I an ARABIC SEMANTIC WEB MODEL a Thesis Submitted to Kent State University in Partial Fulfillment of the Requirements for the De

Total Page:16

File Type:pdf, Size:1020Kb

I an ARABIC SEMANTIC WEB MODEL a Thesis Submitted to Kent State University in Partial Fulfillment of the Requirements for the De AN ARABIC SEMANTIC WEB MODEL A thesis submitted to Kent State University in partial fulfillment of the requirements for the degree of Master of Science by Khalid Ayed B Alharthi August 2013 i Thesis written by by Khalid Ayed B Alharthi B.S., King Khalid University, 2008 M.S., Kent State University, 2013 Approved by Austin Melton ,Chair, Thesis Committee Cheng-Chang Lu , Members, Thesis Committee Angela Guercio Farid Fouad Accepted by Javed Khan , Chair, Department of Computer Science Raymond Craig , Dean, College of Arts and Sciences ii TABLE OF CONTENTS LIST OF FIGURES……….………………………………………………………....…viii LIST OF TABLES……………………………………………………………..……..…x DEDICATION……………………..………………………………………….…......…xiii ACKNOWLEDGMENTS…..…………………..…………...………………....………xiv CHAPTER 1 SEMANTIC WEB…………..……………………………………………1 1.1 What is the Semantic Web? ………..…..……………...………………………... 2 1.2 The Semantic Web Layers Approach…………………………………………….5 1.3 A Graph Database Model………………………………………………………...7 1.3.1 Hierarchical Database Model………….………………………………….7 1.3.2 The Relational Database Model…….…………………………………….8 1.3.3 The Graph Database Model………………………………………………9 1.3.3 The Graph Database Model………………………………………………9 1.3.3.1 The benefits of a Graph Data Model………...……………..…………..10 1.4. Identify Resources on The Web………………………………………………...13 1.4.1 Universal Resource Identifier (URI)…………………………………….13 1.4.2 Fragment Identifier………………………………………………………13 1.4.3 Relative URIs……………………………………………………………14 1.4.4 Internationalized Resource Identifier (IRI)……………………………..14 1.5 Dublin Core Metadata Element Set……………………………………...………14 1.6 The Core Components of Semantic Web…………………………………...….…17 iii 1.6.1.1 The Resource Description Framework (RDF)………………………..17 1.6.1.2 RDF Data Model………………………………………...……………20 1.6.1.3 RDF Literals , Blank Node, and Datatypes…………………………...22 1.6.1.4 RDF Vocabulary URI and Namespace………………………………..23 1.6.1.5 RDF Vocabulary………………………………………………………23 1.6.1.6 Notation-3, Turtle, and N-Triples………………….…………………..23 1.6.2.1 What Is Ontology?.................................................................................24 1.6.2.2 The Benefits of Ontology…………………………………………….25 1.6.2.3.1 RDF Schema (RDFS)……………………………………………….26 1.6.2.3.2 RDFS Terms………………………………………………………...27 1.6.2.4.1 OWL: Web Ontology Language…………………………………....28 1.6.2.4.2 The Sublanguages of OWL…………………………………….…..30 1.6.2.4.3 OWL Language Terms……………………………………………..31 1.6.2.5 SPARQL: Querying the Semantic web……………………………….33 1.7 Real-World Examples of Semantic Web……………………………………..…34 1.7.1 FOAF: Friend of a Friend……………………………………………….34 1.7.2 DBpedia…………………………………………………………………34 1.8 The Popular Frameworks for the Semantic Web Applications…………………35 1.8.1 Jena……………………………………………………………………...35 1.8.2 Protégé…………………………………………………………………..36 CHAPTER 2 Arabic Language………………………………………………………38 2.1 A History of Arabic Language……………………………………………….....38 iv 2.2 Arabic Basics Rules…………………………………………………………..