August 12th, 2008
[For the full entry, please see the Oxford Internet Institute’s Summer Doctoral Programme wiki]
During her presentation to our SDP group, Wendy Hall mentioned that if two people type the same thing into Google, regardless of their purpose for the search, they will get the same results. Jim Hendler raised similar concerns when he spoke of efficiency trumping accuracy in Google search results. Certainly, if users had to wait five minutes or longer for a search engine to deliver a correct answer, they would likely not use search engines with the frequency that they currently do. That said, why can’t search engines be fast and accurate?
Through our SDP discussions, I realized that small studies, such as my dissertation research, can contribute to our understanding of why people search, what they expect, and how best to deliver this information. For example, currently, the consequences of inaccurate search results are minor and thus users are willing to modify their terms multiple times to find what they need. While delivery of search results is quite fast, how long do people spend modifying their terms until they happen upon information that answers their question, or completes their task? The human side, then, absorbs much of the work that the system could potentially provide. Understanding the cognitive process of information search and use could thus better inform the development of more accurate information delivery systems.
In addition to improving the accuracy of information delivery, understanding users’ cognitive processes could inform the depth of information provided about the data itself. Online information is currently, for the most part, opaque in terms of reporting authorship and authority, which makes determining credibility difficult. In developing the semantic web, perhaps an additional question to consider is how we can leverage its ontologies to provide more transparency in terms of who is providing the information, when it has been updated, who is linking to it, and other relevant credibility criteria/measures.
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August 5th, 2008
While still in many ways an elusive topic, the study and definitions of web science became more tangible during our SDP discussions. Before attending OII, I thought web science simply meant the study of how people use the Web. This definition in many ways reflected my disciplinary bias by focusing on the who of the Web, rather than what it is or how it works. In his presentation to our group, Tim Berners-Lee described web science as taking fundamental things and looking at how the Web changes them. Hendler, Shadbolt, Hall, Berners-Lee, and Weitzner (2008) extend this definition to broadly include the study of systems, their development, efficiency, scalability, flexibility and the people who use them, their uses, interactions, interpretations, appropriations, and the communities that form in response to or as a result of, this use.
In addition to addressing the what and who of web science, our discussions addressed an additional how, the methods by which we will study it. The medium of the Web challenges us as researchers to both re-think traditional methods of data collection and analysis and develop new, more flexible methods to measure and record interactions that are in a sense, spatially invisible. Communication online can be both asynchronous and in real-time, remote and co-located. While older communication technologies certainly allowed remote or asynchronous interaction, the Web’s flexibility presents this challenge on an unprecedented scale.
As Hendler, et al. (2008) state, “…web scientists need to develop new methodologies for gathering evidence and finding ways to anticipate how human behavior will impact on the development of a system which is constantly evolving at such an amazing rate.” In a sense, the dynamic, flexible nature of the Web forces interdisciplinary study because a single discipline cannot possibly account for its multiple layers, even when the research has a narrow, specialized focus. In our discussions at OII, Li Zhang used the metaphor about three blind people attempting to describe an elephant based on the parts they see. This discussion summarized the importance of a multi-disciplinary approach to web science: without each of us communicating the parts of the Web we see, whether it be its architecture or use, we run the risk of seeing the Web as solely its tail, or foot, and never understanding the dynamic, flexible phenomenon we study.
Hendler, J., Shadbolt, N., Hall, N., Berners-Lee, T., & Weitzner, D. (2008). Web Science: An interdisciplinary approach to understanding the World Wide Web. Communications of the ACM, 51, 60-69.
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