The Distributed Ontology, Modeling, and Specification Language™
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Semantics Developer's Guide
MarkLogic Server Semantic Graph Developer’s Guide 2 MarkLogic 10 May, 2019 Last Revised: 10.0-8, October, 2021 Copyright © 2021 MarkLogic Corporation. All rights reserved. MarkLogic Server MarkLogic 10—May, 2019 Semantic Graph Developer’s Guide—Page 2 MarkLogic Server Table of Contents Table of Contents Semantic Graph Developer’s Guide 1.0 Introduction to Semantic Graphs in MarkLogic ..........................................11 1.1 Terminology ..........................................................................................................12 1.2 Linked Open Data .................................................................................................13 1.3 RDF Implementation in MarkLogic .....................................................................14 1.3.1 Using RDF in MarkLogic .........................................................................15 1.3.1.1 Storing RDF Triples in MarkLogic ...........................................17 1.3.1.2 Querying Triples .......................................................................18 1.3.2 RDF Data Model .......................................................................................20 1.3.3 Blank Node Identifiers ..............................................................................21 1.3.4 RDF Datatypes ..........................................................................................21 1.3.5 IRIs and Prefixes .......................................................................................22 1.3.5.1 IRIs ............................................................................................22 -
XSAMS: XML Schema for Atomic, Molecular and Solid Data
XSAMS: XML Schema for Atomic, Molecular and Solid Data Version 0.1.1 Draft Document, January 14, 2011 This version: http://www-amdis.iaea.org/xsams/docu/v0.1.1.pdf Latest version: http://www-amdis.iaea.org/xsams/docu/ Previous versions: http://www-amdis.iaea.org/xsams/docu/v0.1.pdf Editors: M.L. Dubernet, D. Humbert, Yu. Ralchenko Authors: M.L. Dubernet, D. Humbert, Yu. Ralchenko, E. Roueff, D.R. Schultz, H.-K. Chung, B.J. Braams Contributors: N. Moreau, P. Loboda, S. Gagarin, R.E.H. Clark, M. Doronin, T. Marquart Abstract This document presents a proposal for an XML schema aimed at describing Atomic, Molec- ular and Particle Surface Interaction Data in distributed databases around the world. This general XML schema is a collaborative project between International Atomic Energy Agency (Austria), National Institute of Standards and Technology (USA), Universit´ePierre et Marie Curie (France), Oak Ridge National Laboratory (USA) and Paris Observatory (France). Status of this document It is a draft document and it may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use this document as reference materials or to cite them as other than “work in progress”. Acknowledgements The authors wish to acknowledge all colleagues and institutes, atomic and molecular database experts and physicists who have collaborated through different discussions to the building up of the concepts described in this document. Change Log Version 0.1: June 2009 Version 0.1.1: November 2010 Contents 1 Introduction 11 1.1 Motivation..................................... 11 1.2 Limitations..................................... 12 2 XSAMS structure, types and attributes 13 2.1 Atomic, Molecular and Particle Surface Interaction Data XML Schema Structure 13 2.2 Attributes .................................... -
Rdfa in XHTML: Syntax and Processing Rdfa in XHTML: Syntax and Processing
RDFa in XHTML: Syntax and Processing RDFa in XHTML: Syntax and Processing RDFa in XHTML: Syntax and Processing A collection of attributes and processing rules for extending XHTML to support RDF W3C Recommendation 14 October 2008 This version: http://www.w3.org/TR/2008/REC-rdfa-syntax-20081014 Latest version: http://www.w3.org/TR/rdfa-syntax Previous version: http://www.w3.org/TR/2008/PR-rdfa-syntax-20080904 Diff from previous version: rdfa-syntax-diff.html Editors: Ben Adida, Creative Commons [email protected] Mark Birbeck, webBackplane [email protected] Shane McCarron, Applied Testing and Technology, Inc. [email protected] Steven Pemberton, CWI Please refer to the errata for this document, which may include some normative corrections. This document is also available in these non-normative formats: PostScript version, PDF version, ZIP archive, and Gzip’d TAR archive. The English version of this specification is the only normative version. Non-normative translations may also be available. Copyright © 2007-2008 W3C® (MIT, ERCIM, Keio), All Rights Reserved. W3C liability, trademark and document use rules apply. Abstract The current Web is primarily made up of an enormous number of documents that have been created using HTML. These documents contain significant amounts of structured data, which is largely unavailable to tools and applications. When publishers can express this data more completely, and when tools can read it, a new world of user functionality becomes available, letting users transfer structured data between applications and web sites, and allowing browsing applications to improve the user experience: an event on a web page can be directly imported - 1 - How to Read this Document RDFa in XHTML: Syntax and Processing into a user’s desktop calendar; a license on a document can be detected so that users can be informed of their rights automatically; a photo’s creator, camera setting information, resolution, location and topic can be published as easily as the original photo itself, enabling structured search and sharing. -
