Programming the Semantic Web - a Microformats Compatible GRDDL Implementation for Activerdf
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Privacy Protection for Smartphones: an Ontology-Based Firewall Johanne Vincent, Christine Porquet, Maroua Borsali, Harold Leboulanger
Privacy Protection for Smartphones: An Ontology-Based Firewall Johanne Vincent, Christine Porquet, Maroua Borsali, Harold Leboulanger To cite this version: Johanne Vincent, Christine Porquet, Maroua Borsali, Harold Leboulanger. Privacy Protection for Smartphones: An Ontology-Based Firewall. 5th Workshop on Information Security Theory and Prac- tices (WISTP), Jun 2011, Heraklion, Crete, Greece. pp.371-380, 10.1007/978-3-642-21040-2_27. hal-00801738 HAL Id: hal-00801738 https://hal.archives-ouvertes.fr/hal-00801738 Submitted on 18 Mar 2013 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. Distributed under a Creative Commons Attribution| 4.0 International License Privacy Protection for Smartphones: An Ontology-Based Firewall Johann Vincent, Christine Porquet, Maroua Borsali, and Harold Leboulanger GREYC Laboratory, ENSICAEN - CNRS University of Caen-Basse-Normandie, 14000 Caen, France {johann.vincent,christine.porquet}@greyc.ensicaen.fr, {maroua.borsali,harold.leboulanger}@ecole.ensicaen.fr Abstract. With the outbreak of applications for smartphones, attempts to collect personal data without their user’s consent are multiplying and the protection of users privacy has become a major issue. In this paper, an approach based on semantic web languages (OWL and SWRL) and tools (DL reasoners and ontology APIs) is described. -
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 -
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. -
Using Rule-Based Reasoning for RDF Validation
Using Rule-Based Reasoning for RDF Validation Dörthe Arndt, Ben De Meester, Anastasia Dimou, Ruben Verborgh, and Erik Mannens Ghent University - imec - IDLab Sint-Pietersnieuwstraat 41, B-9000 Ghent, Belgium [email protected] Abstract. The success of the Semantic Web highly depends on its in- gredients. If we want to fully realize the vision of a machine-readable Web, it is crucial that Linked Data are actually useful for machines con- suming them. On this background it is not surprising that (Linked) Data validation is an ongoing research topic in the community. However, most approaches so far either do not consider reasoning, and thereby miss the chance of detecting implicit constraint violations, or they base them- selves on a combination of dierent formalisms, eg Description Logics combined with SPARQL. In this paper, we propose using Rule-Based Web Logics for RDF validation focusing on the concepts needed to sup- port the most common validation constraints, such as Scoped Negation As Failure (SNAF), and the predicates dened in the Rule Interchange Format (RIF). We prove the feasibility of the approach by providing an implementation in Notation3 Logic. As such, we show that rule logic can cover both validation and reasoning if it is expressive enough. Keywords: N3, RDF Validation, Rule-Based Reasoning 1 Introduction The amount of publicly available Linked Open Data (LOD) sets is constantly growing1, however, the diversity of the data employed in applications is mostly very limited: only a handful of RDF data is used frequently [27]. One of the reasons for this is that the datasets' quality and consistency varies signicantly, ranging from expensively curated to relatively low quality data [33], and thus need to be validated carefully before use. -
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. -
Semantic Skin: from Flat Textual Content to Interconnected Repositories Of
Semantic Skin: from flat textual content to interconnected repositories of semantic data. Claudio Baldassarre ABSTRACT front-end web application. This application offers a faceted One approach to re-balancing the Digital Divide tends to view of the underlying \news-KB". The current blog site favor the production of informative content in flat formats, appearance is merely a stylistic choice, while a running in- which are easy to distribute and consume. At the same time stance is always backed by a SPARQL endpoint over the this approach forbids to deliver the core knowledge perti- \news-KB". The facets are typically rendered as menu ele- nent within the content; i.e. it increases the Knowledge ments5: some menus facet the entire \news-KB" (e.g., news Divide. In some international organizations1, informative Topics, or Provenance); while other menus facet only the content distribution to groups in Latin America happens by content currently visible to the users. The faceting mech- manually collecting text-based content, then disseminating anism is also applied tothe \news archive" as a time-based it via standard mailing lists, or databases copies sent out facet of the repository content. All the facets are popu- regularly. Our demo showcases the use of Semantic Skin lated with SPARQL queries over the \news-model" instances a technology that after semantifying the content submit- in the \news-KB". Each news item is then presented with ted in flat formats, provides access to the information via a its summary, title, publication date, and provenance (e.g., knowledge layer, which is, however, transparent to the end permalink). -
