DOCSLIB.ORG

Creating Ontology-Based Metadata by Annotation for the Semantic Web

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Creating Ontology-Based Metadata by Annotation for the Semantic Web Zur Erlangung des akademischen Grades eines Doktors der Wirtschaftswissenschaften (Dr. rer. pol.) von der Fakult¨at f¨ur Wirtschaftswissenschaften der Universit¨at Fridericiana zu Karlsruhe genehmigte Dissertation. Creating Ontology-based Metadata by Annotation for the Semantic Web von Dipl.-Ing.(FH), Dipl.-Inf.wiss. Siegfried Handschuh Tag der m¨undlichen Pr¨ufung: 16. Februar 2005 Referent: Prof. Dr. Rudi Studer Korreferent: Prof. Dr. Christof Weinhardt To my family. Acknowledgements I would like to thank people that supported me during the process of researching and writing this thesis. First of all, I would like to express my gratitude to my advisor, Prof. Dr. Rudi Studer, for his support, patience, and encouragement throughout my PhD studies at the Institute AIFB at the University of Karlsruhe. I am also grateful to Prof. Dr. Christof Weinhardt on my dissertation committee, and to Prof. Dr. Andreas Oberweis, who served on the examination committee. My work very much profited from working with Prof. Dr. Steffen Staab. I learned a lot from him, he inspiried me with his ideas and he significantly improved my scientific skills, e.g. by teaching me how to successfully write papers. He and Prof. Dr. Gerd Stumme gave me invaluable advice on organizing research workshops. My thanks also goes to all my colleagues in Karlsruhe at the Institute AIFB, the FZI and Ontoprise GmbH for providing a very fruitful and stimulating working atmosphere. In particular to Philipp Cimiano, Nenad and Ljiljana Stojanovic, Sudhir Agarwal and Alexander M¨adche. I’m especially indebted to Dr. Stefan Decker, for taking me on board his Onto- Agents project and the DARPA DAML program, which funded my work on semantic annotation. Tanja Sollazzo, Guylaine Kepeden, Wolf Winkler, Mika Maier-Collin and Kai K¨uhn who wrote their diploma theses under my supervision, contributed to the annotation framework. Furthermore I would like to thank Leo Meyer and Matthias Braun for their implementation work. My gratitude goes to Dr. Simon Beck for improving my time management skills in the final stage of my thesis writing, and my sister-in-law, Caroline for proof- reading drafts of this thesis - any remaining errors are of course mine. I thank my friends Esther St¨aheli and Sven Ruby for their devotion and putting up with me over a number of years; and Jorge Gonzalez for his advice and Julien Tane for the lively discussions. My family, my parents Philomena and Karl receive my deepest gratitude and love for the many years of support and for always believing in me. Last, but not least, I would like to thank my wife Patricia for her patience, love and understanding and our adorable daughter Ella for being a part of our lives from now on. v Acknowledgements vi Contents Acknowledgements v I. Foundations 1 1. Introduction 3 1.1. Motivation & Problem Description . 3 1.2. ResearchQuestions.......................... 4 1.3. Approaches .............................. 5 1.4. Reader’sGuide ............................ 6 2. Metadata and Ontology Languages 9 2.1. Metadata ............................... 9 2.1.1. Metadata Standards . 11 2.1.2. Metalanguages . 11 2.2. XML.................................. 12 2.3. XML Pointer Language (XPointer) . 14 2.3.1. XPath Basics . 15 2.3.2. XPointer Standards . 16 2.3.3. Referencing to Text passages with XPointers . 17 2.4. RDFandRDFS ........................... 20 2.4.1. TheRDFDataModel . 20 2.4.2. RDFSchema ......................... 22 2.4.3. RDFSyntax ......................... 24 2.4.4. Notation3 .......................... 25 2.5. Ontologies............................... 27 2.5.1. Ontology Definition . 