Bi-Directional Transformation Between Normalized Systems Elements and Domain Ontologies in OWL
Bi-directional Transformation between Normalized Systems Elements and Domain Ontologies in OWL Marek Suchanek´ 1 a, Herwig Mannaert2, Peter Uhnak´ 3 b and Robert Pergl1 c 1Faculty of Information Technology, Czech Technical University in Prague, Thakurova´ 9, Prague, Czech Republic 2Normalized Systems Institute, University of Antwerp, Prinsstraat 13, Antwerp, Belgium 3NSX bvba, Wetenschapspark Universiteit Antwerpen, Galileilaan 15, 2845 Niel, Belgium Keywords: Ontology, Normalized Systems, Transformation, Model-driven Development, Ontology Engineering, Software Modelling. Abstract: Knowledge representation in OWL ontologies gained a lot of popularity with the development of Big Data, Artificial Intelligence, Semantic Web, and Linked Open Data. OWL ontologies are very versatile, and there are many tools for analysis, design, documentation, and mapping. They can capture concepts and categories, their properties and relations. Normalized Systems (NS) provide a way of code generation from a model of so-called NS Elements resulting in an information system with proven evolvability. The model used in NS contains domain-specific knowledge that can be represented in an OWL ontology. This work clarifies the potential advantages of having OWL representation of the NS model, discusses the design of a bi-directional transformation between NS models and domain ontologies in OWL, and describes its implementation. It shows how the resulting ontology enables further work on the analytical level and leverages the system design. Moreover, due to the fact that NS metamodel is metacircular, the transformation can generate ontology of NS metamodel itself. It is expected that the results of this work will help with the design of larger real-world applications as well as the metamodel and that the transformation tool will be further extended with additional features which we proposed. -
Rdf Repository Replacing Relational Database
RDF REPOSITORY REPLACING RELATIONAL DATABASE 1B.Srinivasa Rao, 2Dr.G.Appa Rao 1,2Department of CSE, GITAM University Email:[email protected],[email protected] Abstract-- This study is to propose a flexible enable it. One such technology is RDF (Resource information storage mechanism based on the Description Framework)[2]. RDF is a directed, principles of Semantic Web that enables labelled graph for representing information in the information to be searched rather than queried. Web. This can be perceived as a repository In this study, a prototype is developed where without any predefined structure the focus is on the information rather than the The information stored in the traditional structure. Here information is stored in a RDBMS’s requires structure to be defined structure that is constructed on the fly. Entities upfront. On the contrary, information could be in the system are connected and form a graph, very complex to structure upfront despite the similar to the web of data in the Internet. This tremendous potential offered by the existing data is persisted in a peculiar way to optimize database systems. In the ever changing world, querying on this graph of data. All information another important characteristic of information relating to a subject is persisted closely so that in a system that impacts its structure is the reqeusting any information of a subject could be modification/enhancement to the system. This is handled in one call. Also, the information is a big concern with many software systems that maintained in triples so that the entire exist today and there is no tidy approach to deal relationship from subject to object via the with the problem. -
Data Models for Home Services
__________________________________________PROCEEDING OF THE 13TH CONFERENCE OF FRUCT ASSOCIATION Data Models for Home Services Vadym Kramar, Markku Korhonen, Yury Sergeev Oulu University of Applied Sciences, School of Engineering Raahe, Finland {vadym.kramar, markku.korhonen, yury.sergeev}@oamk.fi Abstract An ultimate penetration of communication technologies allowing web access has enriched a conception of smart homes with new paradigms of home services. Modern home services range far beyond such notions as Home Automation or Use of Internet. The services expose their ubiquitous nature by being integrated into smart environments, and provisioned through a variety of end-user devices. Computational intelligence require a use of knowledge technologies, and within a given domain, such requirement as a compliance with modern web architecture is essential. This is where Semantic Web technologies excel. A given work presents an overview of important terms, vocabularies, and data models that may be utilised in data and knowledge engineering with respect to home services. Index Terms: Context, Data engineering, Data models, Knowledge engineering, Semantic Web, Smart homes, Ubiquitous computing. I. INTRODUCTION In recent years, a use of Semantic Web technologies to build a giant information space has shown certain benefits. Rapid development of Web 3.0 and a use of its principle in web applications is the best evidence of such benefits. A traditional database design in still and will be widely used in web applications. One of the most important reason for that is a vast number of databases developed over years and used in a variety of applications varying from simple web services to enterprise portals. In accordance to Forrester Research though a growing number of document, or knowledge bases, such as NoSQL is not a hype anymore [1]. -
Robust Web Content Extraction Marek Kowalkiewicz Maria E
