Abstract
In the new data-intensive science paradigm, data infrastructures have been designed and built to collect, archive, publish, and analyze scientific data for a variety of users. Little attention, however, has been paid to users of these data infrastructures. This study endeavors to improve our understanding of these users’ data usage models through a content analysis of publications related to a frequently cited project in the data-intensive science, Sloan Digital Sky Survey (SDSS). We find that 1) Content analysis of scientific publications could be a complementary method for researchers in HCI community; 2) although SDSS produced a large volume of astronomical data, users did not fully utilize these data; 3) users are not only consumers of scientific data, they are also producers; and 4) studies that can use multiple large scale data sources are relatively rare. Issues of data provenance and usability may prevent researchers from doing research that combines such data sources. Further HCI study of detailed usability issues associated with data infrastructures in the new paradigm is eagerly needed.
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Hey, T., Tansley, S., Tolle, K. (eds.): The Fourth-Paradigm: Data-Intensive Scientific Discovery, 2nd edn. Microsoft Research, Redmond (2009)
Fischer, G.: User Modeling in Human-Computer Interaction. User Modeling and User-Adapted Interaction 11(65), 65–86 (2001)
Borgman, C.L.: Scholarship in the Digital Age: Information, Infrastructure, and the Internet. The MIT Press, Cambridge (2007)
Atkinson, M., De Roure, D.: Data-intensive Reseach: Making best use of research data (Draft 1), e-Science Institute (2009)
York, D.G., et al.: The Sloan Digital Sky Survey: Technical summary. Astronomical Journal 120, 1579–1587 (2000)
Bell, G., Hey, T., Szalay, A.: Beyond the Data Deluge. Science, 1297–1298 (2009)
Ailamaki, A., Kantere, V., Dash, D.: Managing Scientific Data. Communication of the ACM, 68–78 (2010)
Wallis, J.C., et al.: Digital Libraries for Scientific Data Discovery and Reuse: From Vision to Practical Reality. In: IEEE/ACM Joint Conference on Digital Library (JCDL 2010), Surfer’s Paradise, Australia, pp. 333–340 (2010)
Van de Sompel, H., Lagoze, C.: All Aboard: Toward a Machine-Friendly Scholarly Communication System. In: Hey, A.J.G., Tansley, S., Tolle, K. (eds.) The Fourth Paradigm: Data-intensive Scientific Discovery, pp. 193–199. Microsoft, Redmong (2009)
Mangiafico, P.: We are all curators now: envisioning new roles for research libraries in an era of information abundance, social networks, and digital ephemera. Personal Communication (2010)
Doraimani, S., Iamnitchi, A.: File Grouping for Scientific Data Management: Lessons from Experimenting with Real Traces. In: The 17th IEEE International Symposium on High Performance Distributed Computing (HPDC 2008), pp. 153–164. ACM, Boston (2008)
Yao, Q., An, A.: Characterizing Database User’s Access Patterns. In: Galindo, F., Takizawa, M., Traunmüller, R. (eds.) DEXA 2004. LNCS, vol. 3180, pp. 528–538. Springer, Heidelberg (2004)
McKechine, L.E.F., et al.: Research method trends in human information literature. New Review of Information Behaviour Research 3, 113–125 (2002)
White, M.D., Marsh, E.E.: Content Analysis: A flexible methodology. Library Trends 55(1), 22–45 (2006)
Lombard, M., Snyder-Duch, J., Bracken, C.: Content analysis in mass communication: Assessment and Reporting of Intercoder Reliability. Human Communication Research 28, 587–604 (2002)
Mann, B.: Some Data Derivation and Provenance issues in Astronomy. In: Data Provenance/Derivation Workshop, Chicago, IL (2002)
Balazinska, M., et al.: Data Management in the Worldwide Sensor Web. Pervasive, 30–40 (2007)
To share or not to share: Publication and quality assurance of reseach data outputs. Research Information Network (2008)
Borne, K.D., Astroinformatics: A 21st Century Approach to Astronomy, in Position Paper, George Mason University (2009)
Szalay, A., Gray, J.: The World-Wide Telescope. Science, 2037–2040 (2001)
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Zhang, J., Chen, C., Vogeley, M.S. (2011). Modeling Users’ Data Usage Experiences from Scientific Literature. In: Marcus, A. (eds) Design, User Experience, and Usability. Theory, Methods, Tools and Practice. DUXU 2011. Lecture Notes in Computer Science, vol 6770. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21708-1_39
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DOI: https://doi.org/10.1007/978-3-642-21708-1_39
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