Weak Information Work and “Doable” Problems in Interdisciplinary Science

Palmer, Carole L. Weak Information Work and “Doable” Problems in Interdisciplinary Science., 2006 . In 69th Annual Meeting of the American Society for Information Science and Technology (ASIST), Austin (US), 3-8 November 2006. [Conference paper]

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English abstract

Drawing on results from two studies of information use in interdisciplinary science, this paper develops the concept of weak information work (WIW). WIW is examined in relation to a model of how different levels of research work are coordinated and a second framework that delineates dimensions of research problems. Scenarios from neuroinformatics case studies are presented to show how WIW is impacting interdisciplinary projects in brain research. Based on the integration of our results with existing frameworks for understanding scientific research problems and processes, we assert that contemporary interdisciplinary research could benefit from information systems and services devoted to supporting some lines of WIW and by transforming others into strong information work.

Item type: Conference paper
Keywords: information use ; interdisciplinary research ; scientific research problems
Subjects: B. Information use and sociology of information > BA. Use and impact of information.
Depositing user: Norm Medeiros
Date deposited: 18 Dec 2006
Last modified: 02 Oct 2014 12:05
URI: http://hdl.handle.net/10760/8636

References

Cummings, J. N., & Kiesler, S. (2005). Collaborative research across disciplinary and institutional boundaries. Social Studies of Science, 35(5), 703-722.

Finholt, T. A. (2003). Collaboratories as a new form of scientific organization. Economics of Innovation and New Technology, 12(1), 5-25.

Fujimura, J. H. (1987). Constructing ‘do-able’ problems in cancer research: Articulating alignment. Social Studies of Science, 17(2), 257-93.

Hsieh-Yee, I. (1993). Effects of search experience and subject knowledge on the search tactics of novice and experienced searchers. Journal of the American Society of Information Science, 44(3), 161-174.

Karasti, H., Baker, K. S., & Bowker, G. C. (2003). ECSCW 2003 computer supported scientific collaboration (CSSC) workshop report. SIGGROUP Bulletin, 24(2), 6-13.

Kuhn, T. (1962). The structure of scientific revolutions. Chicago: University of Chicago Press.

Langley, P., Simon, H. A., Bradshaw, G. L., & Zytkow, J. M. (1987). Scientific discovery: Computational explorations of the creative process. Cambridge: MIT Press.

MacMullin, S. E., & Taylor, R. S. (1984). Problem dimensions and information traits. The Information Society, 3(1), 91-111.

Palmer, C. L. (1999). Structures and strategies of interdisciplinary science. Journal of the American Society for Information Science, 50(3), 242-253.

Palmer, C. L. (2001). Work at the boundaries of science: Information and the interdisciplinary research process. Dordrecht: Kluwer.

Palmer, C. L., Cragin, M. H., & Hogan, T. P. (2004). Information at the intersections of discovery: Case studies in neuroscience. In L. Schamber & C.L. Barry (Eds.), Proceedings of the American Society for Information Science and Technology annual meeting, 41 (pp. 448-455). Medford, NJ: Information Today.

Palmer, C. L., Cragin, M. H., & Hogan, T. P. (in press). Weak information work in scientific discovery. Information Processing & Management.

Sihvonen, A., & Vakkari, P. (2004). Subject knowledge improves interactive query expansion assisted by a thesaurus. Journal of Documentation, 60(6), 673-690.

Simon, H. A. (1986). Understanding the processes of science: The psychology of scientific discovery. In T. Ganelius (Ed.), Progress in Science and Its Social Conditions: Proceedings of a Nobel Symposium (pp. 159-170). Oxford: Pergamon Press.

Simon, H. A., Langley, P. W., & Bradshaw, G. L. (1981). Scientific discovery as problem-solving. Synthese, 47, 1-27.

Smalheiser, N. R. (2005). The Arrowsmith Project: 2005 status report. In A. Hoffman, H. Motoda, & T. Scheffer (Eds.), Lecture notes in artificial intelligence, 3735 (pp. 26-43). Berlin: Springer.

Sonnenwald, D. H., Maglaughlin, K. L., & Whitton, M. C. (2004). Designing to support situation awareness across distances: An example from a scientific collaboratory. Information Processing & Management 40(6), 989-1011.

Strauss, A. L. (1988). The articulation of project work: An organizational process. Sociological Quarterly, 29(2), 163-178.

Strauss, A., Fagerhaugh, S., Suczek, B., & Wiener, C. (1985). Social organization of medical work. Chicago: University of Chicago Press.

Swanson, D. R., & Smalheiser, N. R. (1999). Implicit text linkages between Medline records: Using Arrowsmith as an aid to scientific discovery. Library Trends, 48(1), 48-59.

Taylor, R. S. (1991). Information use environments. Progress in Communication Sciences, 10, 217-55.

Teasley, S., & Wolinsky, S. M. (2001). Scientific collaborations at a distance. Science, 292(5525), 2254-2255.

Vakkari, P. (1999). Task complexity, problem structure and information actions: Integrating studies on information seeking and retrieval. Information Processing and Management, 35(6), 819-837.

Walsh, J. P., & Maloney, N. G. (2002). Computer network use, collaboration structures, and productivity. In P. Hinds & S. Kiesler (Eds.), Distributed Work (pp. 433-458). Cambridge, MA: MIT Press.

Wildemuth, B. M. (2004). The effects of domain knowledge on search tactic formulation. Journal of the American Society for Information Science and Technology, 55(3), 246–258.


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