Boris Thome, Friederike Hertweck, Serife Yasar, Lukas Jonas, Stefan Conrad
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A dataset of study program availability in German higher education between 1971 and 1996.
Educational systems are dynamic. They shape human capital, technological and societal progress, and also economic growth. Higher education, in particular, fosters innovation, with varying fields of study contributing differently to this process. Yet, despite its importance, no dataset has previously documented the evolution of academic fields across higher education institutions in a specific country. Addressing this gap, we present the RWI-UNI-SUBJECTS1 dataset, the first extensive collection of study opportunities across German higher education institutions between 1971 and 1996. The dataset originates from annual study guides by the German Federal Employment Agency for high school students. To extract the data, a custom-developed computer vision algorithm was used. We further enriched the dataset with administrative codes for fields, institutions, and districts, enabling seamless integration with additional datasets, such as social security data, official student statistics, or the National Educational Panel Study (NEPS). Covering a total of 105,307 study programs between 1971 and 1996, RWI-UNI-SUBJECTS1 offers a valuable foundation for interdisciplinary research on education, innovation, and economic development.
期刊介绍:
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.