RDF and XML: Towards a Unified Query Layer
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Basic Querying with SPARQL
Basic Querying with SPARQL Andrew Weidner Metadata Services Coordinator SPARQL SPARQL SPARQL SPARQL SPARQL Protocol SPARQL SPARQL Protocol And SPARQL SPARQL Protocol And RDF SPARQL SPARQL Protocol And RDF Query SPARQL SPARQL Protocol And RDF Query Language SPARQL SPARQL Protocol And RDF Query Language SPARQL Query SPARQL Query Update SPARQL Query Update - Insert triples SPARQL Query Update - Insert triples - Delete triples SPARQL Query Update - Insert triples - Delete triples - Create graphs SPARQL Query Update - Insert triples - Delete triples - Create graphs - Drop graphs Query RDF Triples Query RDF Triples Triple Store Query RDF Triples Triple Store Data Dump Query RDF Triples Triple Store Data Dump Subject – Predicate – Object Query Subject – Predicate – Object ?s ?p ?o Query Dog HasName Cocoa Subject – Predicate – Object ?s ?p ?o Query Cocoa HasPhoto ------- Subject – Predicate – Object ?s ?p ?o Query HasURL http://bit.ly/1GYVyIX Subject – Predicate – Object ?s ?p ?o Query ?s ?p ?o Query SELECT ?s ?p ?o Query SELECT * ?s ?p ?o Query SELECT * WHERE ?s ?p ?o Query SELECT * WHERE { ?s ?p ?o } Query select * WhErE { ?spiderman ?plays ?oboe } http://deathbattle.wikia.com/wiki/Spider-Man http://www.mmimports.com/wp-content/uploads/2014/04/used-oboe.jpg Query SELECT * WHERE { ?s ?p ?o } Query SELECT * WHERE { ?s ?p ?o } Query SELECT * WHERE { ?s ?p ?o } Query SELECT * WHERE { ?s ?p ?o } LIMIT 10 SELECT * WHERE { ?s ?p ?o } LIMIT 10 http://dbpedia.org/snorql SELECT * WHERE { ?s ?p ?o } LIMIT 10 http://dbpedia.org/snorql SELECT * WHERE { ?s -
Mapping Spatiotemporal Data to RDF: a SPARQL Endpoint for Brussels
International Journal of Geo-Information Article Mapping Spatiotemporal Data to RDF: A SPARQL Endpoint for Brussels Alejandro Vaisman 1, * and Kevin Chentout 2 1 Instituto Tecnológico de Buenos Aires, Buenos Aires 1424, Argentina 2 Sopra Banking Software, Avenue de Tevuren 226, B-1150 Brussels, Belgium * Correspondence: [email protected]; Tel.: +54-11-3457-4864 Received: 20 June 2019; Accepted: 7 August 2019; Published: 10 August 2019 Abstract: This paper describes how a platform for publishing and querying linked open data for the Brussels Capital region in Belgium is built. Data are provided as relational tables or XML documents and are mapped into the RDF data model using R2RML, a standard language that allows defining customized mappings from relational databases to RDF datasets. In this work, data are spatiotemporal in nature; therefore, R2RML must be adapted to allow producing spatiotemporal Linked Open Data.Data generated in this way are used to populate a SPARQL endpoint, where queries are submitted and the result can be displayed on a map. This endpoint is implemented using Strabon, a spatiotemporal RDF triple store built by extending the RDF store Sesame. The first part of the paper describes how R2RML is adapted to allow producing spatial RDF data and to support XML data sources. These techniques are then used to map data about cultural events and public transport in Brussels into RDF. Spatial data are stored in the form of stRDF triples, the format required by Strabon. In addition, the endpoint is enriched with external data obtained from the Linked Open Data Cloud, from sites like DBpedia, Geonames, and LinkedGeoData, to provide context for analysis. -
SPARQL with Xquery-Based Filtering?
