Linked Data Schemata: Fixing Unsound Foundations
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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 -
PDF Formats; the XHTML Version Has Active Links That You Can Follow
Semantic Web @ W3C: Activities, Recommendations and State of Adoption Athens, GA, USA, 2006-11-09 Ivan Herman, W3C Ivan Herman, W3C RDF(S), tools We have a solid specification since 2004: well defined (formal) semantics, clear RDF/XML syntax Lots of tools are available. Are listed on W3C’s wiki: RDF programming environment for 14+ languages, including C, C++, Python, Java, Javascript, Ruby, PHP,… (no Cobol or Ada yet ) 13+ Triple Stores, ie, database systems to store datasets 16+ general development tools (specialized editors, application builders, …) etc Ivan Herman, W3C RDF(S), tools (cont.) Note the large number of large corporations among the tool developers: Adobe, IBM, Software AG, Oracle, HP, Northrop Grumman, … …but the small companies and independent developers also play a major role! Some of the tools are Open Source, some are not; some are very mature, some are not : it is the usual picture of software tools, nothing special any more! Anybody can start developing RDF-based applications today Ivan Herman, W3C RDF(S), tools (cont.) There are lots of tutorials, overviews, or books around the wiki page on books lists 20+ (English) textbooks; 19+ proceedings for 2005 & 2006 alone… again, some of them good, some of them bad, just as with any other areas… Active developers’ communities Ivan Herman, W3C Large datasets are accumulating IngentaConnect bibliographic metadata storage: over 200 million triplets UniProt Protein Database: 262 million triplets RDF version of Wikipedia: more than 47 million triplets RDFS/OWL Representation -
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. -
Mapping Between Digital Identity Ontologies Through SISM
Mapping between Digital Identity Ontologies through SISM Matthew Rowe The OAK Group, Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Street, Sheffield S1 4DP, UK [email protected] Abstract. Various ontologies are available defining the semantics of dig- ital identity information. Due to the rise in use of lowercase semantics, such ontologies are now used to add metadata to digital identity informa- tion within web pages. However concepts exist in these ontologies which are related and must be mapped together in order to enhance machine- readability of identity information on the web. This paper presents the Social identity Schema Mapping (SISM) vocabulary which contains a set of mappings between related concepts in distinct digital identity ontolo- gies using OWL and SKOS mapping constructs. Key words: Semantic Web, Social Web, SKOS, OWL, FOAF, SIOC, PIMO, NCO, Microformats 1 Introduction The semantic web provides a web of machine-readable data. Ontologies form a vital component of the semantic web by providing conceptualisations of domains of knowledge which can then be used to provide a common understanding of some domain. A basic ontology contains a vocabulary of concepts and definitions of the relationships between those concepts. An agent reading a concept from an ontology can look up the concept and discover its properties and characteristics, therefore interpreting how it fits into that particular domain. Due to the great number of ontologies it is common for related concepts to be defined in separate ontologies, these concepts must be identified and mapped together. Web technologies such as Microformats, eRDF and RDFa have allowed web developers to encode lowercase semantics within XHTML pages. -
Enhancing JSON to RDF Data Conversion with Entity Type Recognition
