From Static to Dynamic: LivePublication and the quest for reproducible, living articles

Within the computational sciences, it is intuitive that our research publications are primed to derive more value from integrations across eScience technologies, with substantive efforts being made towards supporting reproducibility and reuse.  Early Research Software Environments (RSEs) and Executable Articles (EAs) paved the for how we conceptualise computational tools and their relationships to our publication containers. More modern platforms such as WholeTale and Binder Hub containerise Literate Programming Environments (LPEs), combining reproducible code, data, and narrative, which have been popularised in the academic publication context. 

In this talk I expand on the previously discussed LivePublication framework---a framework designed to enable the automated generation and modification of scientific articles. LivePublication addresses the challenges of reproducibility within academic articles, and develops upon existing technologies to enable live and dynamic updates to academic articles as new results are generated from experiment interfaces. LivePublication does not set out to create a bespoke, centralised platform for the deployment of live, reproducible publication containers. Instead, it seeks to integrate existing off-the-shelf eScience technologies, from Workflow Management Platforms (WMPs) to LPEs.

ABOUT THE AUTHORS

Mark Gahegan is Professor in Computer Science at the University of Auckland, where he also directs the Centre for eResearch. He is PI of ‘Beyond Prediction…’, a large, 7-year Data Science Programme Grant from MBIE. His research interests are in eScience, GIScience, Data Science and all points in between.

Gus Ellerm is a PhD student in Computer Science at the University of Canterbury and research fellow at the University of Auckland. Currently, they are studying research workflows and their role in supporting live publications. Gus leads the implementation of the work reported here, is funded via the above MBIE grant and is supervised by Ben Adams and Mark Gahegan. Gus has recently been invited to present his work at the Globus World`24 conference.

Ben Adams is Associate Professor of Computer Science and Software Engineering at the University of Canterbury. His research interests revolve around new ways to use computing technology to help advance human understanding of our environment and world, drawing from data science, spatial science and cognitive science.

Nelis Drost Cornelis is a complex systems modeller with experience in fields including ecology, archaeology, oncology and epidemiology. Having experience developing both models and analyses in an academic setting, and production software in a commercial setting, he now works as a Snr. Solutions Specialist at the Center for eResearch, where he supports researchers with modelling, data visualization and software development. https://orcid.org/0000-0002-7355-9978

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