Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature
This work addresses the problem of limited data access for developing lay summarization tools, which can broaden public understanding of science, but it is incremental as it focuses on dataset creation rather than novel methods.
The authors tackled the lack of large-scale datasets for lay summarization of scientific literature by introducing two new biomedical datasets, PLOS and eLife, which include expert-written lay summaries, and they benchmarked these datasets to show their utility and highlight key challenges.
Lay summarisation aims to jointly summarise and simplify a given text, thus making its content more comprehensible to non-experts. Automatic approaches for lay summarisation can provide significant value in broadening access to scientific literature, enabling a greater degree of both interdisciplinary knowledge sharing and public understanding when it comes to research findings. However, current corpora for this task are limited in their size and scope, hindering the development of broadly applicable data-driven approaches. Aiming to rectify these issues, we present two novel lay summarisation datasets, PLOS (large-scale) and eLife (medium-scale), each of which contains biomedical journal articles alongside expert-written lay summaries. We provide a thorough characterisation of our lay summaries, highlighting differing levels of readability and abstractiveness between datasets that can be leveraged to support the needs of different applications. Finally, we benchmark our datasets using mainstream summarisation approaches and perform a manual evaluation with domain experts, demonstrating their utility and casting light on the key challenges of this task.