SPARQL with XQuery-based Filtering? Takahiro Komamizu Nagoya University, Japan [email protected] Abstract. Linked Open Data (LOD) has been proliferated over vari- ous domains, however, there are still lots of open data in various format other than RDF, a standard data description framework in LOD. These open data can also be connected to entities in LOD when they are as- sociated with URIs. Document-centric XML data are such open data that are connected with entities in LOD as supplemental documents for these entities, and to convert these XML data into RDF requires various techniques such as information extraction, ontology design and ontology mapping with human prior knowledge. To utilize document-centric XML data linked from entities in LOD, in this paper, a SPARQL-based seam- less access method on RDF and XML data is proposed. In particular, an extension to SPARQL, XQueryFILTER, which enables XQuery as a filter in SPARQL is proposed. For efficient query processing of the combination of SPARQL and XQuery, a database theory-based query optimization is proposed. Real-world scenario-based experiments in this paper showcase that effectiveness of XQueryFILTER and efficiency of the optimization. 1 Introduction Open data movement is a worldwide movement that data are published online with FAIR principle1. Linked Open Data (LOD) [4] started by Sir Tim Berners- Lee is best aligned with this principle. In LOD, factual records are represented by a set of triples consisting of subject, predicate and object in the form of a stan- dardized representation framework, RDF (Resource Description Framework) [5]. Each element in RDF is represented by network-accessible identifier called URI (Uniform Resource Identifier). -
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. -
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 -
Semantic FAIR Data Web Me
SNOMED CT Research Webinar Today’ Presenter WELCOME! *We will begin shortly* Dr. Ronald Cornet UPCOMING WEBINARS: RESEARCH WEB SERIES CLINICAL WEB SERIES Save the Date! August TBA soon! August 19, 2020 Time: TBA https://www.snomed.org/news-and-events/events/web-series Dr Hyeoun-Ae Park Emeritus Dean & Professor Seoul National University Past President International Medical Informatics Association Research Reference Group Join our SNOMED Research Reference Group! Be notified of upcoming Research Webinars and other SNOMED CT research-related news. Email Suzy ([email protected]) to Join. SNOMED CT Research Webinar: SNOMED CT – OWL in a FAIR web of data Dr. Ronald Cornet SNOMED CT – OWL in a FAIR web of data Ronald Cornet Me SNOMED Use case CT Semantic FAIR data web Me • Associate professor at Amsterdam UMC, Amsterdam Public Health Research Institute, department of Medical Informatics • Research on knowledge representation; ontology auditing; SNOMED CT; reusable healthcare data; FAIR data Conflicts of Interest • 10+ years involvement with SNOMED International (Quality Assurance Committee, Technical Committee, Implementation SIG, Modeling Advisory Group) • Chair of the GO-FAIR Executive board • Funding from European Union (Horizon 2020) Me SNOMED Use case CT Semantic FAIR data web FAIR Guiding Principles https://go-fair.org/ FAIR Principles – concise • Findable • Metadata and data should be easy to find for both humans and computers • Accessible • The user needs to know how data can be accessed, possibly including authentication and authorization -
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. -
OWL 2 Web Ontology Language Quick Reference Guide
OWL 2 Web Ontology Language Quick Reference W3C Proposed Recommendation 22 September Guide 2009 OWL 2 Web Ontology Language Quick Reference Guide W3C Proposed Recommendation 22 September 2009 This version: http://www.w3.org/TR/2009/PR-owl2-quick-reference-20090922/ Latest version: http://www.w3.org/TR/owl2-quick-reference/ Previous version: http://www.w3.org/TR/2009/WD-owl2-quick-reference-20090611/ (color-coded diff) Editors: Jie Bao, Rensselaer Polytechnic Institute Elisa F. Kendall, Sandpiper Software, Inc. Deborah L. McGuinness, Rensselaer Polytechnic Institute Peter F. Patel-Schneider, Bell Labs Research, Alcatel-Lucent Contributors: Li Ding, Rensselaer Polytechnic Institute Ankesh Khandelwal, Rensselaer Polytechnic Institute This document is also available in these non-normative formats: PDF version, Reference Card. 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 15 http://www.w3.org/TR/2009/PR-owl2-quick-reference-20090922/ OWL 2 Web Ontology Language Quick Reference W3C Proposed Recommendation 22 September Guide 2009 This document provides a non-normative quick reference guide to the OWL 2 language. -
Linked Data Overview and Usage in Social Networks
