Information science stands out as a particularly heterogeneous and multidisciplinary academic discipline whose thematic boundaries and foci are constantly evolving dynamically through societal needs and under the influence of a technological imperative. These circumstances make it significantly more difficult to automatically identify relevant dissertations for the discipline through existing classification systems e.g the Dewey Decimal Classification. To solve this problem, an approach is to be developed that goes beyond the existing metadata to include further attributes such as institutes or persons involved from corresponding full texts or online sources for identification. The aim of the project is to create a corpus of dissertations relevant to information science and to conduct a descriptive analysis based on this corpus with regard to thematic trends in the discipline.

This project if funded by the German National Library (DNB) as a DH fellowship. As one of Germany’s great memory institutions, the German National Library makes its data stock and digital collections available for science and research and for creative experimental work as far as this is technically and legally possible. This year, DNB published their first ever call for applications for digital humanities fellowships (DH fellowships), which will enable their holders to research DNB data and collections using methods employed in text and data mining.