27 2.5.2. Classification ......................... 29 2.6. Ontology Languages . 30 3. Semantic Annotation for the Web 35 3.1. TheSemanticWeb .......................... 35 3.2. Infrastructure for the Semantic Web – The Information Foodchain 36 3.3. Processes for the Semantic Web – Knowledge Process and Know- ledgeMetaProcess.......................... 38 vii Contents 3.3.1. Knowledge Meta Process . 39 3.3.2. KnowledgeProcess. 39 3.4. Semantic Annotation . 40 3.4.1. Terminology ......................... 40 3.4.2. The Semantics of Semantic Annotation . 41 3.4.3. Layering of Annotation . 43 3.5. Summary ............................... 44 II. Metadata for the Semantic Web 45 4. Annotation and Authoring Framework 47 4.1. Introduction.............................. 47 4.2. CaseStudiesforCREAM . 48 4.2.1. KA2 Initiative and KA2 Portal . 49 4.2.2. TIME2Research Portal . 49 4.2.3. Authors’ Annotations of Paper Abstracts at ISWC . 50 4.3. RequirementsforCREAM. 51 4.4. DesignofCREAM .......................... 52 4.4.1. CREAMModules ...................... 52 4.4.2. Architecture of CREAM . 57 4.5. MetaOntology ............................ 57 4.5.1. Label ............................. 60 4.5.2. Default Pointing . 61 4.5.3. PropertyMode ........................ 62 4.5.4. Further Meta Ontology Descriptions . 63 4.6. ModesofInteraction . .. .. .. .. .. .. .. 64 4.6.1. Annotation by Typing . 65 4.6.2. Annotation by Markup . 65 4.6.3. Annotation by Authoring . 66 4.7. Conclusion .............................. 67 5. Semi-Automatic Annotation 69 5.1. InformationExtraction. 69 5.1.1. Process of ontology-based Information Extraction . 70 5.1.2. Amilcare ........................... 73 5.1.3. SynthesizingS-CREAM . 75 5.1.4. Discourse Representation (DR) . 78 5.1.5. Conclusion .......................... 81 5.2. TheSelf-AnnotatingWeb . 83 5.2.1. The Process of PANKOW . 84 5.2.2. Pattern-based Categorization of Candidate Proper Nouns 86 5.2.3. Integration into CREAM . 89 viii Contents 5.2.4. Conclusion .......................... 90 6. Deep Annotation 93 6.1. Introduction.............................. 93 6.2. Use Cases for Deep Annotation . 95 6.3. The Process of Deep Annotation . 96 6.4. Architecture.............................. 97 6.5. Server-Side Web Page Markup . 99 6.5.1. Requirements ......................... 99 6.5.2. Database Representation . 99 6.5.3. Query Representation . 100 6.5.4. Result Representation . 101 6.6. Annotation .............................. 102 6.6.1. Annotation Process . 102 6.6.2. Creating Generic Instances of Classes . 103 6.6.3. Creating Generic Attribute Instances . 104 6.6.4. Creating Generic Relationship Instances . 105 6.7. MappingandQuerying. 105 6.7.1. Investigating Mappings . 105 6.7.2. Querying the Database . 106 6.8. Conclusion .............................. 108 7. Application 111 7.1. Linguistic Annotation . 111 7.1.1. The Ontology-based linguistic annotation framework . 112 7.1.2. Annotating anaphoric relations . 114 7.1.3. CREAM and OntoMat . 117 7.1.4. Conclusion .......................... 119 7.2. ServiceAnnotation . 120 7.2.1. UseCase ........................... 120 7.2.2. Overview of the Complete Process of CREAM-Service . 124 7.2.3. Semantic Web Page Markup for Web Services . 126 7.2.4. Browsing and Deep Annotation . 127 7.2.5. Conclusion .......................... 132 III. Evaluation 135 8. Evaluation of Manual Annotation 137 8.1. Introduction.............................. 137 8.2. Evaluation Setting . 138 8.2.1. General Setting . 138 8.2.2. Semantic Annotation Categories . 138 ix Contents 8.3. Formal Definition of Evaluation Setting . 139 8.4. Evaluation Measures . 140 8.4.1. Perfect Agreement — Agreement Precision & Agreement Recall ............................. 140 8.4.2. Sliding Agreements . 141 8.5. Example of an Evaluation . 143 8.6. Cross-EvaluationResults. 