A Celebration of 10 Years of the Science of the Web WEB SCIENCE TRUST BOARD Board Members
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A Comparative Evaluation of Geospatial Semantic Web Frameworks for Cultural Heritage
heritage Article A Comparative Evaluation of Geospatial Semantic Web Frameworks for Cultural Heritage Ikrom Nishanbaev 1,* , Erik Champion 1,2,3 and David A. McMeekin 4,5 1 School of Media, Creative Arts, and Social Inquiry, Curtin University, Perth, WA 6845, Australia; [email protected] 2 Honorary Research Professor, CDHR, Sir Roland Wilson Building, 120 McCoy Circuit, Acton 2601, Australia 3 Honorary Research Fellow, School of Social Sciences, FABLE, University of Western Australia, 35 Stirling Highway, Perth, WA 6907, Australia 4 School of Earth and Planetary Sciences, Curtin University, Perth, WA 6845, Australia; [email protected] 5 School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, WA 6845, Australia * Correspondence: [email protected] Received: 14 July 2020; Accepted: 4 August 2020; Published: 12 August 2020 Abstract: Recently, many Resource Description Framework (RDF) data generation tools have been developed to convert geospatial and non-geospatial data into RDF data. Furthermore, there are several interlinking frameworks that find semantically equivalent geospatial resources in related RDF data sources. However, many existing Linked Open Data sources are currently sparsely interlinked. Also, many RDF generation and interlinking frameworks require a solid knowledge of Semantic Web and Geospatial Semantic Web concepts to successfully deploy them. This article comparatively evaluates features and functionality of the current state-of-the-art geospatial RDF generation tools and interlinking frameworks. This evaluation is specifically performed for cultural heritage researchers and professionals who have limited expertise in computer programming. Hence, a set of criteria has been defined to facilitate the selection of tools and frameworks. -
From the Semantic Web to Social Machines
ARTICLE IN PRESS ARTINT:2455 JID:ARTINT AID:2455 /REV [m3G; v 1.23; Prn:25/11/2009; 12:36] P.1 (1-6) Artificial Intelligence ••• (••••) •••–••• Contents lists available at ScienceDirect Artificial Intelligence www.elsevier.com/locate/artint From the Semantic Web to social machines: A research challenge for AI on the World Wide Web ∗ Jim Hendler a, , Tim Berners-Lee b a Tetherless World Constellation, RPI, United States b Computer Science and AI Laboratory, MIT, United States article info abstract Article history: The advent of social computing on the Web has led to a new generation of Web Received 24 September 2009 applications that are powerful and world-changing. However, we argue that we are just Received in revised form 1 October 2009 at the beginning of this age of “social machines” and that their continued evolution and Accepted 1 October 2009 growth requires the cooperation of Web and AI researchers. In this paper, we show how Available online xxxx the growing Semantic Web provides necessary support for these technologies, outline the challenges we see in bringing the technology to the next level, and propose some starting places for the research. © 2009 Elsevier B.V. All rights reserved. Much has been written about the profound impact that the World Wide Web has had on society. Yet it is primarily in the past few years, as more interactive “read/write” technologies (e.g. Wikis, blogs and photo/video sharing) and social network- ing sites have proliferated, that the truly profound nature of this change is being felt. From the very beginning, however, the Web was designed to create a network of humans changing society empowered using this shared infrastructure. -
Deciding SHACL Shape Containment Through Description Logics Reasoning
Deciding SHACL Shape Containment through Description Logics Reasoning Martin Leinberger1, Philipp Seifer2, Tjitze Rienstra1, Ralf Lämmel2, and Steffen Staab3;4 1 Inst. for Web Science and Technologies, University of Koblenz-Landau, Germany 2 The Software Languages Team, University of Koblenz-Landau, Germany 3 Institute for Parallel and Distributed Systems, University of Stuttgart, Germany 4 Web and Internet Science Research Group, University of Southampton, England Abstract. The Shapes Constraint Language (SHACL) allows for for- malizing constraints over RDF data graphs. A shape groups a set of constraints that may be fulfilled by nodes in the RDF graph. We investi- gate the problem of containment between SHACL shapes. One shape is contained in a second shape if every graph node meeting the constraints of the first shape also meets the constraints of the second. Todecide shape containment, we map SHACL shape graphs into description logic axioms such that shape containment can be answered by description logic reasoning. We identify several, increasingly tight syntactic restrictions of SHACL for which this approach becomes sound and complete. 1 Introduction RDF has been designed as a flexible, semi-structured data format. To ensure data quality and to allow for restricting its large flexibility in specific domains, the W3C has standardized the Shapes Constraint Language (SHACL)5. A set of SHACL shapes are represented in a shape graph. A shape graph represents constraints that only a subset of all possible RDF data graphs conform to. A SHACL processor may validate whether a given RDF data graph conforms to a given SHACL shape graph. A shape graph and a data graph that act as a running example are pre- sented in Fig. -
