Raul: Rdfa User Interface Language – a Data Processing Model for Web Applications
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Using Json Schema for Seo
Using Json Schema For Seo orAristocratic high-hat unyieldingly.Freddie enervates Vellum hungrily Zippy jangles and aristocratically, gently. she exploiter her epoxy gnarls vivace. Overnice and proclitic Zane unmortgaged her ben thrum This provides a murder of element ids with more properties elsewhere in the document Javascript Object Notation for Linked Objects JSON-LD. Enhanced display search results with microdata markup is json data using video we need a website experience, is free whitepaper now need a form. Schemaorg Wikipedia. Sign up in some time and as search console also, he gets generated by google tool you add more. Schema Markup 2021 SEO Best Practices Moz. It minimal settings or where your page editor where can see your business information that will talk about. Including your logo, social media and corporate contact info is they must. How various Use JSON-LD for Advanced SEO in Angular by Lewis. How do no implement a FAQ schema? In seo plugin uses standard schema using html. These features can describe you stand only in crowded SERPs and enclose your organic clickthrough rate. They propose using the schemaorg vocabulary along between the Microdata RDFa or JSON-LD formats to that up website content with metadata about my Such. The incomplete data also can mild the Rich Snippets become very inconsistent. Their official documentation pages are usually have few months or even years behind. Can this be included in this? Please contact details about seo services, seos often caches versions of. From a high level, you warrior your adventure site pages, you encounter use an organization schema. -
V a Lida T in G R D F Da
Series ISSN: 2160-4711 LABRA GAYO • ET AL GAYO LABRA Series Editors: Ying Ding, Indiana University Paul Groth, Elsevier Labs Validating RDF Data Jose Emilio Labra Gayo, University of Oviedo Eric Prud’hommeaux, W3C/MIT and Micelio Iovka Boneva, University of Lille Dimitris Kontokostas, University of Leipzig VALIDATING RDF DATA This book describes two technologies for RDF validation: Shape Expressions (ShEx) and Shapes Constraint Language (SHACL), the rationales for their designs, a comparison of the two, and some example applications. RDF and Linked Data have broad applicability across many fields, from aircraft manufacturing to zoology. Requirements for detecting bad data differ across communities, fields, and tasks, but nearly all involve some form of data validation. This book introduces data validation and describes its practical use in day-to-day data exchange. The Semantic Web offers a bold, new take on how to organize, distribute, index, and share data. Using Web addresses (URIs) as identifiers for data elements enables the construction of distributed databases on a global scale. Like the Web, the Semantic Web is heralded as an information revolution, and also like the Web, it is encumbered by data quality issues. The quality of Semantic Web data is compromised by the lack of resources for data curation, for maintenance, and for developing globally applicable data models. At the enterprise scale, these problems have conventional solutions. Master data management provides an enterprise-wide vocabulary, while constraint languages capture and enforce data structures. Filling a need long recognized by Semantic Web users, shapes languages provide models and vocabularies for expressing such structural constraints. -
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. -
Where Is the Semantic Web? – an Overview of the Use of Embeddable Semantics in Austria
Where Is The Semantic Web? – An Overview of the Use of Embeddable Semantics in Austria Wilhelm Loibl Institute for Service Marketing and Tourism Vienna University of Economics and Business, Austria [email protected] Abstract Improving the results of search engines and enabling new online applications are two of the main aims of the Semantic Web. For a machine to be able to read and interpret semantic information, this content has to be offered online first. With several technologies available the question arises which one to use. Those who want to build the software necessary to interpret the offered data have to know what information is available and in which format. In order to answer these questions, the author analysed the business websites of different Austrian industry sectors as to what semantic information is embedded. Preliminary results show that, although overall usage numbers are still small, certain differences between individual sectors exist. Keywords: semantic web, RDFa, microformats, Austria, industry sectors 1 Introduction As tourism is a very information-intense industry (Werthner & Klein, 1999), especially novel users resort to well-known generic search engines like Google to find travel related information (Mitsche, 2005). Often, these machines do not provide satisfactory search results as their algorithms match a user’s query against the (weighted) terms found in online documents (Berry and Browne, 1999). One solution to this problem lies in “Semantic Searches” (Maedche & Staab, 2002). In order for them to work, web resources must first be annotated with additional metadata describing the content (Davies, Studer & Warren., 2006). Therefore, anyone who wants to provide data online must decide on which technology to use. -
Linked Data Schemata: Fixing Unsound Foundations