144 8.6.1. Basic statistics . 144 8.6.2. Perfect Agreement: Agreement-Precision & Agreement- Recall ............................. 145 8.6.3. Sliding Agreement . 146 8.6.4. Overallresults . 147 8.7. Conclusion .............................. 148 9. Evaluation of Semi-Automatic Annotation 153 9.1. Introduction.............................. 153 9.2. Method ................................ 154 9.2.1. General Setting . 154 9.2.2. The Domain Ontology . 155 9.2.3. Training of the Annotation . 156 9.2.4. Experimental Design . 157 9.2.5. Application of a statistical test . 157 9.2.6. Testprocedure . 157 9.3. Results................................. 158 9.3.1. TimeMeasurement. 158 9.3.2. ResultsofGroupA. 162 9.3.3. ResultsofGroupB. 166 9.3.4. Statistical Results . 169 9.3.5. Summary ........................... 173 9.4. Discussion............................... 174 9.5. Conclusion .............................. 177 IV. Related Work & Conclusions 179 10.Comparison with Related Work 181 10.1. Related Work for the Basic Framework . 181 10.1.1. Knowledge Markup in the Semantic Web . 181 10.1.2. Comparison with Knowledge Acquisition Frameworks . 183 10.1.3. Comparison with Annotation Frameworks . 183 10.1.4. Comparison with Authoring Frameworks . 185 10.2. Related Work for the Extended Framework . 186 10.2.1. Related Work for Deep Annotation . 186 x Contents 10.2.2. Related Work for Pattern-based Annotation . 187 10.3. Related Work for Applications of CREAM . 189 10.3.1. Comparison with Service Annotation . 189 10.3.2. Comparison with Linguistic Annotation . 190 10.4. Related Work for Evaluation . 192 11.Conclusion and Future Work 195 11.1.Contributions .. .. .. .. .. .. .. .. 195 11.2. Insights into Semantic Annotation . 196 11.3.OpenQuestions. .. .. .. .. .. .. .. 197 11.4.FutureResearch . .. .. .. .. .. .. .. 198 11.5.Summary ............................... 199 V. Appendix 201 A. Metadata Standards 203 B. Glossary 205 Bibliography 209 xi Contents xii List of Figures 2.1. Indexingofpointsandnotes. 18 2.2. RDFstatement ............................ 21 2.3. RDFreification...........................
Load more

Recommended publications
  • A Data-Driven Framework for Assisting Geo-Ontology Engineering Using a Discrepancy Index
    University of California Santa Barbara A Data-Driven Framework for Assisting Geo-Ontology Engineering Using a Discrepancy Index A Thesis submitted in partial satisfaction of the requirements for the degree Master of Arts in Geography by Bo Yan Committee in charge: Professor Krzysztof Janowicz, Chair Professor Werner Kuhn Professor Emerita Helen Couclelis June 2016 The Thesis of Bo Yan is approved. Professor Werner Kuhn Professor Emerita Helen Couclelis Professor Krzysztof Janowicz, Committee Chair May 2016 A Data-Driven Framework for Assisting Geo-Ontology Engineering Using a Discrepancy Index Copyright c 2016 by Bo Yan iii Acknowledgements I would like to thank the members of my committee for their guidance and patience in the face of obstacles over the course of my research. I would like to thank my advisor, Krzysztof Janowicz, for his invaluable input on my work. Without his help and encour- agement, I would not have been able to find the light at the end of the tunnel during the last stage of the work. Because he provided insight that helped me think out of the box. There is no better advisor. I would like to thank Yingjie Hu who has offered me numer- ous feedback, suggestions and inspirations on my thesis topic. I would like to thank all my other intelligent colleagues in the STKO lab and the Geography Department { those who have moved on and started anew, those who are still in the quagmire, and those who have just begun { for their support and friendship. Last, but most importantly, I would like to thank my parents for their unconditional love.