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. -
The Web of Data for E-Commerce: Schema.Org and Goodrelations for Researchers and Practitioners
The Web of Data for E-Commerce: Schema.org and GoodRelations for Researchers and Practitioners Martin Hepp() E-Business & Web Science Research Group, Universität der Bundeswehr München, Werner-Heisenberg-Weg 39, 85577, Neubiberg, Germany [email protected] Abstract. Schema.org is one of the main drivers for the adoption of Semantic Web principles by a broad number of organizations and individuals for real business needs. GoodRelations is a well-established conceptual model for representing e-commerce information, one of the few widely used OWL DL on- tologies, and since 2012 the official e-commerce model of schema.org. In this tutorial, we will (1) give a comprehensive overview and hands-on training on the advanced conceptual structures of schema.org for e-commerce, including patterns for ownership and demand, (2) present the full tool chain for producing and consuming respective data, (3) explain the long-term vision of Linked Open Commerce, and (4) discuss advanced topics, like access control, identity and authentication (e.g. with WebID); micropayment services, and data management issues from the publisher and consumer perspective. We will also cover research opportunities resulting from the growing adoption and the re- spective amount of data in RDFa, Microdata, and JSON-LD syntaxes. Keywords: Schema.org · GoodRelations · Semantic Web · Ontologies · Micro- data · OWL · RDFa · JSON-LD · Linked Open Data · E-Commerce · E-Business 1 Introduction Schema.org [1] is one of the main drivers for the adoption of Semantic Web principles by a broad number of people for their real business needs. The resulting amount of real-world RDF1 data exceeds a critical mass so that it becomes interesting as reference data for any kind of foundational Semantic Web research. -
The 8Th ACM Web Science Conference 2016
This is a repository copy of The 8th ACM Web Science Conference 2016. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/103102/ Version: Accepted Version Article: Jäschke, R. (2016) The 8th ACM Web Science Conference 2016. ACM SIGWEB Newsletter (Summer). pp. 1-7. ISSN 1931-1745 https://doi.org/10.1145/2956573.2956574 Reuse Unless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version - refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher’s website. Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ pdfauthor The 8th ACM Web Science Conference 2016 Robert Jaschke¨ L3S Research Center Hannover, Germany This article provides an overview of this year’s ACM Web Science Conference (WebSci’16). It was located in Hannover, Germany, and organized by L3S Research Center and the Web Science Trust. WebSci’16 attracted more than 160 researchers from very different disciplines – ranging from computer science to anthropology. -
The Web Observatory Extension: Facilitating Web Science Collaboration Through Semantic Markup
The Web Observatory Extension: Facilitating Web Science Collaboration through Semantic Markup Dominic DiFranzo John S. Erickson Marie Joan Kristine T. Gloria Tetherless World Constellation, Tetherless World Constellation, Tetherless World Constellation, Rensselaer Polytechnic Institute, Rensselaer Polytechnic Rensselaer Polytechnic Institute, Troy, NY USA Institute, Troy, NY USA Troy, NY USA [email protected] [email protected] [email protected] Joanne S. Luciano Deborah L. McGuinness James Hendler Tetherless World Constellation, Tetherless World Constellation, Tetherles World Constellation, Rensselaer Polytechnic Institute, Rensselaer Polytechnic Rensselaer Polytechnic Institute, Troy, NY USA Institute, Troy, NY USA Troy, NY USA [email protected] [email protected] [email protected] ABSTRACT Still in its infancy, the field of Web Science now faces several The multi-disciplinary nature of Web Science and the large size unique challenges from conflicting methodological philosophies and diversity of data collected and studied by its practitioners has to developing a suitable infrastructure for its scientists to inspired a new type of Web resource known as the Web collaborate and share resources. More importantly, the scale and Observatory. Web observatories are platforms that enable scope of the data produced by users of the Web and studied by researchers to collect, analyze and share data about the Web and Web Scientists is unprecedented for any modern field of study. to share tools for Web research. At the Boston Web Observatory Web Scientists are thus looking to mixed methodology practices, Workshop 2013 [3], a semantic model for describing Web new computational infrastructure and large scale analytics in order Observatories was drafted and an extension to the schema.org to better make sense of this complex phenomena. -