Enhancing JSON to RDF Data Conversion with Entity Type Recognition Fellipe Freire, Crishane Freire and Damires Souza Academic Unit of Informatics, Federal Institute of Education, Science and Technology of Paraiba, João Pessoa, Brazil Keywords: RDF Data Conversion, Entity Type Recognition, Semi-Structured Data, JSON Documents, Semantics Usage. Abstract: Nowadays, many Web data sources and APIs make their data available on the Web in semi-structured formats such as JSON. However, JSON data cannot be directly used in the Web of data, where principles such as URIs and semantically named links are essential. Thus it is necessary to convert JSON data into RDF data. To this end, we have to consider semantics in order to provide data reference according to domain vocabularies. To help matters, we present an approach which identifies JSON metadata, aligns them with domain vocabulary terms and converts data into RDF. In addition, along with the data conversion process, we provide the identification of the semantically most appropriate entity types to the JSON objects. We present the definitions underlying our approach and results obtained with the evaluation. 1 INTRODUCTION principles of this work is using semantics provided by the knowledge domain of the data to enhance The Web has evolved into an interactive information their conversion to RDF data. To this end, we use network, allowing users and applications to share recommended open vocabularies which are data on a massive scale. To help matters, the Linked composed by a set of terms, i.e., classes and Data principles define a set of practices for properties useful to describe specific types of things publishing structured data on the Web aiming to (LOV Documentation, 2016). -
Building Linked Data for Both Humans and Machines∗
Building Linked Data For Both Humans and Machines∗ y z x Wolfgang Halb Yves Raimond Michael Hausenblas Institute of Information Centre for Digital Music Institute of Information Systems & Information London, UK Systems & Information Management Management Graz, Austria Graz, Austria ABSTRACT Existing linked datasets such as [3] are slanted towards ma- In this paper we describe our experience with building the chines as the consumer. Although there are exceptions to riese dataset, an interlinked, RDF-based version of the Eu- this machine-first approach (cf. [13]), we strongly believe rostat data, containing statistical data about the European that satisfying both humans and machines from a single Union. The riese dataset (http://riese.joanneum.at), aims source is a necessary path to follow. at serving roughly 3 billion RDF triples, along with mil- lions of high-quality interlinks. Our contribution is twofold: We subscribe to the view that every LOD dataset can be Firstly, we suggest using RDFa as the main deployment understood as a Semantic Web application. Every Semantic mechanism, hence serving both humans and machines to Web application in turn is a Web application in the sense effectively and efficiently explore and use the dataset. Sec- that it should support a certain task for a human user. With- ondly, we introduce a new way of enriching the dataset out offering a state-of-the-art Web user interface, potential with high-quality links: the User Contributed Interlinking, end-users are scared away. Hence a Semantic Web applica- a Wiki-style way of adding semantic links to data pages. tion needs to have a nice outfit, as well. -
OGC Testbed-14: Semantically Enabled Aviation Data Models Engineering Report
OGC Testbed-14 Semantically Enabled Aviation Data Models Engineering Report Table of Contents 1. Summary . 4 1.1. Requirements & Research Motivation . 4 1.2. Prior-After Comparison. 4 1.3. Recommendations for Future Work . 5 1.4. What does this ER mean for the Working Group and OGC in general . 6 1.5. Document contributor contact points . 6 1.6. Foreword . 6 2. References . 8 3. Terms and definitions . 9 3.1. Semantics . 9 3.2. Service Description. 9 3.3. Service-Oriented Architecture (SOA) . 9 3.4. Registry . 9 3.5. System Wide Information Management (SWIM) . 9 3.6. Taxonomy . 9 3.7. Web Service . 10 4. Abbreviated Terms . 11 5. Overview . 12 6. Review of Data Models . 13 6.1. Information Exchange Models . 13 6.1.1. Flight Information Exchange Model (FIXM). 13 6.1.2. Aeronautical Information Exchange (AIXM) Model. 13 6.1.3. Weather Information Exchange Model (WXXM) . 14 6.1.4. NASA Air Traffic Management (ATM) Model . 14 6.2. Service description models . 19 6.2.1. Service Description Conceptual Model (SDCM) . 19 6.2.2. Web Service Description Ontological Model (WSDOM). 23 6.2.3. SWIM Documentation Controlled Vocabulary (FAA) . 25 7. Semantic Enablement Approaches . 27 8. Metadata level semantic enablement . 33 8.1. Issues with existing metadata standards . 34 8.1.1. Identification of Resources. 34 8.1.2. Resolvable URI. 34 8.1.3. Multilingual Support . 35 8.1.4. External Resource Descriptions . 35 8.1.5. Controlled Vocabulary Management . 36 8.1.6. Keywords Types . 37 8.1.7. Keyword Labeling Inconsistencies . -
