Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 10589 - 10604 December 7-11, 2022 ©2022 Association for Computational Linguistics Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature Tomas Goldsack1, Zhihao Zhang2, Chenghua Lin1∗, Carolina Scarton1 1Department of Computer Science, University of Sheffield, UK 2School of Economics and Management, Beihang University, China {tgoldsack1, c.lin, c.scarton}@sheffield.ac.uk zhhzhang@buaa.edu.cn Abstract Lay summarisation aims to jointly summarise and simplify a given text, thus making its con- tent more comprehensible to non-experts. Au- tomatic approaches for lay summarisation can provide significant value in broadening access to scientific literature, enabling a greater de- gree of both interdisciplinary knowledge shar- ing and public understanding when it comes to research findings. However, current cor- pora 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 con- tains biomedical journal articles alongside expert-written lay summaries. We provide a thorough characterisation of our lay sum- maries, highlighting differing levels of read- ability 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 util- ity and casting light on the key challenges of this task. Our code and datasets are avail- able at https://github.com/TGoldsack1/ Corpora_for_Lay_Summarisation. 1 Introduction Scientific publications contain information that is essential for the preservation and progression of our understanding across all scientific disciplines. Typ- ically being highly technical in nature, such articles tend to assume a degree of background knowledge and make use of domain-specific language, making them difficult to comprehend for one lacking the required expertise (i.e., a lay person). These factors often limit the impact of research to only its direct community (Albert et al., 2015, 2022) and, more 1∗Corresponding author. Technical Abstract The virus SARS-CoV-2 can exploit biological vulner- abilities (e.g. host proteins) in susceptible hosts that predispose to the development of severe COVID-19. To identify host proteins that may contribute to the risk of severe COVID-19, we undertook proteome-wide ge- netic colocalisation tests, and polygenic (pan) and cis- Mendelian randomisation analyses leveraging publicly available protein and COVID-19 datasets... Lay Summary Individuals who become infected with the virus that causes COVID-19 can experience a wide variety of symptoms. These can range from no symptoms or minor symptoms to severe illness and death. Key demographic factors, such as age, gender and race, are known to affect how susceptible an individual is to infection. However, molecular factors, such as unique gene mutations and gene expression levels can also have a major impact on patient responses by affecting the levels of proteins in the body... Figure 1: The first few sentences of the abstract and lay summary of an eLife article, illustrating differences in the language and focus on background information. dangerously, can cause readers (members of the public, …

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