(900) DETECTING CENTRAL RESEARCH RESULTS IN RESEARCH ALLIANCES THROUGH TEXT MINING ON PUBLICATIONS

摘要

Not only in the German research landscape, the establishment of research alliances has become akey element of the national funding structure, especially in order to address current societal, economicand scientific problems. These complex problems are mutually investigated by heterogeneous actorswhose heterogeneity can be mainly seen in a combined research effort of scientific as well asbusiness-driven research - a so-called transdisciplinary research approach. The main challenge whicharises from this approach covers the cooperation of numerous actors in a complex and oftenintransparent collaboration structure. To allow transparence of the central research topics within thesestructure, publication data has to be consolidated and classified.In order to address this challenge, the establishment of an information management environmentsupports the ability to handle big repositories of publication data on the one hand and to visualizedifferent thematic interests on the other hand. In this example, fostering cooperation among actors, byrevealing thematic accordance, connections and development, becomes possible.The paper addresses the question in how far an information management environment can supportthis revealing process by means of classification publication data. Focusing on an informationmanagement environment in its pre-prototypic stage, the development process as well as initial resultsare presented. The results are derived from publication data examined by the transdisciplinaryresearch alliance “Innovative capability in demographic change” initiated by the German FederalMinistry of Education and Research (BMBF).