Linked Data Schemata: Fixing Unsound Foundations
Linked data schemata: fixing unsound foundations Editor(s): Amrapali Zaveri, Stanford University, USA; Dimitris Kontokostas, Universität Leipzig, Germany; Sebastian Hellmann, Universität Leipzig, Germany; Jürgen Umbrich, Wirtschaftsuniversität Wien, Austria Solicited review(s): Mathieu d’Aquin, The Open University, UK; Peter F. Patel-Schneider, Nuance Communications, USA; John McCrae, Insight Centre for Data Analytics, Ireland; One anonymous reviewer Kevin Chekov Feeney, Gavin Mendel Gleason, and Rob Brennan Knowledge and Data Engineering Group & ADAPT Centre, School of Computer Science & Statistics, Trinity College Dublin, Ireland Corresponding author’s e-mail: [email protected] Abstract. This paper describes our tools and method for an evaluation of the practical and logical implications of combining common linked data vocabularies into a single local logical model for the purpose of reasoning or performing quality evalua- tions. These vocabularies need to be unified to form a combined model because they reference or reuse terms from other linked data vocabularies and thus the definitions of those terms must be imported. We found that strong interdependencies between vocabularies are common and that a significant number of logical and practical problems make this model unification inconsistent. In addition to identifying problems, this paper suggests a set of recommendations for linked data ontology design best practice. Finally we make some suggestions for improving OWL’s support for distributed authoring and ontology reuse. Keywords: Linked Data, Reasoning, Data Quality 1. Introduction In order to validate any dataset which uses the adms:Asset term we must combine the adms ontolo- One of the central tenets of the linked data move- gy and the dcat ontology in order to ensure that ment is the reuse of terms from existing well-known dcat:Dataset is a valid class. -
OWL 2 Web Ontology Language XML Serialization W3C Proposed Recommendation 22 September 2009
OWL 2 Web Ontology Language XML Serialization W3C Proposed Recommendation 22 September 2009 OWL 2 Web Ontology Language XML Serialization W3C Proposed Recommendation 22 September 2009 This version: http://www.w3.org/TR/2009/PR-owl2-xml-serialization-20090922/ Latest version: http://www.w3.org/TR/owl2-xml-serialization/ Previous version: http://www.w3.org/TR/2009/CR-owl2-xml-serialization-20090611/ (color-coded diff) Editors: Boris Motik, Oxford University Computing Laboratory Bijan Parsia, University of Manchester Peter F. Patel-Schneider, Bell Labs Research, Alcatel-Lucent Contributors: (in alphabetical order) Sean Bechhofer, University of Manchester Bernardo Cuenca Grau, Oxford University Computing Laboratory Achille Fokoue, IBM Corporation Rinke Hoekstra, University of Amsterdam This document is also available in these non-normative formats: PDF version. Copyright © 2009 W3C® (MIT, ERCIM, Keio), All Rights Reserved. W3C liability, trademark and document use rules apply. Abstract The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. The OWL 2 Document Overview describes the overall state of OWL 2, and should be read before other OWL 2 documents. Page 1 of 35 http://www.w3.org/TR/2009/PR-owl2-xml-serialization-20090922/ OWL 2 Web Ontology Language XML Serialization W3C Proposed Recommendation 22 September 2009 This document specifies an XML serialization for OWL 2 that mirrors its structural specification. -
Slideshare.Net/Scorlosquet/Drupal-As-A-Semantic-Web-Platform
