This text sets out a series of approaches to the analysis and synthesis of the World Wide Web, and other web-like information structures. A comprehensive set of research questions is outlined, together with a sub-disciplinary breakdown, emphasising the multi-faceted nature of the Web, and the multi-disciplinary nature of its study and development. These questions and approaches together set out an agenda for Web Science, the science of decentralised information systems. Web Science is required both as a way to understand the Web, and as a way to focus its development on key communicational and representational requirements. The text surveys central engineering issues, such as the development of the Semantic Web, Web services and P2P. Analytic approaches to discover the Web’s topology, or its graph-like structures, are examined. Finally, the Web as a technology is essentially socially embedded; therefore various issues and requirements for Web use and governance are also reviewed.
Tim Berners-Lee, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Wendy Hall, School of Electronics and Computer Science, University of Southampton, James A. Hendler, Department of Computer Science, Rensselaer Polytechnic Institute, Kieron O’Hara, School of Electronics and Computer Science, University of Southampton, Nigel Shadbolt, School of Electronics and Computer Science, University of Southampton, Daniel J. Weitzner, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology,
Tim Berners-Lee, Wendy Hall, James A. Hendler, Kieron O’Hara, Nigel Shadbolt and Daniel J. Weitzner (2006), “A Framework for Web Science”, Foundations and Trends® in Web Science: Vol. 1: No. 1, pp 1-130. http://dx.doi.org/10.1561/1800000001 Export
Published: Sep 20, 2006
© 2006 T. Berners-Lee, W. Hall, J.A. Hendler, K. O’Hara, N. Shadbolt and D.J. Weitzner
The transformative power of the Internet on all aspects of daily life, including health care, has been widely recognized. These transformations reveal opportunities realized, the promise of future advances, and the problems created by the penetration of the World Wide Web for both individuals and for society at large. Health Web Science explores the role of the Web as it drives discussions, technologies, policies, and solutions related to health. We also examine the impact of the Web’s health-related uses on the design, structure and evolution of the Web itself. The orientation of Health Web Science, compared to related research domains, motivates innovation in Web technology and better utilization of the Web for communication, collaboration, information access and sharing, remote sensing, and even remote treatment.
Joanne S. Luciano, Rensselaer Polytechnic Institute and Predictive Medicine, Inc., USA, firstname.lastname@example.org Grant P. Cumming, NHS Grampian, UK, email@example.com Eva Kahana, Case Western University, USA, firstname.lastname@example.org Mark D. Wilkinson, Universidad Politécnica de Madrid, Spain, email@example.com Elizabeth H. Brooks, Digital Health Institute, The Glasgow School of Art, Scotland, firstname.lastname@example.org Holly Jarman, University of Michigan School of Public Health, USA, email@example.com Deborah L. McGuinness, Rensselaer Polytechnic Institute, USA, firstname.lastname@example.org Minna S. Levine, SymTrend, Inc., USA, email@example.com
Joanne S. Luciano, Grant P. Cumming, Eva Kahana, Mark D. Wilkinson, Elizabeth H. Brooks, Holly Jarman, Deborah L. McGuinness and Minna S. Levine (2014), “Health Web Science”, Foundations and Trends® in Web Science: Vol. 4: No. 4, pp 269-419. http://dx.doi.org/10.1561/1800000019 Export
Published: Oct 14, 2014
© 2014 J. S. Luciano, G. P Cumming, E. Kahana, M. D. Wilkinson, E. H. Brooks, H. Jarman, D. L. McGuinness and M. S. Levine
Will your next doctor be a human being—or a machine? Will you have a choice? If you do, what should you know before making it? This book introduces the reader to the pitfalls and promises of artificial intelligence (AI) in its modern incarnation and the growing trend of systems to “reach off the Web” into the real world.
Hendler, J., & Mulvehill, A. (2016). Social Machines: The Coming Collision of Artificial Intelligence, Social Networking, and Humanity. Apress. DOI: 10.1007/978-1-4842-1156-4
Published: Sep 27, 2016
© 2016 James Hendler and Alice Mulvehill.
In this monograph we consider the development of Web Science since the launch of this journal and its inaugural publication ‘A Framework for Web Science’ . The theme of emergence is discussed as the characteristic phenomenon of Web-scale applications, where many unrelated micro-level actions and decisions, uninformed by knowledge about the macro-level, still produce noticeable and coherent effects at the scale of the Web. A model of emergence is mapped onto the multitheoretical multilevel (MTML) model of communication networks explained in . Four specific types of theoretical problem are outlined. First, there is the need to explain local action. Second, the global patterns that form when local actions are repeated at scale have to be detected and understood. Third, those patterns feed back into the local, with intricate and often fleeting causal connections to be traced. Finally, as Web Science is an engineering discipline, issues of control of this feedback must be addressed. The idea of a social machine is introduced, where networked interactions at scale can help to achieve goals for people and social groups in civic society; an important aim of Web Science is to understand how such networks can operate, and how they can control the effects they produce on their own environment.
Kieron O’Hara, University of Southampton, UK, firstname.lastname@example.org Noshir S. Contractor, Northwestern University, USA, email@example.com Wendy Hall, University of Southampton, UK, firstname.lastname@example.org James A. Hendler, Rensselaer Polytechnic Institute, USA, email@example.com Nigel Shadbolt, University of Southampton, UK, firstname.lastname@example.org
Kieron O’Hara, Noshir S. Contractor, Wendy Hall, James A. Hendler and Nigel Shadbolt (2013), “Web Science: Understanding the Emergence of Macro-Level Features on the World Wide Web”, Foundations and Trends® in Web Science: Vol. 4: No. 2–3, pp 103-267. http://dx.doi.org/10.1561/1800000017 Export
Published: Dec 18, 2013
© 2013 K. O’Hara, N. S. Contractor, W. Hall, J. A. Hendler, and N. Shadbolt