…39 2.2.1 The Arabic Alphabet…………………………………………………..39 2.2.2 Supplementary Letters………………………………………………...41 2.2.3 Writing Arabic Letters………………………………………………...41 2.2.4 Arabic Vowels………………………………………………………...43 2.2.4.1 Short Vowels…………………………………………………..43 2.2.4.2 Long Vowels………………………………………………....44 2.2.4.3 Diphthongs…………………………………………………….45 2.2.5 Tashdīd…………………………………………………………………45 2.2.6 Tanwīn…………………………………………………………………..46 2.2.7 Types of Hamzah………………………………………………………..46 2.2.7.1 Permanent Hamzah………………………...……………………46 2.2.7.2 Connecting Hamzah………………………………………….….48 2.2.8 The Sun and Moon Letters………………………………………………49 2.2.9 Gender in Arabic…………………………………………..…………….50 2.2.10 Singular, Dual and Plural………………………………………...…….52 2.2.11 Arabic Sentence………………………………………………………..55 2.2.11.1 Nouns ……………………………………………………...…..55 2.2.11.2 The Verb……………………………………………………….56 2.2.11.3 Particles………………………………………………………..57 2.2.11.4 Basic Arabic Sentence Structure………………………………58 CHAPTER 3 Arabic Language and Semantic Web…………………………….……59 v 3.1 Arab Countries…………………………………………………………….....59 3.2 Arabic One of the Most Influential Languages………………………………60 3.3 The importance of Arabic language…………………………………………..63 3.4 Differences Between Arabic and English Languages………………………...64 3.5 Arabic Language and Semantic web Technologies…………………………..68 3.6 Abstract………………………………………………………………………..72 CHAPTER 4 An Arabic Semantic Web Model………………………….……...…74 4.1 An Arabic Core Metadata Initiative (ACMI)….………………………………76 4.2 An Arabic Semantic Web Model………………………………………………84 4. 2.1 Storing Arabic Data as Graph Database (RDF Triple)……………….84 4.2.1.1 Visualizing Arabic Sentences as Graph Database….……….88 4.2.1.2 Arabic RDF Triple……………………………………………90 4.2.2 Arabic RDF……………………………………………………………90 4.2.2.1 Abstract Model of Arabic RDF………..…………………….92 4.2.2.2 Arabic RDF Serialization: Arabic RDF/XML ……………..103 4.2.2.2.1 Arabic RDF Vocabulary Terms I………………….104 4.2.2.2.2 Arabic RDF Vocabulary Terms II…………………108 4.2.2.2.3 Arabic RDF Vocabulary Terms III…………..….…111 4.2.2.2.4 Arabic RDF Vocabulary Terms IV………………...112 4.2.2.2.5 Arabic RDF Vocabulary Terms V………………….114 4.2.2.2.6 Arabic RDF Vocabulary Terms VI…………………115 4.2.2.2.7 Using (ACMI) in RDF Documents…………….……117 vi 4.2.2.3 Benefits of Using Standard Arabic RDF Vocabulary ….......118 118..………………………………………(تعريف المفاهيم)Arabic Web Ontology 4.2.3 4.2.3.1 Arabic Web Ontology and its Benefits……………………….….119 4.2.3.2 Basic Notions of Arabic Web Ontology………………………....120 4.2.3.3 Arabic Web Ontology Language (AOWL) Vocabulary Terms….121 4.2.3.3.1 AOWL Vocabulary Terms I……………………..121 4.2.3.3.2 AOWL Vocabulary Terms II…………………….122 4.2.3.3.3 AOWL Vocabulary Terms III…………………...124 4.2.3.3.4 AOWL Vocabulary Terms IV……………………127 4.2.3.3.5 AOWL Vocabulary Terms V…………………….128 4.2.3.3.6 AOWL Vocabulary Terms VI……………………132 4.2.3.3.7 AOWL Vocabulary Terms VII………………......136 4.2.3.3.8 AOWL Vocabulary Terms VIII…….……………138 4.2.3.3.9 AOWL Vocabulary Terms IX……………………142 4.2.3.3.10 AOWL Vocabulary Terms X ………..………….145 4.2.3.3.11 AOWL Vocabulary Terms XI…………………..152 CHAPTER 5 Conclusion and Future Work………………………….……...….154 5.1 Conclusion………………………………………………………………154 5.2 Future Work and Recommendations……………………………………155 BIBLIOGRAPHY………………………………………………………………… 157 vii LIST OF FIGURES Figure 1.1. Generations of the web…………………..……………………………………2 Figure 1.2. Shows the layered approach of the semantic web……..…………………..….3 Figure 1.3. Illustrates the structure of the hierarchical database model……..…………….8 Figure 1.4. Illustrates the structure of the relational database model………….