The Role of Data Science in Web Science

Web science relies on an interdisciplinary approach that seeks to go beyond what any one subject can say about the World Wide Web. By incorporating numerous disciplinary perspectives and relying heavily on domain knowledge and expertise, data science has emerged as an important new area that integrates statistics with computational knowledge, data collection, cleaning and processing, analysis methods, and visualization to produce actionable insights from big data. As a discipline to use within Web science research, data science offers significant opportunities for uncovering trends in large Web-based datasets. A Web science observatory exemplifies this relationship by offering an online platform of tools for carrying out Web science research, allowing users to carry out data science techniques to produce insights into Web science issues such as community development, online behavior, and information propagation. The authors outline the similarities and differences of these two growing subject areas to demonstrate the important relationship developing between them.

[1]  Thanassis Tiropanis,et al.  Building a Real-Time Web Observatory , 2015, IEEE Internet Computing.

[2]  Wendy Hall,et al.  The Web Observatory: A Middle Layer for Broad Data , 2014, Big Data.

[3]  Catherine Pope,et al.  A manifesto for Web Science , 2010 .

[4]  Thanassis Tiropanis,et al.  Web evolution and Web Science , 2012, Comput. Networks.

[5]  Leandros Tassiulas,et al.  Network science, web science, and internet science , 2015, Commun. ACM.

[6]  Alex Wright,et al.  Web science meets network science , 2011, Commun. ACM.

[7]  James A. Hendler,et al.  The Web Science Observatory , 2013, IEEE Intelligent Systems.

[8]  Chris Mattmann,et al.  Computing: A vision for data science , 2013, Nature.

[9]  Su White,et al.  Web Science : Expanding the Notion of Computer Science , 2011 .

[10]  Vasant Dhar,et al.  Data science and prediction , 2012, CACM.