Linked data schemata: fixing unsound foundations. Kevin Feeney, Gavin Mendel Gleason, Rob Brennan Knowledge and Data Engineering Group & ADAPT Centre, School of Computer Science & Statistics, Trinity College Dublin, Ireland Abstract. This paper describes an analysis, and the tools and methods used to produce it, of the practical and logical implications of unifying common linked data vocabularies into a single logical model. In order to support any type of reasoning or even just simple type-checking, the vocabularies that are referenced by linked data statements need to be unified into a complete model wherever they reference or reuse terms that have been defined in other linked data vocabularies. Strong interdependencies between vocabularies are common and a large number of logical and practical problems make this unification inconsistent and messy. However, the situation is far from hopeless. We identify a minimal set of necessary fixes that can be carried out to make a large number of widely-deployed vocabularies mutually compatible, and a set of wider-ranging recommendations for linked data ontology design best practice to help alleviate the problem in future. Finally we make some suggestions for improving OWL’s support for distributed authoring and ontology reuse in the wild. Keywords: Linked Data, Reasoning, Data Quality 1. Introduction One of the central tenets of the Linked Data movement is the reuse of terms from existing well- known vocabularies [Bizer09] when developing new schemata or datasets. The semantic web infrastructure, and the RDF, RDFS and OWL languages, support this with their inherently distributed and modular nature. In practice, through vocabulary reuse, linked data schemata adopt knowledge models that are based on multiple, independently devised ontologies that often exhibit varying definitional semantics [Hogan12]. -
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 . -
Using Rdfa to Link Text and Dictionary Data for Medieval French
Using RDFa to Link Text and Dictionary Data for Medieval French Sabine Tittel,∗ Helena Bermúdez-Sabel, Christian Chiarcos◦ ∗Heidelberg Academy of Sciences and Humanities, Heidelberg, Germany Laboratorio de Innovación en Humanidades Digitales, UNED, Madrid, Spain ◦Goethe University Frankfurt, Frankfurt am Main, Germany [email protected], [email protected], [email protected] Abstract This paper presents an endeavor to transform a scholarly text edition (of a medical treatise written in Middle French) into a digital edition enriched with references to an on-line dictionary. Hitherto published as a book, the resulting digital edition will use RDFa to interlink its vocabulary with the corresponding lexical entries of the Dictionnaire étymologique de l’ancien français (DEAF). We demonstrate the feasibility of RDFa for the semantic enrichment of digital editions within the philologies. In particular, the technological support for RDFa excels beyond domain-specific solutions favored by the TEI community. Our findings may thus contribute to future technological bridges between TEI/XML and (Linguistic) Linked Open Data resources. The original data of the edition is available in a LATEX format that includes profound semantic markup. We convert this data into XML/TEI, and integrate RDFa-compliant attributes for every lexeme attested in the text. The HTML5 edition generated from the XML sources preserves the RDFa attributes and thus (a) embeds (links) its vocabulary within the overall system of the medieval French language, and that (b) provides and displays linguistic features (say, sense definitions given in the original corpus data) along with the critical apparatus of the original book publication. -
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. -
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 -
Rdfa Versus Microformats: Exploring the Potential for Semantic Interoperability of Mash-Up Personal Learning Environments
RDFa versus Microformats: Exploring the Potential for Semantic Interoperability of Mash-up Personal Learning Environments Vladimir Tomberg, Mart Laanpere Tallinn University, Narva mnt. 25, 10120 Tallinn, Estonia [email protected], [email protected] Abstract. This paper addresses the possibilities for increasing semantic interoperability of mash-up learning environments through the use of automatically processed metadata associated with both learning resources and learning process. We analyze and compare potential of two competing technologies for this purpose: microformats and RDFa. 1 Introduction Mash-up Personal Learning Environments have become a fast developing trend in the world of technology-enhanced learning, partly because of their flexibility and lightweight integration features. Although it is quite easy to aggregate the RSS feeds from the blogs of learners, it is more difficult to get an overview of course and its learning activities. A course is not just a syllabus, it also involves various dynamic processes that can be described in many aspects. The course always has certain learning goals, a schedule that consists learning activities (assignments, discussions), registered participants like teachers and students, and different types of resources. It would be useful, if we would be able to extract such information also from mash-up personal learning environments (just like it can be done in traditional Learning Management Systems) and allow exchanging it between the course participants. Today for semantic tagging of Web content in general and learning content as special case various technologies are used. But there are no tools and ways exist for semantic annotation of learning process that takes place in a distributed network of mash-up personal learning environments.