INPUT CONTRIBUTION Group Name:* MAS WG Title:* Semantic Web Best Practices
Semantic Web best practices INPUT CONTRIBUTION Group Name:* MAS WG Title:* Semantic Web best practices. Semantic Web Guidelines for domain knowledge interoperability to build the Semantic Web of Things Source:* Eurecom, Amelie Gyrard, Christian Bonnet Contact: Amelie Gyrard, [email protected], Christian Bonnet, [email protected] Date:* 2014-04-07 Abstract:* This contribution proposes to describe the semantic web best practices, semantic web tools, and existing domain ontologies for uses cases (smart home and health). Agenda Item:* Tbd Work item(s): MAS Document(s) Study of Existing Abstraction & Semantic Capability Enablement Impacted* Technologies for consideration by oneM2M. Intended purpose of Decision document:* Discussion Information Other <specify> Decision requested or This is an informative paper proposed by the French Eurecom institute as a recommendation:* guideline to MAS contributors on Semantic web best practices, as it was suggested during MAS#9.3 call. Amélie Gyrard is a new member in oneM2M (via ETSI PT1). oneM2M IPR STATEMENT Participation in, or attendance at, any activity of oneM2M, constitutes acceptance of and agreement to be bound by all provisions of IPR policy of the admitting Partner Type 1 and permission that all communications and statements, oral or written, or other information disclosed or presented, and any translation or derivative thereof, may without compensation, and to the extent such participant or attendee may legally and freely grant such copyright rights, be distributed, published, and posted on oneM2M’s web site, in whole or in part, on a non- exclusive basis by oneM2M or oneM2M Partners Type 1 or their licensees or assignees, or as oneM2M SC directs. -
Wiki Semantics Via Wiki Templating
Chapter XXXIV Wiki Semantics via Wiki Templating Angelo Di Iorio Department of Computer Science, University of Bologna, Italy Fabio Vitali Department of Computer Science, University of Bologna, Italy Stefano Zacchiroli Universitè Paris Diderot, PPS, UMR 7126, Paris, France ABSTRACT A foreseeable incarnation of Web 3.0 could inherit machine understandability from the Semantic Web, and collaborative editing from Web 2.0 applications. We review the research and development trends which are getting today Web nearer to such an incarnation. We present semantic wikis, microformats, and the so-called “lowercase semantic web”: they are the main approaches at closing the technological gap between content authors and Semantic Web technologies. We discuss a too often neglected aspect of the associated technologies, namely how much they adhere to the wiki philosophy of open editing: is there an intrinsic incompatibility between semantic rich content and unconstrained editing? We argue that the answer to this question can be “no”, provided that a few yet relevant shortcomings of current Web technologies will be fixed soon. INTRODUCTION Web 3.0 can turn out to be many things, it is hard to state what will be the most relevant while still debating on what Web 2.0 [O’Reilly (2007)] has been. We postulate that a large slice of Web 3.0 will be about the synergies between Web 2.0 and the Semantic Web [Berners-Lee et al. (2001)], synergies that only very recently have begun to be discovered and exploited. We base our foresight on the observation that Web 2.0 and the Semantic Web are converging to a common point in their initially split evolution lines. -
Hidden Meaning
FEATURES Microdata and Microformats Kit Sen Chin, 123RF.com Chin, Sen Kit Working with microformats and microdata Hidden Meaning Programs aren’t as smart as humans when it comes to interpreting the meaning of web information. If you want to maximize your search rank, you might want to dress up your HTML documents with microformats and microdata. By Andreas Möller TML lets you mark up sections formats and microdata into your own source code for the website shown in of text as headings, body text, programs. Figure 1 – an HTML5 document with a hyperlinks, and other web page business card. The Heading text block is H elements. However, these defi- Microformats marked up with the element h1. The text nitions have nothing to do with the HTML was originally designed for hu- for the business card is surrounded by meaning of the data: Does the text refer mans to read, but with the explosive the div container element, and <br/> in- to a person, an organization, a product, growth of the web, programs such as troduces a line break. or an event? Microformats [1] and their search engines also process HTML data. It is easy for a human reader to see successor, microdata [2] make the mean- What do programs that read HTML data that the data shown in Figure 1 repre- ing a bit more clear by pointing to busi- typically find? Listing 1 shows the HTML sents a business card – even if the text is ness cards, product descriptions, offers, and event data in a machine-readable LISTING 1: HTML5 Document with Business Card way. -