Linked Data Publishing with Drupal Joachim Neubert ZBW – German National Library of Economics Leibniz Information Centre for Economics SWIB13 Workshop Hamburg, Germany 25.11.2013 ZBW is member of the Leibniz Association My background • Scientific software developer at ZBW – German National Library for Economics, mainly concerned with Linked Open Data and knowledge organization systems and services • Published 20th Century Press Archives in 2010, with some 100,000 digitized newspaper articles in dossiers (http://zbw.eu/beta/p20, custom application written in Perl) • Published a repository of ZBW Labs projects recently – basicly project descriptions and a blog (http://zbw.eu/labs, Drupal based) Page 2 Workshop Agenda – Part 1 1) Drupal 7 as a Content Management System: Linked Data by Default Hands-on: Get familiar with Drupal and it‘s default RDF mappings 2) Using Drupal 7as a Framework for Content Management Hands-on: Create a custom content type and map it to RDF Page 3 Workshop Agenda – Part 2 Produce other RDF Serialization Formats: RDF/XML, Turtle, Ntriples, JSON-LD Create a SPARQL Endpoint from your Drupal Site Cool URIs Create Out-Links with Web Taxonomy Current limitations of RDF/LD support in Drupal 7 Outlook on Drupal 8 Page 4 Drupal as a CMS (Content Management System) ready for RDF and Linked Data Page 5 Why at all linked data enhanced publishing? • Differentiate the subjects of your web pages and their attributes • Thus, foster data reuse in 3rd party services and applications • Mashups • Search engines • Create meaningful -
XHTML+Rdfa 1.1 - Third Edition Table of Contents
XHTML+RDFa 1.1 - Third Edition Table of Contents XHTML+RDFa 1.1 - Third Edition Support for RDFa via XHTML Modularization W3C Recommendation 17 March 2015 This version: http://www.w3.org/TR/2015/REC-xhtml-rdfa-20150317/ Latest published version: http://www.w3.org/TR/xhtml-rdfa/ Implementation report: http://www.w3.org/2010/02/rdfa/wiki/CR-ImplementationReport Previous version: http://www.w3.org/TR/2014/PER-xhtml-rdfa-20141216/ Previous Recommendation: http://www.w3.org/TR/2013/REC-xhtml-rdfa-20130822/ Editor: Shane McCarron, Applied Testing and Technology, Inc., [email protected] Please check the errata for any errors or issues reported since publication. This document is also available in these non-normative formats: XHTML+RDFa, Diff from Previous Recommendation, Postscript version, and PDF version The English version of this specification is the only normative version. Non-normative translations may also be available. Copyright © 2007-2015 W3C® (MIT, ERCIM, Keio, Beihang). W3C liability, trademark and document use rules apply. Abstract RDFa Core 1.1 [RDFA-CORE [p.61] ] defines attributes and syntax for embedding semantic markup in Host Languages. This document defines one such Host Language. This language is a superset of XHTML 1.1 [XHTML11-2e [p.61] ], integrating the attributes as defined in RDFa Core 1.1. This document is intended for authors who want to create XHTML Family documents that embed rich semantic markup. - 1 - Status of This Document XHTML+RDFa 1.1 - Third Edition Status of This Document This section describes the status of this document at the time of its publication. -
State of the Semantic Web
State of the Semantic Web Ivan Herman, W3C Sunday, 18 May, 2008 (2) > So where are we with the Semantic Web? State of the Semantic Web, Ivan Herman (2) Copyright © 2008, W3C (3) > We have the basic technologies Stable specifications for the basics since 2004: RDF, OWL Work is being done to properly incorporate rules We have a standard for query since 2008: SPARQL We have some additional technologies to access/create RDF data: GRDDL, RDFa, POWDER, … Some fundamental vocabularies became pervasive (FOAF, Dublin Core,…) State of the Semantic Web, Ivan Herman (3) Copyright © 2008, W3C (4) > Lots of Tools (not an exhaustive list!) • Triple Stores • Middleware • RDFStore, AllegroGraph, Tucana • IODT, Open Anzo, DartGrid • RDF Gateway, Mulgara, SPASQL • Ontology Works, Ontoprise • Jena’s SDB, D2R Server, SOR • Profium Semantic Information Router • Virtuoso, Oracle11g • Software AG’s EII, Thetus Publisher, Asio, SDS • Sesame, OWLIM, Tallis Platform • … • … • Semantic Web Browsers • Reasoners • Disco, Tabulator, Zitgist, OpenLink Viewer • Pellet, RacerPro, KAON2, FaCT++ • … • Ontobroker, Ontotext • Development Tools SHER, Oracle 11g, AllegroGraph • • SemanticWorks, Protégé • … • Jena, Redland, RDFLib, RAP • Converters • Sesame, SWI-Prolog • flickurl, TopBraid Composer • TopBraid Composer, DOME • GRDDL, Triplr, jpeg2rdf • … • … • Semantic Wiki and CMS systems • Search Engines • Semantic Media Wiki, Platypus • Falcon, Sindice, Swoogle • Visual knowledge • … • Drupal 7 Inspired by “Enterprise Semantic Web in Practice”, Jeff Pollock, Oracle. See also