………….9 Figure 1.5. Shows the use of graph databases on social networks……………………..10 Figure 1.6. Shows an example of the graph database…………………………………...12 Figure 1.7. Shows the representation of statements……………………………………...19 Figure 1.8. Shows the RDF triple……………………………...………………………...22 Figure 1.9. Jena’s homepage site…………………………...……………………………36 Figure 1.10. Shows the homepage site of Protégé………...……………………………..37 Figure 3.1. Speakers of Arabic language……………………...………………………..60 Figure 3.2 Most influential language in the world……………………………….………61 Figure 3.3. The mount of people that speak a language………...……………………….62 Figure 3.4. Number of primary speakers………………………..……………………….63 Figure 3.5. Arabic script represents 8.9% of the world’s languages……...……………..64 Figure 3.6. The garbled appearance of Arabic characters when using the Ontoviz ...…..70 Figure 3.7 Beseiso’s framework of semantic web for an Arabic language………..…….71 Figure 4.1. Visualizes the relation of (Ahmed and Aisha are a couple) as graph…..…...86 Figure 4.2. Representing my address information as a graph………………….…….….88 Figure 4.3. Represents three Arabic nominal sentences as a graph………….…..….…..89 viii Figure 4.4. Represents four Arabic verbal sentences as graph………………….…….89 Figure 4.5. Shows the graph structure of an Arabic statement………………..……….93 Figure 4.6. Shows the graph representation of the statements in List 4.1……....……...94 Figure 4.7 Graph representation of List 4.6 and List 4.8……………………….……102 ix LIST OF TABLES Table 1.1. Expressing figure 1.7 as a collection of RDF triple…….….………………..21 Table 1.2 RDFS class terms……………………………………….……………………27 Table 1.3. RDFS class terms…………………………….……………………………....28 Table 2.1. The Arabic Alphabet……… …………………….…………………...………40 Table 2.2. Supplementary Letters…………………………..……………………………41 Table 2.3. Writing Arabic Letters…………………………..……………………………41 43...……………………………..……………………………..……… ا join ل .Table 2.4 Table 2.5. Short vowels…………………………………………………………………44 Table 2.6. Examples of long vowels……………………………………………………44 Table 2.7. Examples of diphthongs…………………………………………………..…45 Table 2.8. Examples of Tashdīd…………………………………………………...……45 Table 2.9. Examples of Tanwīn………………………………………………………….46 Table 2.10. Permanent hamzah at the beginning of the word……………………………47 Table 2.11. Permanent hamzah at the middle of the word………………..……………..48 Table 2.12. Permanent hamzah at the end of the word…………………………………..48 Table 2.13. Sun Letters………………………………………………………………….49 Table 2.14. Moon Letters………………………………………………………………..50 Table 2.15. Examples of masculine and feminine gender……………………...………..51 Table 2.16. Closed ‘ta’ at the end does not form feminine nouns of some masculine…..52 Table 2.17. Sound Masculine Plural……………………………………………………..53 x Table 2.18. Sound Feminine Plural………………………………………………………54 Table 2.19. Broken Plural…………………………………..……………………………54 Table 2.20. Example of Particles…………………………………..…………………….57 66...…………...….……(نوم )Table 3.1 Represents different derivations words of the word Table 3.2. Arabic represents the dual relationship ………………………..……………..68 Table 4.1. Attributes that specify the ACMI terms…………………..…………………..76
Recommended publications
  • 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
    [Show full text]
  • Binary RDF for Scalable Publishing, Exchanging and Consumption in the Web of Data
