You can follow the UEA ReproducibiliTea Group on Twitter #ReproTeaUEA and contact them by email at ukrn.team@uea.ac.uk Dr Stephanie Rossit is the institutional lead.
Recordings of Previous events are available below.
Reproducible research ... Authors provide all the necessary data and the computer codes to run the analysis again, re-creating the results.
Replication: A study that arrives at the same scientific findings as another study, collecting new data (possibly with different methods), and completing new analyses.
Attribution: University of Illinois Library
See also: Definitions of Reproducibility and Replication, The Turing Way
UK Reproducibility Network (UKRN)
ReproducibiliTea national initiative with local institutional branches
Garret Christensen, Jeremy Freese and Edward Miguel (2019), Transparent and Reproducible Social Science Research : How to Do Open Science. Oakland, California: University of California Press. [Unlimited e-book access from UEA Library]
Berkeley Initiative for Transparency in the Social Sciences (BITSS), Transparent and Open Social Science Research (MOOC)
The Turing Way: Guide for Reproducible Research
Reproducibility and Research Integrity EasternARC
This academic year there will be taught sessions and drop in sessions available every month. There is a flyer attached detailing sessions in March and April.
Perhaps you have inherited a large code base as part of your research and you would just like some pointers on the best way to get to grips with it, or perhaps you have a bug you cannot fix and it is slowing your progress down?
If you have any questions or you would like to sign up to any of the sessions, let us know through the code clinic email address code.clinic@uea.ac.uk and the code clinic team will get back to you!
Thurs 25th April 2024 Building Diverse Interactive Research Outputs to Reach and Engage Different Audiences [Join via Teams 14.00-15.00], Dr Kacper Sokol, ETH Zurich.
Abstract: Despite immense technological advances finding their way into our everyday life and working practices, scientific publishing has seen much less evolution. While moving on from hand- or type-written manuscripts to electronic documents allowed for faster and more convenient editing, dissemination and review, the (now obsolete and unnatural) limitations of the "movable type" publication format persist. Among others, this glass wall poses significant challenges to effective communication of scientific findings with their ever-increasing volume, velocity and complexity. Open science, nonetheless, has the capacity to overcome these challenges as I will demonstrate in this talk. Kacper will discuss his experience with building bespoke publishing workflows aimed at generating multiple output formats – e.g., documents, computational notebooks and slideshows – from a single collection of source files. He will also review publishing toolkits such as Quarto and the Jupyter ecosystem as well as complementary technologies such as Jupyter Widgets, Reveal.JS and RISE. Since existing tools may not fulfil the needs of a particular use case, he will examine the possible customisation and extension of the aforementioned authoring environments. In the end, all of these technologies come together to help researchers create a suite of diverse and engaging online learning materials, thus better communicate their findings to distinct audiences without much technical overhead.
Short speaker bio: Kacper is a Research Fellow in the Medical Data Science group in the Department of Computer Science of ETH Zurich. His main research focus is transparency – interpretability and explainability – of data-driven predictive systems based on artificial intelligence and machine learning algorithms. In the past, he has worked on enhancing transparency of predictive models with feasible and actionable counterfactual explanations and robust modular surrogate explainers. He has also introduced Explainability Fact Sheets – a comprehensive taxonomy of AI and ML explainers – and prototyped dialogue-driven interactive explainability systems. Additionally, he designed and led the development of FAT Forensics – an open-source fairness, accountability and transparency Python toolkit. Kacper holds a doctorate in Computer Science from the University of Bristol, United Kingdom. Before joining ETH, he was a Research Fellow at the ARC Centre of Excellence for Automated Decision-Making and Society, affiliated with the RMIT University in Melbourne, Australia and had held numerous research positions at the University of Bristol, working with projects such as REFrAMe, SPHERE and European Union's AI Research Excellence Centre TAILOR.
Wed 21st February 2024 Annotating for Transparent Inquiry in qualitative research: making archival documents accessible [Recording now available], Dr Joseph O'Mahoney, University of Reading
Wed 24th January 2024 Transparent and Rigorous Political Research: Rationale, Contexts and Trends [Recording now available], Dr Eike Rinke, University of Leeds
Tuesday 14 November 2023 Achieving Reproducibility by Sharing Methods on protocols.io [Recording now available], Dr Emma Ganley, protocols.io
Wed 1 November 2023 Assessing quality in qualitative research: Challenges and opportunities [Recording now available], Dr Rebecca Whiting, Birkbeck
Wed 28th June 2023 Democritisation Without Dimunition - opportunities in global publishing for promoting equity and excellence in scientific communication [Recording now available], Professor Kevin Tyler, UEA
Wed 31st May 2023 Replication and Credibility of Research - An Economist's Perspective [Recording now available],, Associate Professor, Dr Maren Duvendack, University of East Anglia
Wed 26th April 2023 Gazing into the Abyss of p-Hacking [Recording now available], Dr. Angelika Stefan, University of Amsterdam
Wed 22nd February 2023 Robustness and Transparency in Scientific Methods, Statistics & Study Design [Recording now available], Dr. Daniel Lakens, Eindhoven University of Technology
Wed 25th January 2023 Enhance your academic writing and peer review with reporting guidelines [Recording now available], Dr Jennifer de Beyer, UK EQUATOR Centre's Training Programme, University of Oxford
Wed 7th December 2022 The establishment of the Global Reproducibility Network [Recording now available], Professor Marcus Munafo, University of Bristol
Wed 23rd November 2022 FAIRsharing.org: scientific databases [Recording now available], Dr. Allyson Lister, University of Oxford
Wed 26th October 2022 Practice of Sharing Synthetic Datasets
ReproducibiliTea is a world-wide network of open research (journal) clubs that discuss ideas about improving transparency and reproducibility in research work, and the open research movement at a larger scale.
The UEA section of ReproducibiliTea was set up in November 2021 by PhD students and ECRs across all faculties who were local leads for the UK Reproducibility Network (UKRN): Prerna Aneja; Dr. Ann-Kathrin Johnen; Dr. Amanda Burke; Dr. Kamran Qureshi; Dr. Gonçalo da Silva.
UEA joined the UKRN in 2021 and our institutional lead is Dr. Stéphanie Rossit. The UKRN is peer-led consortium that aims to ensure the UK retains its place as a centre for world-leading research. They do this by investigating the factors that contribute to robust research, promoting training activities, and disseminating best practice.
The main aim of the UEA ReproducibiliTea sessions is to support researchers from all career stages (from students to professors) in navigating the possibilities and challenges that the open research movement brings about. Through these sessions, the organisers hope to encourage researchers to adopt more open research practices and show them the benefits of doing so on both an individual and community-level.
These events take place on the last Wednesday of the month. For more info, please contact ukrn@uea.ac.uk
Follow us on Twitter for more Open Research updates: ReproTeaUEA
YouTube channel [session recordings]