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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

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Abstract

Internet of Things (IoT) brings the third development wave of the global information industry which makes users, network and perception devices cooperate more closely. However, if IoT has security problems, it may cause a variety of damage and even threaten human lives and properties. To improve the abilities of monitoring, providing emergency response and predicting the development trend of IoT security, a new paradigm called network security situation awareness (NSSA) is proposed. However, it is limited by its ability to mine and evaluate security situation elements from multi-source heterogeneous network security information. To solve this problem, this paper proposes an IoT network security situation awareness model using situation reasoning method based on semantic ontology and user-defined rules. Ontology technology can provide a unified and formalized description to solve the problem of semantic heterogeneity in the IoT security domain. In this paper, four key sub-domains are proposed to reflect an IoT security situation: context, attack, vulnerability and network flow. Further, user-defined rules can compensate for the limited description ability of ontology, and hence can enhance the reasoning ability of our proposed ontology model. The examples in real IoT scenarios show that the ability of the network security situation awareness that adopts our situation reasoning method is more comprehensive and more powerful reasoning abilities than the traditional NSSA methods. [http://ieeexplore.ieee.org/abstract/document/7999187/]

Content

DOI 10.1109/ACCESS.2017.2734681.

Source

IEEE Access. 10.1109/ACCESS.2017.2734681, 5, (21046-21056) [http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7999187]

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Abstract

The success of the use of ontology-based systems depends on efficient and user-friendly methods of formulating queries against the ontology. We propose a method to query a class of ontologies, called facet ontologies ( fac-ontologies ), using a faceted human-oriented approach. A fac-ontology has two important features: (a) a hierarchical view of it can be defined as a nested facet over this ontology and the view can be used as a faceted interface to create queries and to explore the ontology; (b) the ontology can be converted into an ontological database , the ABox of which is stored in a database, and the faceted queries are evaluated against this database. We show that the proposed faceted interface makes it possible to formulate queries that are semantically equivalent to $${\mathcal {SROIQ}}^{Fac}$$ SROIQ Fac , a limited version of the $${\mathcal {SROIQ}}$$ SROIQ description logic. The TBox of a fac-ontology is divided into a set of rules defining intensional predicates and a set of constraint rules to be satisfied by the database. We identify a class of so-called reflexive weak cycles in a set of constraint rules and propose a method to deal with them in the chase procedure. The considerations are illustrated with solutions implemented in the DAFO system ( data access based on faceted queries over ontologies ).

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Abstract

The Resource Description Framework (RDF) is a general-purpose language for representing information in the Web. This specification describes how to use RDF to describe RDF vocabularies. This specification defines a vocabulary for this purpose and defines other built-in RDF vocabulary initially specified in the RDF Model and Syntax Specification.

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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.

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Abstract

The Resource Description Framework (RDF) is a language for representing information about resources in the World Wide Web. This Primer is designed to provide the reader with the basic knowledge required to effectively use RDF. It introduces the basic concepts of RDF and describes its XML syntax. It describes how to define RDF vocabularies using the RDF Vocabulary Description Language, and gives an overview of some deployed RDF applications. It also describes the content and purpose of other RDF specification documents.

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Abstract

The Resource Description Framework (RDF) is a framework for representing information in the Web. RDF Concepts and Abstract Syntax defines an abstract syntax on which RDF is based, and which serves to link its concrete syntax to its formal semantics. It also includes discussion of design goals, key concepts, datatyping, character normalization and handling of URI references.

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Content

Tutorial topics and outline 1. Tutorial Background Overview The Semantic Web, Linked Data, and the Resource Description Framework 2. Ontology Basics and RDFS Tutorial Semantic modeling, domain ontologies, and RDF Vocabulary Description Language (RDFS) concepts and terminology Examples: domain ontologies, models, and schemas Exercises 3. OWL Overview Tutorial Web Ontology Language (OWL): selected concepts and terminology Exercises

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Abstract

This is a specification of a precise semantics, and corresponding complete systems of inference rules, for the Resource Description Framework (RDF) and RDF Schema (RDFS).

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Abstract

Both Topic Maps and the W3C Semantic Web technologies are meta-level semantic maps describing relationships between information resources. Previous attempts at interoperability between XTM Topic Maps and RDF have proved problematic. The ISO's drafting of an explicit Topic Map Data Model [TMDM 05] combined with the advent of the W3C's XML and RDFbased Description Logic-equivalent Web Ontology Language [OWLDL 04] now provides the means for the construction of an unambiguous semantic model to represent Topic Maps, in a form that is equivalent to a Description Logic representation. This paper describes the construction of the proposed TMDM ISO Topic Map Standard in OWL DL (Description Logic equivalent) form. The construction is claimed to exactly match the features of the proposed TMDM. The intention is that the topic map constructs described herein, once officially published on the world-wide web, may be used by Topic Map authors to construct their Topic Maps in OWL DL. The advantage of OWL DL Topic Map construction over XTM, the existing XML-based DTD standard, is that OWL DL allows many constraints to be explicitly stated. OWL DL's suite of tools, although currently still somewhat immature, will provide the means for both querying and enforcing constraints. This goes a long way towards fulfilling the requirements for a Topic Map Query Language (TMQL) and Constraint Language (TMCL), which the Topic Map Community may choose to expend effort on extending. Additionally, OWL DL has a clearly defined formal semantics (Description Logic ref)