Le Microformat Hproduct C'est Quoi ? Pourquoi Utiliser Le Microformat
Apprendre à utiliser les microformats : hProduct 2017-02-21 23:02:01 Nicolaseo Le microformat hProduct c’est quoi ? hProduct est un microformat approprié pour publier et embarquer les données de vos produits. C’est une sorte de méta tags qui permet de structurer vos données pour permettre aux robots des moteurs de recherche de mieux référencer votre contenu. Pourquoi utiliser le microformat hProduct Le microformat hProduct est basé sur un ensemble de champs très important pour communiquer avec les robots des moteurs de recherche comme Google. Utiliser les {meta- tags|richsnippets|microformats} (et tout ce qui peut permettre aux moteurs de recherche de mieux classer votre contenu) vous apportera plus de visibilité sur internet grâce à un meilleur référencement de votre site et de son contenu. Comment utiliser le microformat hProduct Le schéma hProduct se compose de ce qui suit : hproduct brand. optionnel. texte. peut aussi utiliser hCard pour les fabricants. category. optionnel. texte. peut aussi utiliser rel-tag. ré-utilisé à partir de hCard. price. optionnel. floating point number. peut utiliser un format de devise. description. optionnel. texte. peut aussi inclure un marquage HTML valide. réutilisé à partir de hReview. fn. requis. texte. nom du produit ou titre. réutilisé de hCard. photo. optionnel. élément image ou lien. réutilisé de hCard. url. optionnel. href. peut contenir rel-tag rel=’product’. ré-utilisé de hCard. review. optionnel. hReview, ou hReview-aggregate. listing. optionnel. hListing, ou hListing-aggregate. identifier. optionnel. type. requis. – exemples : model mpn upc isbn issn ean jan sn vin sku value. requis. – l’étiquette peut être implicite. Détails des champs du microformat hProduct Les noms de classe category, fn, photo, url sont réutilisés à partir de hCard. -
Using Rule-Based Reasoning for RDF Validation
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Ghent University Academic Bibliography Using Rule-Based Reasoning for RDF Validation Dörthe Arndt, Ben De Meester, Anastasia Dimou, Ruben Verborgh, and Erik Mannens Ghent University - imec - IDLab Sint-Pietersnieuwstraat 41, B-9000 Ghent, Belgium [email protected] Abstract. The success of the Semantic Web highly depends on its in- gredients. If we want to fully realize the vision of a machine-readable Web, it is crucial that Linked Data are actually useful for machines con- suming them. On this background it is not surprising that (Linked) Data validation is an ongoing research topic in the community. However, most approaches so far either do not consider reasoning, and thereby miss the chance of detecting implicit constraint violations, or they base them- selves on a combination of dierent formalisms, eg Description Logics combined with SPARQL. In this paper, we propose using Rule-Based Web Logics for RDF validation focusing on the concepts needed to sup- port the most common validation constraints, such as Scoped Negation As Failure (SNAF), and the predicates dened in the Rule Interchange Format (RIF). We prove the feasibility of the approach by providing an implementation in Notation3 Logic. As such, we show that rule logic can cover both validation and reasoning if it is expressive enough. Keywords: N3, RDF Validation, Rule-Based Reasoning 1 Introduction The amount of publicly available Linked Open Data (LOD) sets is constantly growing1, however, the diversity of the data employed in applications is mostly very limited: only a handful of RDF data is used frequently [27]. -
Rule Interchange Format: the Framework
Rule Interchange Format: The Framework Michael Kifer State University of New York at Stony Brook 1 Outline What is Rule Interchange Format (RIF)? RIF Framework Basic Logic Dialect (BLD) 2 What is RIF? A collection of dialects Rule system 1 (rigorously defined rule languages) semantics preserving Intended to facilitate rule mapping sharing and exchange RIF dialect X Dialect consistency Sharing of RIF machinery: semantics preserving XML syntax mapping Presentation syntax Semantics Rule system 2 3 Why Rule Exchange ? (and not The One True Rule Language ) Many different paradigms for rule languages Pure first-order Logic programming/deductive databases Production rules Reactive rules Many different features, syntaxes Different commercial interests Many egos, different preferences, ... 4 Why RIF Dialects ? (and not just one dialect ) Again: many paradigms for rule languages First-order rules Logic programming/deductive databases Reactive rules Production rules Many different semantics Classical first-order Stable-model semantics for negation Well-founded semantics for negation ... ... ... A carefully chosen set of interrelated dialects can serve the purpose of sharing and exchanging rules over the Web 5 Current State of RIF Dialects Need your feedback! Advanced LP . Advanced LP dialect 1 dialect N RIF-PRD (Production Rules Dialect) Basic LP dialect RIF-BLD (Basic Logic Dialect) - ready to go - under development - future plans RIF-Core 6 Why Is RIF Important? Best chance yet to bring rule languages into mainstream Can make