    WWW 2012 – PhD Symposium April 16–20, 2012, Lyon, France Binary RDF for Scalable Publishing, Exchanging and Consumption in the Web of Data Javier D. Fernández 1;2 Supervised by: Miguel A. Martínez Prieto 1 and Claudio Gutierrez 2 1 Department of Computer Science, University of Valladolid (Spain) 2 Department of Computer Science, University of Chile (Chile) [email protected] ABSTRACT era and hence they share a document-centric view, providing The Web of Data is increasingly producing large RDF data- human-focused syntaxes, disregarding large data. sets from diverse fields of knowledge, pushing the Web to In a typical scenario within the current state-of-the-art, a data-to-data cloud. However, traditional RDF represen- efficient interchange of RDF data is limited, at most, to com- tations were inspired by a document-centric view, which pressing the verbose plain data with universal compression results in verbose/redundant data, costly to exchange and algorithms. The resultant file has no logical structure and post-process. This article discusses an ongoing doctoral the- there is no agreed way to efficiently publish such data, i.e., sis addressing efficient formats for publication, exchange and to make them (publicly) available for diverse purposes and consumption of RDF on a large scale. First, a binary serial- users. In addition, the data are hardly usable at the time of ization format for RDF, called HDT, is proposed. Then, we consumption; the consumer has to decompress the file and, focus on compressed rich-functional structures which take then, to use an appropriate external tool (e.g.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • Rdfs:Frbr– Towards an Implementation Model for Library Catalogs Using Semantic Web Technology
    rdfs:frbr– Towards an Implementation Model for Library Catalogs Using Semantic Web Technology Stefan Gradmann SUMMARY. The paper sets out from a few basic observations (biblio- graphic information is still mostly part of the ‘hidden Web,’ library au- tomation methods still have a low WWW-transparency, and take-up of FRBR has been rather slow) and continues taking a closer look at Se- mantic Web technology components. This results in a proposal for im- plementing FRBR as RDF-Schema and of RDF-based library catalogues built on such an approach. The contribution concludes with a discussion of selected strategic benefits resulting from such an approach. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: <[email protected]> Web- site: <http://www.HaworthPress.com> © 2005 by The Haworth Press, Inc. All rights reserved.] Stefan Gradmann, PhD, is Head, Hamburg University “Virtual Campus Library” Unit, which is part of the computing center and has a mission of providing information management services to the university as a whole, including e-publication services and open access to electronic scientific information resources. Address correspondence to: Stefan Gradmann, Virtuelle Campusbibliothek Regionales Rechenzentrum der Universität Hamburg, Schlüterstrasse 70, D-20146 Hamburg, Germany (E-mail: [email protected]). [Haworth co-indexing entry note]: “rdfs:frbr–Towards an Implementation Model for Library Cata- logs Using Semantic Web Technology.” Gradmann, Stefan. Co-published simultaneously in Cataloging & Classification Quarterly (The Haworth Information Press, an imprint of The Haworth Press, Inc.) Vol. 39, No. 3/4, 2005, pp. 63-75; and: Functional Requirements for Bibliographic Records (FRBR): Hype or Cure-All? (ed: Patrick Le Boeuf) The Haworth Information Press, an imprint of The Haworth Press, Inc., 2005, pp.