Robust Web Content Extraction Marek Kowalkiewicz Maria E. Orlowska Tomasz Kaczmarek Witold Abramowicz Department of Management Department of Information Department of Management Department of Management Information Systems Technology and Electrical Information Systems Information Systems The Poznan University of Engineering The Poznan University of The Poznan University of Economics The University of Economics Economics Al. Niepodleglosci 10 Queensland Al. Niepodleglosci 10 Al. Niepodleglosci 10 60-967 Poznan, Poland Brisbane, St. Lucia 60-967 Poznan, Poland 60-967 Poznan, Poland +48 (61) 8543631 QLD 4072, Australia +48 (61) 8543631 +48 (61) 8543381 +61 (7) 33652989 [email protected] [email protected] [email protected] [email protected] ABSTRACT There is a number of technologies to extract information from We present an empirical evaluation and comparison of two webpages. For a state of the art analysis, see previously content extraction methods in HTML: absolute XPath expressions mentioned paper [2] and an extensive study by Laender et al. [3]. and relative XPath expressions. We argue that the relative XPath Robustness of content extraction methods, with a focus on XPath, expressions, although not widely used, should be used in has been presented in a work by Abe and Hori [1]. The authors preference to absolute XPath expressions in extracting content proposed four content anchoring approaches and tested them on from human-created Web documents. Evaluation of robustness documents from four Web sites. The samples used in theory study covers four thousand queries executed on several hundred were too small to be statistically valid. However the authors make webpages. We show that in referencing parts of real world a significant step towards establishing an understanding of the dynamic HTML documents, relative XPath expressions are on applicability of content extraction methods in real world Web average significantly more robust than absolute XPath ones. -
Integrating Fuzzy Logic in Ontologies
INTEGRATING FUZZY LOGIC IN ONTOLOGIES Silvia Calegari and Davide Ciucci Dipartimento di Informatica, Sistemistica e Comunicazione, Universita` degli Studi di Milano Bicocca, via Bicocca degli Arcimboldi 8, 20126 Milano, Italy Keywords: Concept modifiers, fuzzy logics, fuzzy ontologies, membership modifiers, KAON, ontology editor. Abstract: Ontologies have proved to be very useful in sharing concepts across applications in an unambiguous way. Nowadays, in ontology-based applications information is often vague and imprecise. This is a well-known problem especially for semantics-based applications, such as e-commerce, knowledge management, web por- tals, etc. In computer-aided reasoning, the predominant paradigm to manage vague knowledge is fuzzy set theory. This paper presents an enrichment of classical computational ontologies with fuzzy logic to create fuzzy ontologies. So, it is a step towards facing the nuances of natural languages with ontologies. Our pro- posal is developed in the KAON ontology editor, that allows to handle ontology concepts in an high-level environment. 1 INTRODUCTION A possible solution to handle uncertain data and, hence, to tackle these problems, is to incorporate fuzzy logic into ontologies. The aim of fuzzy set An ontology is a formal conceptualization of a partic- theory (Klir and Yuan, 1995) introduced by L. A. ular domain of interest shared among heterogeneous Zadeh (Zadeh, 1965) is to describe vague concepts applications. It consists of entities, attributes, rela- through a generalized notion of set, according to tionships and axioms to provide a common under- which an object may belong to a certain degree (typ- standing of the real world (Lammari and Mtais, 2004; ically a real number from the interval [0,1]) to a set. -
Arxiv:1009.3391V3 [Cs.LO] 4 Nov 2010
Fuzzy Ontology Representation using OWL 2 I Fernando Bobilloa, Umberto Stracciab aDepartment of Computer Science and Systems Engineering, University of Zaragoza, Spain bIstituto di Scienza e Tecnologie dell'Informazione (ISTI - CNR), Pisa, Italy Abstract The need to deal with vague information in Semantic Web languages is rising in importance and, thus, calls for a standard way to represent such information. We may address this issue by either extending current Semantic Web languages to cope with vagueness, or by providing a procedure to represent such informa- tion within current standard languages and tools. In this work, we follow the latter approach, by identifying the syntactic differences that a fuzzy ontology language has to cope with, and by proposing a concrete methodology to rep- resent fuzzy ontologies using OWL 2 annotation properties. We also report on the prototypical implementations. Key words: Fuzzy OWL 2, Fuzzy Ontologies, Fuzzy Languages for the Semantic Web, Fuzzy Description Logics 1. Introduction Today, there is a growing interest in the development of knowledge representa- tion formalisms able to deal with uncertainty, which is a very common require- ment in real world applications. Despite the undisputed success of ontologies, classical ontology languages are not appropriate to deal with vagueness or impre- cision in the knowledge, which is inherent to most of the real world application domains [29]. Since fuzzy set theory and fuzzy logic [30] are suitable formalisms to handle these types of knowledge, fuzzy ontologies emerge as useful in several applica- arXiv:1009.3391v3 [cs.LO] 4 Nov 2010 tions, ranging from (multimedia) information retrieval to image interpretation, ontology mapping, matchmaking, decision making, or the Semantic Web [19]. -