    [Show full text]
  • A Survey of Top-Level Ontologies to Inform the Ontological Choices for a Foundation Data Model
    A survey of Top-Level Ontologies To inform the ontological choices for a Foundation Data Model Version 1 Contents 1 Introduction and Purpose 3 F.13 FrameNet 92 2 Approach and contents 4 F.14 GFO – General Formal Ontology 94 2.1 Collect candidate top-level ontologies 4 F.15 gist 95 2.2 Develop assessment framework 4 F.16 HQDM – High Quality Data Models 97 2.3 Assessment of candidate top-level ontologies F.17 IDEAS – International Defence Enterprise against the framework 5 Architecture Specification 99 2.4 Terminological note 5 F.18 IEC 62541 100 3 Assessment framework – development basis 6 F.19 IEC 63088 100 3.1 General ontological requirements 6 F.20 ISO 12006-3 101 3.2 Overarching ontological architecture F.21 ISO 15926-2 102 framework 8 F.22 KKO: KBpedia Knowledge Ontology 103 4 Ontological commitment overview 11 F.23 KR Ontology – Knowledge Representation 4.1 General choices 11 Ontology 105 4.2 Formal structure – horizontal and vertical 14 F.24 MarineTLO: A Top-Level 4.3 Universal commitments 33 Ontology for the Marine Domain 106 5 Assessment Framework Results 37 F. 25 MIMOSA CCOM – (Common Conceptual 5.1 General choices 37 Object Model) 108 5.2 Formal structure: vertical aspects 38 F.26 OWL – Web Ontology Language 110 5.3 Formal structure: horizontal aspects 42 F.27 ProtOn – PROTo ONtology 111 5.4 Universal commitments 44 F.28 Schema.org 112 6 Summary 46 F.29 SENSUS 113 Appendix A F.30 SKOS 113 Pathway requirements for a Foundation Data F.31 SUMO 115 Model 48 F.32 TMRM/TMDM – Topic Map Reference/Data Appendix B Models 116 ISO IEC 21838-1:2019
    [Show full text]
  • Annotea: an Open RDF Infrastructure for Shared Web Annotations
    Proceedings of the WWW 10th International Conference, Hong Kong, May 2001. Annotea: An Open RDF Infrastructure for Shared Web Annotations Jos´eKahan,1 Marja-Riitta Koivunen,2 Eric Prud’Hommeaux2 and Ralph R. Swick2 1 W3C INRIA Rhone-Alpes 2 W3C MIT Laboratory for Computer Science {kahan, marja, eric, swick}@w3.org Abstract. Annotea is a Web-based shared annotation system based on a general-purpose open RDF infrastructure, where annotations are modeled as a class of metadata.Annotations are viewed as statements made by an author about a Web doc- ument. Annotations are external to the documents and can be stored in one or more annotation servers.One of the goals of this project has been to re-use as much existing W3C technol- ogy as possible. We have reacheditmostlybycombining RDF with XPointer, XLink, and HTTP. We have also implemented an instance of our system using the Amaya editor/browser and ageneric RDF database, accessible through an Apache HTTP server. In this implementation, the merging of annotations with documents takes place within the client. The paper presents the overall design of Annotea and describes some of the issues we have faced and how we have solved them. 1Introduction One of the basic milestones in the road to a Semantic Web [22] is the as- sociation of metadata to content. Metadata allows the Web to describe properties about some given content, even if the medium of this content does not directly provide the necessary means to do so. For example, ametadata schema for digital photos [15] allows the Web to describe, among other properties, the camera model used to take a photo, shut- ter speed, date, and location.
    [Show full text]
  • 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].
    [Show full text]
  • Semantic Web Foundations for Representing, Reasoning, and Traversing Contextualized Knowledge Graphs
    Wright State University CORE Scholar Browse all Theses and Dissertations Theses and Dissertations 2017 Semantic Web Foundations for Representing, Reasoning, and Traversing Contextualized Knowledge Graphs Vinh Thi Kim Nguyen Wright State University Follow this and additional works at: https://corescholar.libraries.wright.edu/etd_all Part of the Computer Engineering Commons, and the Computer Sciences Commons Repository Citation Nguyen, Vinh Thi Kim, "Semantic Web Foundations for Representing, Reasoning, and Traversing Contextualized Knowledge Graphs" (2017). Browse all Theses and Dissertations. 1912. https://corescholar.libraries.wright.edu/etd_all/1912 This Dissertation is brought to you for free and open access by the Theses and Dissertations at CORE Scholar. It has been accepted for inclusion in Browse all Theses and Dissertations by an authorized administrator of CORE Scholar. For more information, please contact [email protected]. Semantic Web Foundations for Representing, Reasoning, and Traversing Contextualized Knowledge Graphs A dissertation submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy By VINH THI KIM NGUYEN B.E., Vietnam National University, 2007 2017 Wright State University WRIGHT STATE UNIVERSITY GRADUATE SCHOOL December 15, 2017 I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY Vinh Thi Kim Nguyen ENTITLED Semantic Web Foundations of Representing, Reasoning, and Traversing in Contextualized Knowledge Graphs BE ACCEPTED IN PARTIAL FUL- FILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Doctor of Philosophy. Amit Sheth, Ph.D. Dissertation Director Michael Raymer, Ph.D. Director, Computer Science and Engineering Ph.D. Program Barry Milligan, Ph.D. Interim Dean of the Graduate School Committee on Final Examination Amit Sheth, Ph.D.