    [Show full text]
  • RDF/XML: RDF Data on the Web
    Developing Ontologies • have an idea of the required concepts and relationships (ER, UML, ...), • generate a (draft) n3 or RDF/XML instance, • write a separate file for the metadata, • load it into Jena with activating a reasoner. • If the reasoner complains about an inconsistent ontology, check the metadata file alone. If this is consistent, and it complains only when also data is loaded: – it may be due to populating a class whose definition is inconsistent and that thus must be empty. – often it is due to wrong datatypes. Recall that datatype specification is not interpreted as a constraint (that is violated for a given value), but as additional knowledge. 220 Chapter 6 RDF/XML: RDF Data on the Web • An XML representation of RDF data for providing RDF data on the Web could be done straightforwardly as a “holds” relation mapped according to SQLX (see ⇒ next slide). • would be highly redundant and very different from an XML representation of the same data • search for a more similar way: leads to “striped XML/RDF” – data feels like XML: can be queried by XPath/Query and transformed by XSLT – can be parsed into an RDF graph. • usually: provide RDF/XML data to an agreed RDFS/OWL ontology. 221 A STRAIGHTFORWARD XML REPRESENTATION OF RDF DATA Note: this is not RDF/XML, but just some possible representation. • RDF data are triples, • their components are either URIs or literals (of XML Schema datatypes), • straightforward XML markup in SQLX style, • since N3 has a term structure, it is easy to find an XML markup. <my-n3:rdf-graph xmlns:my-n3="http://simple-silly-rdf-xml.de#"> <my-n3:triple> <my-n3:subject type="uri">foo://bar/persons/john</my-n3:subject> <my-n3:predicate type="uri">foo://bar/meta#name</my-n3:predicate> <my-n3:object type="http://www.w3.org/2001/XMLSchema#string">John</my-n3:object> </my-n3 triple> <my-n3:triple> ..
    [Show full text]
  • Exercise Sheet 1
    Semantic Web, SS 2017 1 Exercise Sheet 1 RDF, RDFS and Linked Data Submit your solutions until Friday, 12.5.2017, 23h00 by uploading them to ILIAS. Later submissions won't be considered. Every solution should contain the name(s), email adress(es) and registration number(s) of its (co-)editor(s). Read the slides for more submission guidelines. 1 Knowledge Representation (4pts) 1.1 Knowledge Representation Humans usually express their knowledge in natural language. Why aren't we using, e.g., English for knowledge representation and the semantic web? 1.2 Terminological vs Concrete Knowledge What is the role of terminological knowledge (e.g. Every company is an organization.), and what is the role of facts (e.g. Microsoft is an organization. Microsoft is headquartered in Redmond.) in a semantic web system? Hint: Imagine an RDF ontology that contains either only facts (describing factual knowledge: states of aairs) or constraints (describing terminological knowledge: relations between con- cepts). What could a semantic web system do with it? Semantic Web, SS 2017 2 2 RDF (10pts) RDF graphs consist of triples having a subject, a predicate and an object. Dierent syntactic notations can be used in order to serialize RDF graphs. By now you have seen the XML and the Turtle syntax of RDF. In this task we will use the Notation3 (N3) format described at http://www.w3.org/2000/10/swap/Primer. Look at the following N3 le: @prefix model: <http://example.com/model1/> . @prefix cdk: <http://example.com/chemistrydevelopmentkit/> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
    [Show full text]
  • DELIVERABLE D3.2 Survey of Data Models, Ontologies and Standards in the Wider Energy Efficient Buildings Domain
    Ref. Ares(2019)5483631 - 30/08/2019 Project Acronym: BIMERR Project Full Title: BIM-based holistic tools for Energy-driven Renovation of existing Residences Grant Agreement: 820621 Project Duration: 42 months DELIVERABLE D3.2 Survey of data models, ontologies and standards in the wider Energy Efficient Buildings domain Deliverable Status: Final File Name: D3.2. Survey of data models ontologies and standards v1.0.docx Due Date: 31/08/2019 (M8) Submission Date: 30/08/2019 (M8) Task Leader: UPM (T3.2) Dissemination level Public X Confidential, only for members of the Consortium (including the Commission Services) This project has received funding from the European Union’s Horizon 2020 Research and innovation programme under Grant Agreement n°820621 The BIMERR project consortium is composed of: Fraunhofer Gesellschaft Zur Foerderung Der Angewandten Forschung FIT Germany E.V. CERTH Ethniko Kentro Erevnas Kai Technologikis Anaptyxis Greece UPM Universidad Politecnica De Madrid Spain UBITECH Ubitech Limited Cyprus SUITE5 Suite5 Data Intelligence Solutions Limited Cyprus Hypertech (Chaipertek) Anonymos Viomichaniki Emporiki Etaireia HYPERTECH Greece Pliroforikis Kai Neon Technologion MERIT Merit Consulting House Sprl Belgium XYLEM Xylem Science And Technology Management Gmbh Austria GU Glassup Srl Italy Anonymos Etaireia Kataskevon Technikon Ergon, Emporikon CONKAT Greece Viomichanikonkai Nautiliakon Epicheiriseon Kon'kat BOC Boc Asset Management Gmbh Austria BX Budimex Sa Poland UOP University Of Peloponnese Greece EXE Exergy Ltd United Kingdom HWU Heriot-Watt University United Kingdom NT Novitech As Slovakia FER Ferrovial Agroman S.A Spain Disclaimer BIMERR project has received funding from the European Union’s Horizon 2020 Research and innovation programme under Grant Agreement n°820621.