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Abstract

The Web Ontology Language OWL is a semantic markup language for publishing and sharing ontologies on the World Wide Web. OWL is developed as a vocabulary extension of RDF (the Resource Description Framework) and is derived from the DAML+OIL Web Ontology Language. This document contains a structured informal description of the full set of OWL language constructs and is meant to serve as a reference for OWL users who want to construct OWL ontologies.

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Abstract

The paper analysed here is a kind of position paper. In order to get a better under-standing of the reported work I used the retrieval interface of the thesaurus, the so-called NCI DTS Browser accessible via the Web3, and I perused the cited OWL file4 with numerous "Find" and "Find next" string searches. In addition the file was im-ported into Protégé 2000, Release 2.0, with OWL Plugin 1.0 and Racer Plugin 1.7.14. At the end of the paper's introduction the authors say: "In the following sections, this paper will describe the terminology development process at NCI, and the issues associated with converting a description logic based nomenclature to a semantically rich OWL ontology." While I will not deal with the first part, i.e. the terminology development process at NCI, I do not see the thesaurus as a description logic based nomenclature, or its cur-rent state and conversion already result in a "rich" OWL ontology. What does "rich" mean here? According to my view there is a great quantity of concepts and links but a very poor description logic structure which enables inferences. And what does the fol-lowing really mean, which is said a few lines previously: "Although editors have defined a number of named ontologic relations to support the description-logic based structure of the Thesaurus, additional relation-ships are considered for inclusion as required to support dependent applications."
According to my findings several relations available in the thesaurus query interface as "roles", are not used, i.e. there are not yet any assertions with them. And those which are used do not contribute to complete concept definitions of concepts which represent thesaurus main entries. In other words: The authors claim to already have a "description logic based nomenclature", where there is not yet one which deserves that title by being much more than a thesaurus with strict subsumption and additional inheritable semantic links. In the last section of the paper the authors say: "The most time consuming process in this conversion was making a careful analysis of the Thesaurus to understand the best way to translate it into OWL." "For other conversions, these same types of distinctions and decisions must be made. The expressive power of a proprietary encoding can vary widely from that in OWL or RDF. Understanding the original semantics and engineering a solution that most closely duplicates it is critical for creating a useful and accu-rate ontology." My question is: What decisions were made and are they exemplary, can they be rec-ommended as "the best way"? I raise strong doubts with respect to that, and I miss more profound discussions of the issues at stake. The following notes are dedicated to a critical description and assessment of the results of that conversion activity. They are written in a tutorial style more or less addressing students, but myself being a learner especially in the field of medical knowledge representation I do not speak "ex cathedra".

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Abstract

This document describes in brief how to express the content and structure of a classification scheme, and metadata about a classification scheme, in RDF using the SKOS vocabulary. RDF allows data to be linked to and/or merged with other RDF data by semantic web applications. The Semantic Web, which is based on the Resource Description Framework (RDF), provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. Publishing classifications schemes in SKOS will unify the great many of existing classification efforts in the framework of the Semantic Web.

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Abstract

The Resource Description Framework (RDF) is a general-purpose language for representing information in the Web. This document defines an XML syntax for RDF called RDF/XML in terms of Namespaces in XML, the XML Information Set and XML Base. The formal grammar for the syntax is annotated with actions generating triples of the RDF graph as defined in RDF Concepts and Abstract Syntax. The triples are written using the N-Triples RDF graph serializing format which enables more precise recording of the mapping in a machine processable form. The mappings are recorded as tests cases, gathered and published in RDF Test Cases.

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Abstract

This document describes in brief how to express the content and structure of a thesaurus, and metadata about a thesaurus, in RDF. Using RDF allows data to be linked to and/or merged with other RDF data by semantic web applications. The Semantic Web, which is based on the Resource Description Framework (RDF), provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries.