Linked Data Overview and Usage in Social Networks Gustavo G. Valdez Technische Universitat Berlin Email: project [email protected] Abstract—This paper intends to introduce the principles of Webpages, also possibly reference any Object or Concept (or Linked Data, show some possible uses in Social Networks, even relationships of concepts/objects). advantages and disadvantages of using it, aswell as presenting The second one combines the unique identification of the an example application of Linked Data to the field of social networks. first with a well known retrieval mechanism (HTTP), enabling this URIs to be looked up via the HTTP protocol. I. INTRODUCTION The third principle tackles the problem of using the same The web is a very good source of human-readable informa- document standards, in order to have scalability and interop- tion that has improved our daily life in several areas. By using erability. This is done by having a standard, the Resource De- rich text and hyperlinks, it made our access to information scription Framewok (RDF), which will be explained in section something more active rather than passive. But the web was III-A. This standards are very useful to provide resources that made for humans and not for machines, even though today are machine-readable and are identified by a URI. a lot of the acesses to the web are made by machines. This The fourth principle basically advocates that hyperlinks has lead to the search for adding structure, so that data is should be used not only to link webpages, but also to link more machine-readable. -
Semantic Description of Web Services
Semantic Description of Web Services Thabet Slimani CS Department, Taif University, P.O.Box 888, 21974, KSA Abstract syntaxes) and in terms of the paradigms proposed for The tasks of semantic web service (discovery, selection, employing these in practice. composition, and execution) are supposed to enable seamless interoperation between systems, whereby human intervention is This paper is dedicated to provide an overview of these kept at a minimum. In the field of Web service description approaches, expressing their classification in terms of research, the exploitation of descriptions of services through commonalities and differences. It provides an semantics is a better support for the life-cycle of Web services. understanding of the technical foundation on which they The large number of developed ontologies, languages of are built. These techniques are classified from a range of representations, and integrated frameworks supporting the research areas including Top-down, Bottom-up and Restful discovery, composition and invocation of services is a good Approaches. indicator that research in the field of Semantic Web Services (SWS) has been considerably active. We provide in this paper a This paper does also provide some grounding that could detailed classification of the approaches and solutions, indicating help the reader perform a more detailed analysis of the their core characteristics and objectives required and provide different approaches which relies on the required indicators for the interested reader to follow up further insights objectives. We provide a little detailed comparison and details about these solutions and related software. between some approaches because this would require Keywords: SWS, SWS description, top-down approaches, addressing them from the perspective of some tasks bottom-up approaches, RESTful services. -
A Visual Notation for the Integrated Representation of OWL Ontologies
A Visual Notation for the Integrated Representation of OWL Ontologies Stefan Negru1 and Steffen Lohmann2 1Faculty of Computer Science, Alexandru Ioan Cuza University, General Berthelot 16, 700483 Iasi, Romania 2Institute for Visualization and Interactive Systems (VIS), Universit¨atsstraße 38, 70569 Stuttgart, Germany [email protected], [email protected] Keywords: Ontology Visualization, Visual Notation, OWL, Semantic Web, Knowledge Visualization, Ontologies. Abstract: The paper presents a visual notation for the Web Ontology Language (OWL) providing an integrated view on the classes and individuals of ontologies. The classes are displayed as circles, with the size of each circle representing its connectivity in the ontology. The individuals are represented as sections in the circles so that it is immediately clear from the visualization how many individuals the classes contain. The notation can be used to visualize the property relations of either the classes (conceptual layer) or of selected individuals (integrated layer), while certain elements are always shown for a better understanding. It requires only a small number of graphical elements and the resulting visualizations are comparatively compact. Yet, the notation is comprehensive, as it defines graphical representations for all OWL elements that can be reasonably visualized. The applicability of the notation is illustrated by the example of the Friend of a Friend (FOAF) ontology. 1 INTRODUCTION reasoning. Even though it provides great means to de- scribe and integrate information on the Web, its text- The Web of Data has attracted large interest for both based representation is difficult to understand for av- data publishers and consumers in the last years. -
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.