    [Show full text]
  • Using Shape Expressions (Shex) to Share RDF Data Models and to Guide Curation with Rigorous Validation B Katherine Thornton1( ), Harold Solbrig2, Gregory S
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Repositorio Institucional de la Universidad de Oviedo Using Shape Expressions (ShEx) to Share RDF Data Models and to Guide Curation with Rigorous Validation B Katherine Thornton1( ), Harold Solbrig2, Gregory S. Stupp3, Jose Emilio Labra Gayo4, Daniel Mietchen5, Eric Prud’hommeaux6, and Andra Waagmeester7 1 Yale University, New Haven, CT, USA [email protected] 2 Johns Hopkins University, Baltimore, MD, USA [email protected] 3 The Scripps Research Institute, San Diego, CA, USA [email protected] 4 University of Oviedo, Oviedo, Spain [email protected] 5 Data Science Institute, University of Virginia, Charlottesville, VA, USA [email protected] 6 World Wide Web Consortium (W3C), MIT, Cambridge, MA, USA [email protected] 7 Micelio, Antwerpen, Belgium [email protected] Abstract. We discuss Shape Expressions (ShEx), a concise, formal, modeling and validation language for RDF structures. For instance, a Shape Expression could prescribe that subjects in a given RDF graph that fall into the shape “Paper” are expected to have a section called “Abstract”, and any ShEx implementation can confirm whether that is indeed the case for all such subjects within a given graph or subgraph. There are currently five actively maintained ShEx implementations. We discuss how we use the JavaScript, Scala and Python implementa- tions in RDF data validation workflows in distinct, applied contexts. We present examples of how ShEx can be used to model and validate data from two different sources, the domain-specific Fast Healthcare Interop- erability Resources (FHIR) and the domain-generic Wikidata knowledge base, which is the linked database built and maintained by the Wikimedia Foundation as a sister project to Wikipedia.
