The XML and Semantic Web Worlds: Technologies, Interoperability and Integration
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A Hierarchical SVG Image Abstraction Layer for Medical Imaging
A Hierarchical SVG Image Abstraction Layer for Medical Imaging Edward Kim1, Xiaolei Huang1, Gang Tan1, L. Rodney Long2, Sameer Antani2 1Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA; 2Communications Engineering Branch, National Library of Medicine, Bethesda, MD ABSTRACT As medical imaging rapidly expands, there is an increasing need to structure and organize image data for efficient analysis, storage and retrieval. In response, a large fraction of research in the areas of content-based image retrieval (CBIR) and picture archiving and communication systems (PACS) has focused on structuring information to bridge the “semantic gap”, a disparity between machine and human image understanding. An additional consideration in medical images is the organization and integration of clinical diagnostic information. As a step towards bridging the semantic gap, we design and implement a hierarchical image abstraction layer using an XML based language, Scalable Vector Graphics (SVG). Our method encodes features from the raw image and clinical information into an extensible “layer” that can be stored in a SVG document and efficiently searched. Any feature extracted from the raw image including, color, texture, orientation, size, neighbor information, etc., can be combined in our abstraction with high level descriptions or classifications. And our representation can natively characterize an image in a hierarchical tree structure to support multiple levels of segmentation. Furthermore, being a world wide web consortium (W3C) standard, SVG is able to be displayed by most web browsers, interacted with by ECMAScript (standardized scripting language, e.g. JavaScript, JScript), and indexed and retrieved by XML databases and XQuery. Using these open source technologies enables straightforward integration into existing systems. -
Towards Ontology Based BPMN Implementation. Sophea Chhun, Néjib Moalla, Yacine Ouzrout
Towards ontology based BPMN Implementation. Sophea Chhun, Néjib Moalla, Yacine Ouzrout To cite this version: Sophea Chhun, Néjib Moalla, Yacine Ouzrout. Towards ontology based BPMN Implementation.. SKIMA, 6th Conference on Software Knowledge Information Management and Applications., Jan 2012, Chengdu, China. 8 p. hal-01551452 HAL Id: hal-01551452 https://hal.archives-ouvertes.fr/hal-01551452 Submitted on 6 Nov 2018 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. 1 Towards ontology based BPMN implementation CHHUN Sophea, MOALLA Néjib and OUZROUT Yacine University of Lumiere Lyon2, laboratory DISP, France Natural language is understandable by human and not machine. None technical persons can only use natural language to specify their business requirements. However, the current version of Business process management and notation (BPMN) tools do not allow business analysts to implement their business processes without having technical skills. BPMN tool is a tool that allows users to design and implement the business processes by connecting different business tasks and rules together. The tools do not provide automatic implementation of business tasks from users’ specifications in natural language (NL). Therefore, this research aims to propose a framework to automatically implement the business processes that are expressed in NL requirements. -
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). -
Ontologies and Semantic Web for the Internet of Things - a Survey
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/312113565 Ontologies and Semantic Web for the Internet of Things - a survey Conference Paper · October 2016 DOI: 10.1109/IECON.2016.7793744 CITATIONS READS 5 256 2 authors: Ioan Szilagyi Patrice Wira Université de Haute-Alsace Université de Haute-Alsace 10 PUBLICATIONS 17 CITATIONS 122 PUBLICATIONS 679 CITATIONS SEE PROFILE SEE PROFILE Some of the authors of this publication are also working on these related projects: Physics of Solar Cells and Systems View project Artificial intelligence for renewable power generation and management: Application to wind and photovoltaic systems View project All content following this page was uploaded by Patrice Wira on 08 January 2018. The user has requested enhancement of the downloaded file. Ontologies and Semantic Web for the Internet of Things – A Survey Ioan Szilagyi, Patrice Wira MIPS Laboratory, University of Haute-Alsace, Mulhouse, France {ioan.szilagyi; patrice.wira}@uha.fr Abstract—The reality of Internet of Things (IoT), with its one of the most important task in an IoT system [6]. Providing growing number of devices and their diversity is challenging interoperability among the things is “one of the most current approaches and technologies for a smarter integration of fundamental requirements to support object addressing, their data, applications and services. While the Web is seen as a tracking and discovery as well as information representation, convenient platform for integrating things, the Semantic Web can storage, and exchange” [4]. further improve its capacity to understand things’ data and facilitate their interoperability. In this paper we present an There is consensus that Semantic Technologies is the overview of some of the Semantic Web technologies used in IoT appropriate tool to address the diversity of Things [4], [7]–[9]. -
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. -
Bibliography of Erik Wilde