    [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]
  • Studying Social Tagging and Folksonomy: a Review and Framework
    Studying Social Tagging and Folksonomy: A Review and Framework Item Type Journal Article (On-line/Unpaginated) Authors Trant, Jennifer Citation Studying Social Tagging and Folksonomy: A Review and Framework 2009-01, 10(1) Journal of Digital Information Journal Journal of Digital Information Download date 02/10/2021 03:25:18 Link to Item http://hdl.handle.net/10150/105375 Trant, Jennifer (2009) Studying Social Tagging and Folksonomy: A Review and Framework. Journal of Digital Information 10(1). Studying Social Tagging and Folksonomy: A Review and Framework J. Trant, University of Toronto / Archives & Museum Informatics 158 Lee Ave, Toronto, ON Canada M4E 2P3 jtrant [at] archimuse.com Abstract This paper reviews research into social tagging and folksonomy (as reflected in about 180 sources published through December 2007). Methods of researching the contribution of social tagging and folksonomy are described, and outstanding research questions are presented. This is a new area of research, where theoretical perspectives and relevant research methods are only now being defined. This paper provides a framework for the study of folksonomy, tagging and social tagging systems. Three broad approaches are identified, focusing first, on the folksonomy itself (and the role of tags in indexing and retrieval); secondly, on tagging (and the behaviour of users); and thirdly, on the nature of social tagging systems (as socio-technical frameworks). Keywords: Social tagging, folksonomy, tagging, literature review, research review 1. Introduction User-generated keywords – tags – have been suggested as a lightweight way of enhancing descriptions of on-line information resources, and improving their access through broader indexing. “Social Tagging” refers to the practice of publicly labeling or categorizing resources in a shared, on-line environment.
    [Show full text]
  • The Application of Semantic Web Technologies to Content Analysis in Sociology
    THEAPPLICATIONOFSEMANTICWEBTECHNOLOGIESTO CONTENTANALYSISINSOCIOLOGY MASTER THESIS tabea tietz Matrikelnummer: 749153 Faculty of Economics and Social Science University of Potsdam Erstgutachter: Alexander Knoth, M.A. Zweitgutachter: Prof. Dr. rer. nat. Harald Sack Potsdam, August 2018 Tabea Tietz: The Application of Semantic Web Technologies to Content Analysis in Soci- ology, , © August 2018 ABSTRACT In sociology, texts are understood as social phenomena and provide means to an- alyze social reality. Throughout the years, a broad range of techniques evolved to perform such analysis, qualitative and quantitative approaches as well as com- pletely manual analyses and computer-assisted methods. The development of the World Wide Web and social media as well as technical developments like optical character recognition and automated speech recognition contributed to the enor- mous increase of text available for analysis. This also led sociologists to rely more on computer-assisted approaches for their text analysis and included statistical Natural Language Processing (NLP) techniques. A variety of techniques, tools and use cases developed, which lack an overall uniform way of standardizing these approaches. Furthermore, this problem is coupled with a lack of standards for reporting studies with regards to text analysis in sociology. Semantic Web and Linked Data provide a variety of standards to represent information and knowl- edge. Numerous applications make use of these standards, including possibilities to publish data and to perform Named Entity Linking, a specific branch of NLP. This thesis attempts to discuss the question to which extend the standards and tools provided by the Semantic Web and Linked Data community may support computer-assisted text analysis in sociology. First, these said tools and standards will be briefly introduced and then applied to the use case of constitutional texts of the Netherlands from 1884 to 2016.
