@incollection{WittDiesnerSteffenetal.2018, author = {Andreas Witt and Jana Diesner and Diana Steffen and Rezvaneh Rezapour and Jutta Bopp and Norman Fiedler and Christoph K{\"o}ller and Manu Raster and Jennifer Wockenfu{\"s}}, title = {Impact of scientific research beyond academia: an alternative classification schema}, series = {Proceedings of the LREC 2018 workshop. 1st workshop on computational impact detection from text data. 08 May 2018 – Miyazaki, Japan}, editor = {Jana Diesner and Georg Rehm and Andreas Witt}, publisher = {European language resources association (ELRA)}, address = {Paris, France}, isbn = {979-10-95546-05-4}, url = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-74679}, pages = {34 -- 39}, year = {2018}, abstract = {The actual or anticipated impact of research projects can be documented in scientific publications and project reports. While project reports are available at varying level of accessibility, they might be rarely used or shared outside of academia. Moreover, a connection between outcomes of actual research project and potential secondary use might not be explicated in a project report. This paper outlines two methods for classifying and extracting the impact of publicly funded research projects. The first method is concerned with identifying impact categories and assigning these categories to research projects and their reports by extension by using subject matter experts; not considering the content of research reports. This process resulted in a classification schema that we describe in this paper. With the second method which is still work in progress, impact categories are extracted from the actual text data.}, language = {en} }