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Boundaries, Borders, and Information Needs: Examining Concepts in Information Systems

This talk addresses epistemology, or how we know what we know, of data and data science. It examines concepts and authors as links between science, information, and knowledge, as well as natural and constructed boundaries. Using Star and Griesemer鈥檚 notion of the boundary object I argue two points: 1) that boundaries are useful aids in examining the thematic and sociological currents in information and 2) that concepts themselves can serve as practical aids in information seeking. This is important in order to understand and analyze the creation and surrounding contexts of knowledge, in addition to shortening the time for serendipity in information seeking (Foster and Ford, 2003). Work presented in this talk used a domain-centric approach for the broad transdisciplinary area of cognitive science. Data spanning the years 2006-2016 were drawn from the Web of Science庐 using a seed and expand approach for journals containing the string 鈥渃ogni*,鈥� and analyzed against the National Science Foundation classification of scientific journals using natural language processing. Title data were processed to extract and compare boundary-spanning concepts temporally, and show an increase in the diversity of conceptual content in the core of cognitive science. Boundary-spanning concepts are addressed, and the case of Alzheimer鈥檚 Disease as a boundary concept is addressed. A test case surrounding the complex information problem of rage from the perspective of youth is used to illustrate the practicality of this approach to aid in the information retrieval process. Next steps for analysis and studies are outlined, showing an exciting potential for future work in concept-based classification and retrieval to assist in our understanding of how knowledge is created, stored, and how to better use knowledge stored in information systems