    [Show full text]
  • XML for Java Developers G22.3033-002 Course Roadmap
    XML for Java Developers G22.3033-002 Session 1 - Main Theme Markup Language Technologies (Part I) Dr. Jean-Claude Franchitti New York University Computer Science Department Courant Institute of Mathematical Sciences 1 Course Roadmap Consider the Spectrum of Applications Architectures Distributed vs. Decentralized Apps + Thick vs. Thin Clients J2EE for eCommerce vs. J2EE/Web Services, JXTA, etc. Learn Specific XML/Java “Patterns” Used for Data/Content Presentation, Data Exchange, and Application Configuration Cover XML/Java Technologies According to their Use in the Various Phases of the Application Development Lifecycle (i.e., Discovery, Design, Development, Deployment, Administration) e.g., Modeling, Configuration Management, Processing, Rendering, Querying, Secure Messaging, etc. Develop XML Applications as Assemblies of Reusable XML- Based Services (Applications of XML + Java Applications) 2 1 Agenda XML Generics Course Logistics, Structure and Objectives History of Meta-Markup Languages XML Applications: Markup Languages XML Information Modeling Applications XML-Based Architectures XML and Java XML Development Tools Summary Class Project Readings Assignment #1a 3 Part I Introduction 4 2 XML Generics XML means eXtensible Markup Language XML expresses the structure of information (i.e., document content) separately from its presentation XSL style sheets are used to convert documents to a presentation format that can be processed by a target presentation device (e.g., HTML in the case of legacy browsers) Need a
    [Show full text]
  • An Introduction to RDF
    An Introduction to RDF Knowledge Technologies 1 Manolis Koubarakis Acknowledgement • This presentation is based on the excellent RDF primer by the W3C available at http://www.w3.org/TR/rdf-primer/ and http://www.w3.org/2007/02/turtle/primer/ . • Much of the material in this presentation is verbatim from the above Web site. Knowledge Technologies 2 Manolis Koubarakis Presentation Outline • Basic concepts of RDF • Serialization of RDF graphs: XML/RDF and Turtle • Other Features of RDF (Containers, Collections and Reification). Knowledge Technologies 3 Manolis Koubarakis What is RDF? •TheResource Description Framework (RDF) is a data model for representing information (especially metadata) about resources in the Web. • RDF can also be used to represent information about things that can be identified on the Web, even when they cannot be directly retrieved on the Web (e.g., a book or a person). • RDF is intended for situations in which information about Web resources needs to be processed by applications, rather than being only displayed to people. Knowledge Technologies 4 Manolis Koubarakis Some History • RDF draws upon ideas from knowledge representation, artificial intelligence, and data management, including: – Semantic networks –Frames – Conceptual graphs – Logic-based knowledge representation – Relational databases • Shameless self-promotion : The closest to RDF, pre-Web knowledge representation language is Telos: John Mylopoulos, Alexander Borgida, Matthias Jarke, Manolis Koubarakis: Telos: Representing Knowledge About Information Systems. ACM Trans. Inf. Syst. 8(4): 325-362 (1990). Knowledge Technologies 5 Manolis Koubarakis The Semantic Web “Layer Cake” Knowledge Technologies 6 Manolis Koubarakis RDF Basics • RDF is based on the idea of identifying resources using Web identifiers and describing resources in terms of simple properties and property values.
    [Show full text]
  • On Blank Nodes
    On Blank Nodes Alejandro Mallea1, Marcelo Arenas1, Aidan Hogan2, and Axel Polleres2;3 1 Department of Computer Science, Pontificia Universidad Católica de Chile, Chile Email: {aemallea,marenas}@ing.puc.cl 2 Digital Enterprise Research Institute, National University of Ireland Galway, Ireland Email: {aidan.hogan,axel.polleres}@deri.org 3 Siemens AG Österreich, Siemensstrasse 90, 1210 Vienna, Austria Abstract. Blank nodes are defined in RDF as ‘existential variables’ in the same way that has been used before in mathematical logic. However, evidence suggests that actual usage of RDF does not follow this definition. In this paper we thor- oughly cover the issue of blank nodes, from incomplete information in database theory, over different treatments of blank nodes across the W3C stack of RDF- related standards, to empirical analysis of RDF data publicly available on the Web. We then summarize alternative approaches to the problem, weighing up advantages and disadvantages, also discussing proposals for Skolemization. 1 Introduction The Resource Description Framework (RDF) is a W3C standard for representing in- formation on the Web using a common data model [18]. Although adoption of RDF is growing (quite) fast [4, § 3], one of its core features—blank nodes—has been sometimes misunderstood, sometimes misinterpreted, and sometimes ignored by implementers, other standards, and the general Semantic Web community. This lack of consistency between the standard and its actual uses calls for attention. The standard semantics for blank nodes interprets them as existential variables, de- noting the existence of some unnamed resource. These semantics make even simple entailment checking intractable. RDF and RDFS entailment are based on simple entail- ment, and are also intractable due to blank nodes [14].
    [Show full text]