Adapting Digital Information to Scientific Practices

There is no doubt that patterns and trends in information use are rapidly changing in the digital environment. Studies have shown that scientists are “reading” more and that users of all kinds are applying new linking and “bouncing” search strategies on the Web. The nature of scholarly networks is also changing. In addition to the invisible colleges traditionally represented through citation indicators, we now see evidence of looser, more informal, “invisible constituencies” in scholarly web interactions. In terms of expectations, utopian e-research scenarios promoted decades ago are now seen as realistic and obtainable goals. As research becomes increasingly dependent on digital content and tools, we have an unprecedented opportunity to apply our knowledge of information behavior and research practice to improve information support for scientific inquiry. Yet, we have a limited base of knowledge of the value and impact of information resources on scientific work. Measures of accessing, downloading, linking, and citing behavior tell us very little about the actual activities of reading, experimenting, or problem solving, or about the features of information that effectively fuel new discoveries in the course of scientific research. While it may be obvious that not all information activities and sources are equal, their varying roles and contributions to the conduct of science have not been well documented. But this is precisely what we need to understand to set priorities for information system development that will improve conditions for scientists to make progress on research problems. In this presentation, I will discuss different dimensions of information use in the practice of science and how they are changing. This use-centric view is based on results from our studies of the role of information in varying modes of interdisciplinary science, our model of “weak” and “strong” information work in the research process, and field tests of a literature-based discovery (LBD) tool in neuroscience laboratories. I will also argue that as we add more direct investigation of research practice to our base of user studies, the unrealized potentials of our literature systems as tools and infrastructure for scientific discovery become more apparent.NSF CISE/IIS/DST 0222848unpublishednot peer reviewe