Network Science
review articles DOI:10.1145/2699416 Jacob Moreno’s25 efforts to develop Exploring three interdisciplinary areas and the “sociometry.” Soon thereafter, the mathematical framework offered by extent they overlap. Are they all part of the graph theory was also picked up by same larger domain? psychologists,2 anthropologists,23 and other social scientists to create an in- BY THANASSIS TIROPANIS, WENDY HALL, JON CROWCROFT, terdiscipline called Social Networks. NOSHIR CONTRACTOR, AND LEANDROS TASSIULAS The interdiscipline of Social Networks expanded even further toward the end of the 20th century with an explosion of interest in exploring networks in biological, physical, and technologi- Network cal systems. The term Network Sci- ence emerged as an interdisciplinary area that draws on disciplines such as physics, mathematics, computer sci- Science, ence, biology, economics, and sociol- ogy to encompass networks that were not necessarily social.1,26,35 The study of networks involves developing ex- planatory models to understand the Web Science, emergence of networks, building predictive models to anticipate the evolution of networks, and construct- ing prescriptive models to optimize and Internet the outcomes of networks. One of the main tenets of Network Science is to identify common underpinning principles and laws that apply across Science very different networks and explore why in some cases those patterns vary. The Internet and the Web, given their spectacular growth and impact, are networks that have captured the imagination of many network scien- THE OBSERVATION OF patterns that characterize key insights networks, from biological to technological and social, ˽ Web Science and Internet Science aim to understand the evolution of the Web and the impact of the Web and the Internet on society and the Internet respectively and to inform debates about their future. -
Navigational Efficiency of Broad Vs. Narrow Folksonomies
Navigational Efficiency of Broad vs. Narrow Folksonomies Denis Helic Christian Körner Michael Granitzer Knowledge Management Knowledge Management Chair of Media Informatics Institute Institute University of Passau Graz University of Technology Graz University of Technology Passau, Germany Graz, Austria Graz, Austria Michael.Granitzer@uni- [email protected] [email protected] passau.de Markus Strohmaier Christoph Trattner Knowledge Management Institute for Information Institute and Know-Center Systems and Computer Media Graz University of Technology Graz University of Technology Graz, Austria Graz, Austria [email protected] [email protected] ABSTRACT Keywords Although many social tagging systems share a common tri- Navigation, Folksonomy, Keywords, Tags partite graph structure, the collaborative processes that are generating these structures can di ffer significantly. For ex- 1. INTRODUCTION ample, while resources on Delicious are usually tagged by all In social tagging systems, users organize information us- users who bookmark the web page cnn.com , photos on Flickr ing so-called tags – a set of freely chosen words or concepts are usually tagged just by a single user who uploads the – to annotate various resources such as web pages on Deli- photo. In the literature, this distinction has been described cious, photos on Flickr, or scientific articles on BibSonomy. as a distinction between broad vs. narrow folksonomies . In addition to using tagging systems for personal organiza- This paper sets out to explore navigational di fferences be- tion of information, users can also socially share their an- tween broad and narrow folksonomies in social hypertextual notations with each other. The information structure that systems. We study both kinds of folksonomies on a dataset emerges through such processes has been typically described provided by Mendeley - a collaborative platform where users 1 as “folksonomies ” ( fol k-generated ta xonomies ). -
A Manifesto for Web Science? Susan Halford, Cathy Pope, Leslie Carr University of Southampton Southampton United Kingdom