    [Show full text]
  • Instructions on the Annotation of Pdf Files
    P-annotatePDF-v11b INSTRUCTIONS ON THE ANNOTATION OF PDF FILES To view, print and annotate your chapter you will need Adobe Reader version 9 (or higher). This program is freely available for a whole series of platforms that include PC, Mac, and UNIX and can be downloaded from http://get.adobe.com/reader/. The exact system requirements are given at the Adobe site: http://www.adobe.com/products/reader/tech-specs.html. Note: if you opt to annotate the file with software other than Adobe Reader then please also highlight the appropriate place in the PDF file. PDF ANNOTATIONS Adobe Reader version 9 Adobe Reader version X and XI When you open the PDF file using Adobe Reader, the To make annotations in the PDF file, open the PDF file using Commenting tool bar should be displayed automatically; if Adobe Reader XI, click on ‘Comment’. not, click on ‘Tools’, select ‘Comment & Markup’, then click If this option is not available in your Adobe Reader menus on ‘Show Comment & Markup tool bar’ (or ‘Show then it is possible that your Adobe Acrobat version is lower Commenting bar’ on the Mac). If these options are not than XI or the PDF has not been prepared properly. available in your Adobe Reader menus then it is possible that your Adobe Acrobat version is lower than 9 or the PDF has not been prepared properly. This opens a task pane and, below that, a list of all (Mac) Comments in the text. PDF ANNOTATIONS (Adobe Reader version 9) The default for the Commenting tool bar is set to ‘off’ in version 9.
    [Show full text]
  • Browser Security Features
    Browser Security features Michael Sonntag Institute of Networks and Security Cookies: Securing them Attention: These are “requests” by the server setting the cookie Browsers will follow them, but applications not necessarily Secure/HTTPS-only: Do not send unencrypted This is an element of the Cookie header itself “Set-Cookie: “ …content, domain, expiration… “;Secure” Often the application contains an option to set this automatically HTTP-only: No access by JavaScript This is an element of the Cookie header itself “Set-Cookie: “ …content, domain, expiration… “;HttpOnly” Host-only: Do not set the “Domain” attribute Not set: Send to exactly this host only Domain set: Send to every host at or under this domain Priority: When too many cookies from a single domain, delete those of low priority first Not really a security feature! 2 Cookies: Securing them SameSite: Cookie should not be sent with cross-site requests (some CSRF-prevention; prevent cross-origin information leakage) “Strict” : Never cross origin; not even when clicking on a link on site A leading to B the Cookie set from B is actually sent to B “Lax” (default): Sent when clicking on most links, but not with POST requests: “Same-Site” and “cross-site top-level navigation” Not as good as strict: E.g. “<link rel='prerender’>” is a same-site request fetched automatically (and kept in the background!) Sent: GET requests leading to a top-level target (=URL in address bar changes; but may contain e.g. path) I.e.: Will not be sent for iframes, images, XMLHttpRequests
    [Show full text]
  • Application of Ontological Models for Representing Engineering Concepts in Engineering
    SCIENTIFIC PROCEEDINGS X INTERNATIONAL CONGRESS "MACHINES, TECHNOLОGIES, MATERIALS" 2013 ISSN 1310-3946 APPLICATION OF ONTOLOGICAL MODELS FOR REPRESENTING ENGINEERING CONCEPTS IN ENGINEERING Martin Ivanov1, Nikolay Tontchev2 New Bulgarian University, Sofia, Montivideo 211, University of Transport, Sofia, Geo Milev 1582 Abstract: The necessity, opportunities and advantages from developing ontological models of engineering concepts in the field of machine manufacturing technology are introduced. The characteristics and principles of the methodology for developing engineering technology models are presented. An experimental ontological model developed by the authors based on Protégé OWL 4.2 is described. Keywords: ONTOLOGICAL MODELS, ENGINEERING CONCEPTS, IDEF5, PROTEGE OWL 1. Introduction - Existing objects and phenomena in the subject area in the terms of the accepted terminology (vocabulary/vocabularies, Modern engineering activities take place in an evolving and in this case – the so called engineering lexicon or EL); enriching information environment characterized by exponentially - How objects and phenomena relate to each other; increasing information flows, variety of means for access and in the formats of data presentation, diversity of engineering problems, - How they are used within the subject area, and outside it; solved by automated means, penetration of the artificial intelligence methods and the semantic Web, too. Effectiveness of engineering is - Rules that define their existence and behavior. highly dependent on the access and the opportunities for efficient The ontology is composed on the basis of a specific vocabulary processing of this information, in particular by the use of models for and terminology characteristic for the subject area. This implies (a) formally describing, processing and dissemination of knowledge strict definitions (axioms) of the terms and rules (grammars) resulting from research and engineering practice.
    [Show full text]