Information and Discovery in Neuroscience

Carole L. Palmer, Melissa H. Cragin & Timothy P. Hogan Graduate School of Library and Information Science, University of Illinois, Urbana-Champaign, 501 E. Daniel St., Champaign, IL 61 820. Ernail: {clpalmer, cragin, thogan}@uiuc.edu

Introduction It is becoming increasingly difficult for scientists to

identify, manage, and process all the information needed to conduct their research. Information work is especially complex in fields like neuroscience where research is often carried out by multidisciplinary teams, and new discoveries may require understanding of an extensive body of accumulated knowledge. This project investigates the information activities and resources associated with advances and roadblocks in neuroscience research to address the following research question: What information conditions are associated with significant progress or problems during the course of research? The study examines the daily work of neuroscience teams through laboratory field studies, with a particular focus on the role of cooperation and information sharing across disciplines and subdisciplines. Determining the information work that is critical to advancing the research process will clarify the kinds of information support that can best promote discovery and collaboration.

Neuroscience Information Environment "Neuroscientists are llke puzzle builders who must

integrate and fit together numerous small pieces of information derived from the hundreds of available techniques ... [with] incomplete knowledge of how different pieces relate to one another'' (Pachura and Martin, 1991, p. 28). Withm the field of neuroscience there is an acute awareness that new information technologies are needed for managing the extensive bodies of accumulated data and knowledge. Major initiatives, such as the Human Brain Project and the Biomedical Informatics Research Network (BIRN), are responding to problems of fragmentation in neuroscience by supporting projects designed to integrate immense data sets and foster information sharing (Shepherd et al, 1998; Koslow, 2000; Maisel, 2001). Th~s study complements ongoing and systematic informatics activities in neuroscience by assessing the impact of current mformation systems and the potential for new tools and resources.

As Gerson (2002) notes, to understand discovery we need to analyze the conditions under which effective intersections take place and the circumstances that block

or retard the formation of fruitful intersections. This three-year study aims to achieve this type of analysis through four objectives: 1) identify the types of information needed and used by neuroscientists in day-to- day research work; 2) develop profiles of high impact information and significant information problems; 3) map effective combinations of information activities and resources; 4) analyze strategies and roadblocks in the flow of information between teams and domains. The scope of thls study also allows testing of our previous results on the relationship between modes of research and information practices in interdisciplinary science (Palmer, 2001). In this poster we report on the design of the study and preliminary findings from analysis of year-one data.

Approach and Methods Our project is being conducted in cooperation with the

Arrowsmith Project, whlch is directed by Neil Smalheiser, Department of Psychlatry at the University of Illinois at Chicago and supported by the NIMH Human Brain Project. Smalheiser and Don Swanson, from the University of Chicago, have collaborated to develop a data mining system for assessing hypotheses in disconnected disciplinary literatures (Swanson and Smalheiser, 1999; Smalheiser, 2002). To inform further development of the system, the Arrowsmith Project is conducting field tests at four neuroscience labs across the country. Data on information activities are being collected through an electronic lab notebook developed by Smalheiser's team. Scientists use the notebook to record Arrowsmith searches and other types of information activities. We are analyzing the search reports collected from the labs, but the bulk of our data comes from qualitative field studies performed at the Arrowsmith field test sites to build case studies of the research projects at the laboratories.

The case studies include data collected through interviews, observations, and analysis of documents produced by the research teams. Critical incidents that represent the thrusts of our study-important advances in a line of research, information based roadblocks, or cross- disciplinary interaction-are being examined in depth and developed longitudinally. Qualitative interviews are conducted regularly with key informants at the lab sites and are being selectively extended to include close

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collaborators and other research personnel. Observations of scientists' daily work are providing specific data on how information tools and resources are used, as well as context for describing the ongoing lab activities. Analysis of documents produced by the researchers, including journal articles, proposals, and working notes, adds supplemental data on how information is used and created by the scientists.

Most of the data collected in year one came from two anonymous sites in different parts of the country. Data collection at a third site is underway and is being scaled up in year two. The type of research conducted at the two current sites varies in important ways. One lab is focused on learning and memory and is organized to support electrophysiology and behavioral research using small mammals. The other is much larger, supporting electron microscopy and tomography research of many scientists and researchers, some of whom travel to use the lab's facilities. This second lab is also set up to do neuroinformatics research, resulting in the integration of new tools directly into the research processes of biologists and anatomists. The former lab is most interested in identifying and explicating the role of interacting systems in the brain. The latter is interested in cell biology and understanding the function of different cell structures. The two labs also have different orientations to collaboration and data sharing, thus they capture and use data quite differently. The scope and variation of the research at these sites offer a broad base for investigating the relationship between information and the processes of discovery in neuroscience.

Analysis of Information Practices Longitudinal case analysis and comparison across cases

will continue throughout the three-year project. This poster presents a preliminary topology of the types of information involved in research at the sites, an analysis of the information problems that researchers face, and profiles of high impact information. Other early findings to be presented include (but are not limited to) the barriers to information flow between clinical and basic research communities, problems related to limited access to retrospective literatures, the strong influence of small specialized conferences, and the deluge of information at more general conference venues. The poster includes an

assessment of the electronic notebook as a data collection instrument and its viability for future studies of information in laboratory science.

ACKNOWLEDGEMENT The Information Work and Discovery Potentials in

Neuroscience Research project is funded by the National Science Foundation, Grant #0222848. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF.

REFERENCES Gerson, E. (2002). Premature discovery is failure of intersection

among social worlds. In Ernest B. Hook (Ed.), Prematurity and scientific discovery. Berkeley: University of California Press.

Koslow, S.H. (2000). Should the neuroscience community make a paradigm shift to sharing primary data? Nature Neuroscience, 3 (9), 863-865.

Maisel, M. (200 I ) . Biomedical Informatics Research Network to improve understanding of brain disorders. Envision, 17 (4). Retrieved May 14,2003, from http://www.npaci.edu/enVision/vl7.4/biomed.html#data.

Pachura, C.M. & Martin, J.B. (Eds.) (1991). Advancing neuroscience in the decade of the brain. In Mapping the brain and its functions: integrating enabling technologies into neuroscience research. Washington, D.C.: National Academy Press.

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

Shepherd, G.M., Mirsky, J.S., Healy, M.D., Singer, M.S., Skoufos, E., Hines, M.S., Nadkami, P.M., and Miller, P.L. (1998). The Human Brain Project: Neuroinformatics tools for integrating, searching and modeling multidisciplinary neuroscience data. Trends in Neurosciences, 21 (1 l), 460-468.

Smalheiser, N.R. (2002). Informatics and hypothesis-driven research. EMBO Reports, 3 (S), 702.

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

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