Observing Data-Driven Approaches to Covid-19: Reflections from a Distributed, Remote, Interdisciplinary Research Project
DOI:
https://doi.org/10.19164/jlrm.v1i1.1160Abstract
The Observatory for Monitoring Data-Driven Approaches to Covid-19 (OMDDAC) is an Arts and Humanities Research Council funded research project investigating data-driven approaches to Covid-19, focused upon legal, ethical, policy and operational challenges. The project is a collaboration between Northumbria University (Law School, Department of Computing and Information Sciences, Department of Mathematics) and the Royal United Services Institute, a defence and security think-tank, and aims to carry out integrated interdisciplinary research, regarded as the most challenging type of interdisciplinarity but where the outputs can be the most impactful. Due to the constraints of the pandemic, the project has been carried out in a fully distributed and remote manner, with some team members never having met in person. The subject of the research is continually changing and developing, creating unique project management issues, with the impact of the pandemic pervasive in the lives of the researchers. This article takes the form of a series of reflections from the points of view of individual project researchers – the specialist legal researcher, the think-tank Co-Investigator, the post-doctoral researcher, statistical and data science researchers, and the Principal Investigator – and organised under two main themes - project management and internal communication; and methodologies/interdisciplinary research. We thus draw out lessons for future remote and distributed research, focused upon interdisciplinarity, the benefits and challenges of remote research methodologies, and issues of collegiality. Finally, we warn that it will be a false economy for universities and funders to assume that research projects can continue to be conducted in a mainly remote manner and therefore, that budgetary savings can be made by reducing time allocations, travel and academic networking.
Published
Issue
Section
License
Copyright (c) 2021 Rachel Allsopp, Claire Bessant, Keith Ditcham, Ardi Janjeva, Guangquan Li, Marion Oswald, Mark Warner
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).