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Abstract

Terminology has evolved from static and prescriptive theories to dynamic and cognitive approaches. Thanks to these approaches, there have been significant advances in the design and elaboration of terminological resources. This has resulted in the creation of tools such as terminological knowledge bases, which are able to show how concepts are interrelated through different semantic or conceptual relations. Of these relations, hyponymy is the most relevant to terminology work because it deals with concept categorization and term hierarchies. This doctoral thesis presents an enhancement of the semantic structure of EcoLexicon, a terminological knowledge base on environmental science. The aim of this research was to improve the description, categorization, and representation of hyponymy in environmental terminology. Therefore, we created HypoLexicon, a new stand-alone module for EcoLexicon in the form of a hyponymy-based terminological resource. This resource contains twelve terminological entries from four specialized domains (Biology, Chemistry, Civil Engineering, and Geology), which consist of 309 concepts and 465 terms associated with those concepts. This research was mainly based on the theoretical premises of Frame-based Terminology. This theory was combined with Cognitive Linguistics, for conceptual description and representation; Corpus Linguistics, for the extraction and processing of linguistic and terminological information; and Ontology, related to hyponymy and relevant for concept categorization. HypoLexicon was constructed from the following materials: (i) the EcoLexicon English Corpus; (ii) other specialized terminological resources, including EcoLexicon; (iii) Sketch Engine; and (iv) Lexonomy. This thesis explains the methodologies applied for corpus extraction and compilation, corpus analysis, the creation of conceptual hierarchies, and the design of the terminological template. The results of the creation of HypoLexicon are discussed by highlighting the information in the hyponymy-based terminological entries: (i) parent concept (hypernym); (ii) child concepts (hyponyms, with various hyponymy levels); (iii) terminological definitions; (iv) conceptual categories; (v) hyponymy subtypes; and (vi) hyponymic contexts. Furthermore, the features and the navigation within HypoLexicon are described from the user interface and the admin interface. In conclusion, this doctoral thesis lays the groundwork for developing a terminological resource that includes definitional, relational, ontological and contextual information about specialized hypernyms and hyponyms. All of this information on specialized knowledge is simple to follow thanks to the hierarchical structure of the terminological template used in HypoLexicon. Therefore, not only does it enhance knowledge representation, but it also facilitates its acquisition.

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Abstract

This paper presents an overview of the work in progress at the W3C to produce a standard conversion of WordNet to the RDF/OWL representation language in use in the SemanticWeb community. Such a standard representation is useful to provide application developers a high-quality resource and to promote interoperability. Important requirements in this conversion process are that it should be complete and should stay close to WordNet's conceptual model. The paper explains the steps taken to produce the conversion and details design decisions such as the composition of the class hierarchy and properties, the addition of suitable OWL semantics and the chosen format of the URIs. Additional topics include a strategy to incorporate OWL and RDFS semantics in one schema such that both RDF(S) infrastructure and OWL infrastructure can interpret the information correctly, problems encountered in understanding the Prolog source files and the description of the two versions that are provided (Basic and Full) to accommodate different usages of WordNet.

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Abstract

This description of OWL, the Web Ontology Language being designed by the W3C Web Ontology Working Group, contains a high-level abstract syntax for both OWL DL and OWL Lite, sublanguages of OWL. A model-theoretic semantics is given to provide a formal meaning for OWL ontologies written in this abstract syntax. A model-theoretic semantics in the form of an extension to the RDF semantics is also given to provide a formal meaning for OWL ontologies as RDF graphs (OWL Full). A mapping from the abstract syntax to RDF graphs is given and the two model theories are shown to have the same consequences on OWL ontologies that can be written in the abstract syntax.

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Abstract

SKOS Core provides a model for expressing the basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, 'folksonomies', other types of controlled vocabulary, and also concept schemes embedded in glossaries and terminologies. The SKOS Core Vocabulary is an application of the Resource Description Framework (RDF), that can be used to express a concept scheme as an RDF graph. Using RDF allows data to be linked to and/or merged with other data, enabling data sources to be distributed across the web, but still be meaningfully composed and integrated. This document is a guide using the SKOS Core Vocabulary, for readers who already have a basic understanding of RDF concepts. This edition of the SKOS Core Guide [SKOS Core Guide] is a W3C Public Working Draft. It is the authoritative guide to recommended usage of the SKOS Core Vocabulary at the time of publication.

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Abstract

SKOS (Simple Knowledge Organisation System) provides a model for expressing the basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, folksonomies, and other types of controlled vocabulary. As an application of the Resource Description Framework (RDF) SKOS allows concepts to be documented, linked and merged with other data, while still being composed, integrated and published on the World Wide Web. This document is an implementors guide for those who would like to represent their concept scheme using SKOS. In basic SKOS, conceptual resources (concepts) can be identified using URIs, labelled with strings in one or more natural languages, documented with various types of notes, semantically related to each other in informal hierarchies and association networks, and aggregated into distinct concept schemes. In advanced SKOS, conceptual resources can be mapped to conceptual resources in other schemes and grouped into labelled or ordered collections. Concept labels can also be related to each other. Finally, the SKOS vocabulary itself can be extended to suit the needs of particular communities of practice.