómez-Pérez. * Practical Aspects of Query Rewriting for OWL 2, Héctor Pérez-Urbina, Ian Horrocks and Boris Motik. * CSage: Use of a Configurable Semantically Attributed Graph Editor as Framework for Editing and Visualization, Lawrence Levin. * A Conformance Test Suite for the OWL 2 RL/RDF Rules Language and the OWL 2 RDF-Based Semantics, Michael Schneider and Kai Mainzer. * Improving the Data Quality of Relational Databases using OBDA and OWL 2 QL, Olivier Cure. * Temporal Classes and OWL, Natalya Keberle. * Using Ontologies for Medical Image Retrieval - An Experiment, Jasmin Opitz, Bijan Parsia and Ulrike Sattler. * Task Representation and Retrieval in an Ontology-Guided Modelling System, Yuan Ren, Jens Lemcke, Andreas Friesen, Tirdad Rahmani, Srdjan Zivkovic, Boris Gregorcic, Andreas Bartho, Yuting Zhao and Jeff Z. Pan. * A platform for reasoning with OWL-EL knowledge bases in a Peer-to-Peer environment, Alexander De Leon and Michel Dumontier. * Axiomé: a Tool for the Elicitation and Management of SWRL Rules, Saeed Hassanpour, Martin O'Connor and Amar Das. * SQWRL: A Query Language for OWL, Martin O'Connor and Amar Das. * Classifying ELH Ontologies In SQL Databases, Vincent Delaitre and Yevgeny Kazakov. * A Semantic Web Approach to Represent and Retrieve Information in a Corporate Memory, Ana B. Rios-Alvarado, R. Carolina Medina-Ramirez and Ricardo Marcelin-Jimenez. * Towards a Graphical Notation for OWL 2, Elisa Kendall, Roy Bell, Roger Burkhart, Mark Dutra and Evan Wallace.
    Demo/Position Papers * Conjunctive Query Answering in Distributed Ontology Systems for Ontologies with Large OWL ABoxes, Xueying Chen and Michel Dumontier. * Node-Link and Containment Methods in Ontology Visualization, Julia Dmitrieva and Fons J. Verbeek. * A JC3IEDM OWL-DL Ontology, Steven Wartik. * Semantically Enabled Temporal Reasoning in a Virtual Observatory, Patrick West, Eric Rozell, Stephan Zednik, Peter Fox and Deborah L. McGuinness. * Developing an Ontology from the Application Up, James Malone, Tomasz Adamusiak, Ele Holloway, Misha Kapushesky and Helen Parkinson.
  15. Blanco, E.; Cankaya, H.C.; Moldovan, D.: Composition of semantic relations : model and applications (2010) 0.02 
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    Abstract
    This paper presents a framework for combining semantic relations extracted from text to reveal even more semantics that otherwise would be missed. A set of 26 relations is introduced, with their arguments defined on an ontology of sorts. A semantic parser is used to extract these relations from noun phrases and verb argument structures. The method was successfully used in two applications: rapid customization of semantic relations to arbitrary domains and recognizing entailments.
    Source
    Proceedings of the 23rd International Conference on Computational Linguistics (COLING 2010), Poster Volume, Beijing, China. Ed.: Chu-Ren Huang and Dan Jurafsky
  16. Beppler, F.D.; Fonseca, F.T.; Pacheco, R.C.S.: Hermeneus: an architecture for an ontology-enabled information retrieval (2008) 0.02 
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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
  17. Lange, C.: Ontologies and languages for representing mathematical knowledge on the Semantic Web (2011) 0.02 
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    Abstract
    Mathematics is a ubiquitous foundation of science, technology, and engineering. Specific areas, such as numeric and symbolic computation or logics, enjoy considerable software support. Working mathematicians have recently started to adopt Web 2.0 environment, such as blogs and wikis, but these systems lack machine support for knowledge organization and reuse, and they are disconnected from tools such as computer algebra systems or interactive proof assistants.We argue that such scenarios will benefit from Semantic Web technology. Conversely, mathematics is still underrepresented on the Web of [Linked] Data. There are mathematics-related Linked Data, for example statistical government data or scientific publication databases, but their mathematical semantics has not yet been modeled. We argue that the services for the Web of Data will benefit from a deeper representation of mathematical knowledge. Mathematical knowledge comprises logical and functional structures - formulæ, statements, and theories -, a mixture of rigorous natural language and symbolic notation in documents, application-specific metadata, and discussions about conceptualizations, formalizations, proofs, and (counter-)examples. Our review of approaches to representing these structures covers ontologies for mathematical problems, proofs, interlinked scientific publications, scientific discourse, as well as mathematical metadata vocabularies and domain knowledge from pure and applied mathematics. Many fields of mathematics have not yet been implemented as proper Semantic Web ontologies; however, we show that MathML and OpenMath, the standard XML-based exchange languages for mathematical knowledge, can be fully integrated with RDF representations in order to contribute existing mathematical knowledge to theWeb of Data. We conclude with a roadmap for getting the mathematical Web of Data started: what datasets to publish, how to interlink them, and how to take advantage of these new connections.
  18. Priss, U.: Faceted knowledge representation (1999) 0.02 
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    Abstract
    Faceted Knowledge Representation provides a formalism for implementing knowledge systems. The basic notions of faceted knowledge representation are "unit", "relation", "facet" and "interpretation". Units are atomic elements and can be abstract elements or refer to external objects in an application. Relations are sequences or matrices of 0 and 1's (binary matrices). Facets are relational structures that combine units and relations. Each facet represents an aspect or viewpoint of a knowledge system. Interpretations are mappings that can be used to translate between different representations. This paper introduces the basic notions of faceted knowledge representation. The formalism is applied here to an abstract modeling of a faceted thesaurus as used in information retrieval.
    Date
    22. 1.2016 17:30:31
  19. Aitken, S.; Reid, S.: Evaluation of an ontology-based information retrieval tool (2000) 0.02 
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    Abstract
    This paper evaluates the use of an explicit domain ontology in an information retrieval tool. The evaluation compares the performance of ontology-enhanced retrieval with keyword retrieval for a fixed set of queries across several data sets. The robustness of the IR approach is assessed by comparing the performance of the tool on the original data set with that on previously unseen data.
    Content
    Beitrag für: Workshop on the Applications of Ontologies and Problem-Solving Methods, (eds) Gómez-Pérez, A., Benjamins, V.R., Guarino, N., and Uschold, M. European Conference on Artificial Intelligence 2000, Berlin.
  20. Tudhope, D.; Hodge, G.: Terminology registries (2007) 0.02 
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    Content
    Präsentation während der Veranstaltung "Networked Knowledge Organization Systems and Services: The 6th European Networked Knowledge Organization Systems (NKOS) Workshop, Workshop at the 11th ECDL Conference, Budapest, Hungary, September 21st 2007".
    Date
    26.12.2011 13:22:07

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