dretbiblio dretbiblio Erik Wilde's Bibliography References [1] AFIPS Fall Joint Computer Conference, San Francisco, California, December 1968. [2] Seventeenth IEEE Conference on Computer Communication Networks, Washington, D.C., 1978. [3] ACM SIGACT-SIGMOD Symposium on Principles of Database Systems, Los Angeles, Cal- ifornia, March 1982. ACM Press. [4] First Conference on Computer-Supported Cooperative Work, 1986. [5] 1987 ACM Conference on Hypertext, Chapel Hill, North Carolina, November 1987. ACM Press. [6] 18th IEEE International Symposium on Fault-Tolerant Computing, Tokyo, Japan, 1988. IEEE Computer Society Press. [7] Conference on Computer-Supported Cooperative Work, Portland, Oregon, 1988. ACM Press. [8] Conference on Office Information Systems, Palo Alto, California, March 1988. [9] 1989 ACM Conference on Hypertext, Pittsburgh, Pennsylvania, November 1989. ACM Press. [10] UNIX | The Legend Evolves. Summer 1990 UKUUG Conference, Buntingford, UK, 1990. UKUUG. [11] Fourth ACM Symposium on User Interface Software and Technology, Hilton Head, South Carolina, November 1991. [12] GLOBECOM'91 Conference, Phoenix, Arizona, 1991. IEEE Computer Society Press. [13] IEEE INFOCOM '91 Conference on Computer Communications, Bal Harbour, Florida, 1991. IEEE Computer Society Press. [14] IEEE International Conference on Communications, Denver, Colorado, June 1991. [15] International Workshop on CSCW, Berlin, Germany, April 1991. [16] Third ACM Conference on Hypertext, San Antonio, Texas, December 1991. ACM Press. [17] 11th Symposium on Reliable Distributed Systems, Houston, Texas, 1992. IEEE Computer Society Press. [18] 3rd Joint European Networking Conference, Innsbruck, Austria, May 1992. [19] Fourth ACM Conference on Hypertext, Milano, Italy, November 1992. ACM Press. [20] GLOBECOM'92 Conference, Orlando, Florida, December 1992. IEEE Computer Society Press. http://github.com/dret/biblio (August 29, 2018) 1 dretbiblio [21] IEEE INFOCOM '92 Conference on Computer Communications, Florence, Italy, 1992. -
RDF Query Languages Need Support for Graph Properties
RDF Query Languages Need Support for Graph Properties Renzo Angles1, Claudio Gutierrez1, and Jonathan Hayes1,2 1 Dept. of Computer Science, Universidad de Chile 2 Dept. of Computer Science, Technische Universit¨at Darmstadt, Germany {rangles,cgutierr,jhayes}@dcc.uchile.cl Abstract. This short paper discusses the need to include into RDF query languages the ability to directly query graph properties from RDF data. We study the support that current RDF query languages give to these features, to conclude that they are currently not supported. We propose a set of basic graph properties that should be added to RDF query languages and provide evidence for this view. 1 Introduction One of the main features of the Resource Description Framework (RDF) is its ability to interconnect information resources, resulting in a graph-like structure for which connectivity is a central notion [GLMB98]. As we will argue, basic concepts of graph theory such as degree, path, and diameter play an important role for applications that involve RDF querying. Considering the fact that the data model influences the set of operations that should be provided by a query language [HBEV04], it follows the need for graph operations support in RDF query languages. For example, the query “all relatives of degree 1 of Alice”, submitted to a genealogy database, amounts to retrieving the nodes adjacent to a resource. The query “are suspects A and B related?”, submitted to a police database, asks for any path connecting these resources in the (RDF) graph that is stored in this database. The query “what is the Erd˝osnumber of Alberto Mendelzon”, submitted to (a RDF version of) DBLP, asks simply for the length of the shortest path between the nodes representing Erd˝osand Mendelzon. -
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. -
SHACL Satisfiability and Containment
SHACL Satisfiability and Containment Paolo Pareti1 , George Konstantinidis1 , Fabio Mogavero2 , and Timothy J. Norman1 1 University of Southampton, Southampton, United Kingdom {pp1v17,g.konstantinidis,t.j.norman}@soton.ac.uk 2 Università degli Studi di Napoli Federico II, Napoli, Italy [email protected] Abstract. The Shapes Constraint Language (SHACL) is a recent W3C recom- mendation language for validating RDF data. Specifically, SHACL documents are collections of constraints that enforce particular shapes on an RDF graph. Previous work on the topic has provided theoretical and practical results for the validation problem, but did not consider the standard decision problems of satisfiability and containment, which are crucial for verifying the feasibility of the constraints and important for design and optimization purposes. In this paper, we undertake a thorough study of different features of non-recursive SHACL by providing a translation to a new first-order language, called SCL, that precisely captures the semantics of SHACL w.r.t. satisfiability and containment. We study the interaction of SHACL features in this logic and provide the detailed map of decidability and complexity results of the aforementioned decision problems for different SHACL sublanguages. Notably, we prove that both problems are undecidable for the full language, but we present decidable combinations of interesting features. 1 Introduction The Shapes Constraint Language (SHACL) has been recently introduced as a W3C recommendation language for the validation of RDF graphs, and it has already been adopted by mainstream tools and triplestores. A SHACL document is a collection of shapes which define particular constraints and specify which nodes in a graph should be validated against these constraints.