Ontology Languages – a Review
International Journal of Computer Theory and Engineering, Vol.2, No.6, December, 2010 1793-8201 Ontology Languages – A Review V. Maniraj, Dr.R. Sivakumar 1) Logical Languages Abstract—Ontologies have been becoming a hot research • First order predicate logic topic for the application in artificial intelligence, semantic web, Software Engineering, Library Science and information • Rule based logic Architecture. Ontology is a formal representation of set of concepts within a domain and relationships between those • concepts. It is used to reason about the properties of that Description logic domain and may be used to define the domain. An ontology language is a formal language used to encode the ontologies. A 2) Frame based Languages number of research languages have been designed and released • Similar to relational databases during the past few years by the research community. They are both proprietary and standard based. In this paper a study has 3) Graph based Languages been reported on the different features and issues of these • languages. This paper also addresses the challenges for Semantic network research community in the further development of ontology languages. • Analogy with the web is rationale for the semantic web I. INTRODUCTION Ontology engineering (or ontology building) is a subfield II. BACKGROUND of knowledge engineering that studies the methods and CycL1 in computer science and artificial intelligence is an methodologies for building ontologies. It studies the ontology language used by Doug Lenat’s Cye artificial ontology development process, the ontology life cycle, the intelligence project. Ramanathan V. Guna was instrumental methods and methodologies for building ontologies, and the in the design of the language. -
Habilitation (Summary of Main Contributions to the Field and Some General Perspectives on Future Research) Ivan Varzinczak
Habilitation (Summary of main contributions to the field and some general perspectives on future research) Ivan Varzinczak To cite this version: Ivan Varzinczak. Habilitation (Summary of main contributions to the field and some general perspec- tives on future research). Artificial Intelligence [cs.AI]. Université d’Artois, 2019. tel-03048085 HAL Id: tel-03048085 https://tel.archives-ouvertes.fr/tel-03048085 Submitted on 9 Dec 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Habilitation Summary of main contributions to the field and some general perspectives on future research1 Ivan Varzinczak CRIL, CNRS UMR 8188 Université d’Artois, Lens, France [email protected] https://ijv.ovh “Habilitation à diriger des recherches” defended on 26 November 2019 at Université d’Artois before the following jury: • Franz Baader (TU Dresden, Germany) • Stéphane Demri (CNRS, France) • Hans van Ditmarsch (CNRS, France) • Sébastien Konieczny (CNRS, France) • Pierre Marquis (Université d’Artois, France) • Marie-Laure Mugnier (Université de Montpellier, France) • Odile Papini (Université Aix-Marseille, France) • Leon var der Torre (Université du Luxembourg, Luxembourg) 1For a more detailed description of my recent research, the reader is referred to the companion monograph titled Defeasible Description Logics, which is the main scientific document for this “Habil- itation à diriger des recherches”. -
CURIE Syntax 1.0 CURIE Syntax 1.0
CURIE Syntax 1.0 CURIE Syntax 1.0 CURIE Syntax 1.0 A syntax for expressing Compact URIs W3C Working Draft 26 November 2007 This version: http://www.w3.org/TR/2007/WD-curie-20071126 Latest version: http://www.w3.org/TR/curie Previous version: http://www.w3.org/TR/2007/WD-curie-20070307 Diff from previous version: curie-diff.html Editors: Mark Birbeck, x-port.net Ltd. Shane McCarron, Applied Testing and Technology, Inc. This document is also available in these non-normative formats: PostScript version, PDF version. The English version of this specification is the only normative version. Non-normative translations may also be available. Copyright © 2007 W3C® (MIT, ERCIM, Keio), All Rights Reserved. W3C liability, trademark and document use rules apply. Abstract The aim of this document is to outline a syntax for expressing URIs in a generic, abbreviated syntax. While it has been produced in conjunction with the HTML Working Group, it is not specifically targeted at use by XHTML Family Markup Languages. Note that the target audience for this document is Language designers, not the users of those Languages. Status of this Document This section describes the status of this document at the time of its publication. Other documents may supersede this document. A list of current W3C publications and the latest revision of this technical report can be found in the W3C technical reports index at http://www.w3.org/TR/. - 1 - Table of Contents CURIE Syntax 1.0 This document is an updated working draft based upon comments received since the last draft.