A Manifesto for Web Science? Susan Halford, Cathy Pope, Leslie Carr University of Southampton Southampton United Kingdom [email protected] Categories and Subject Descriptors The call for Web Science insists that we open up this H.3.5 [Information Storage and Retrieval]: Online space. In doing so, a flag has been planted. Hendler, Information Services Berners-Lee et al have named this territory for web science and have begun to map it from their vantage point in General Terms Computer Science. But – and as they would be the first to Management, Documentation, Economics, Security, acknowledge – this is only one vantage point. Other Human Factors, Legal Aspects. disciplines will add new perspectives and interpretations. However, it is by no means certain that we will all agree Keywords about what we see. For whilst we might all agree that Web Web science Science cannot develop without inter-disciplinarity, we 1. INTRODUCTION should be clear from the beginning that this is no simple matter. We need to be realistic about what we are getting A clarion call for a new science of the web has been ourselves into. There will be big challenges in making sounded in the pages of CACM (Hendler et al 2008) and ourselves understood to each other and developing elsewhere in path-breaking papers by Berners-Lee et al collaborative understandings will require us to leave the (2006a, 2006b). These authors point to a paradox: despite comfort of our disciplinary silos. But, the promise of new the huge effect that the web has had on computing – not to forms of knowledge and understanding that are bigger than mention the world – computer scientists rarely study the the sum of our parts are gains worth working for. -
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KI Special Issue Social Media (version as of Oct 29, 2012) Interview with Jim Hendler on Social Media and Collective Intelligence Panagiotis Takis Metaxas James A. Hendler ((**max 180 words)) James Hendler is the Tetherless World Professor of Computer and Cognitive Science and the Head of the Computer Science Department at RPI. He also serves as a Director of the UK’s charitable Web Science Trust and is a visiting Professor at DeMontfort University in Leicester, UK. Hendler has authored about 200 technical papers in the areas of Semantic Web, artificial intelligence, agent-based computing and high performance processing. One of the early “Semantic Web” innovators, Hendler is a Fellow of the American Association for Artificial Intelligence, the British Computer Society, the IEEE and the AAAS. In 2010, Hendler was named one of the 20 most innovative professors in America by Playboy magazine and was selected as an “Internet Web Expert” by the US government. He is the Editor-in-Chief emeritus of IEEE Intelligent Systems and is the first computer scientist to serve on the Board of Reviewing Editors for Science. Hendler was the recipient of a 2012 Strata Conference Data Innovation Award for his work in Open Government Data. KI: We see a very broad interpretation of Social Media these days. How do you define Social Media? In the real world people form communities of various kinds that are bound together by social relationships – those relationships are the real-world “social networks” that social-networking sites rely on. Personally, I see social media as the online means for realizing, extending, maintaining, etc. -
Coverage of Academic Citation Databases Compared with Coverage
The current issue and full text archive of this journal is available on Emerald Insight at: www.emeraldinsight.com/1468-4527.htm Coverage of Coverage of academic citation academic databases compared with citation coverage of scientific social media databases Personal publication lists as 255 calibration parameters Received 24 July 2014 Fourth revision approved Fee Hilbert, Julia Barth, Julia Gremm, Daniel Gros, Jessica Haiter, 5 January 2015 Maria Henkel, Wilhelm Reinhardt and Wolfgang G. Stock Department of Information Science, Heinrich Heine University, Dusseldorf, Germany Abstract Purpose – The purpose of this paper is to show how the coverage of publications is represented in information services. Academic citation databases (Web of Science, Scopus, Google Scholar) and scientific social media (Mendeley, CiteULike, BibSonomy) were analyzed by applying a new method: the use of personal publication lists of scientists. Design/methodology/approach – Personal publication lists of scientists of the field of information science were analyzed. All data were taken in collaboration with the scientists in order to guarantee complete publication lists. Findings – The demonstrated calibration parameter shows the coverage of information services in the field of information science. None of the investigated databases reached a coverage of 100 percent. However Google Scholar covers a greater amount of publications than other academic citation databases and scientific social media. Research limitations/implications – Results were limited to the publications of scientists working at an information science department from 2003 to 2012 at German-speaking universities. Practical implications – Scientists of the field of information science are encouraged to review their publication strategy in case of quality and quantity. Originality/value – The paper confirms the usefulness of personal publication lists as a calibration parameter for measuring coverage of information services.