Open Research Community Management

Introduction

Building communities in data science is crucial for bringing together diverse stakeholders, enabling knowledge exchange and co-creating a collaborative system in which AI research can thrive. At the Turing, this vision is realised by the integration of Research Community Managers (RCMs) in projects where multiple internal and external stakeholders are involved. As the visible and most connected member of the project, they apply Open Research and Community Management approaches to foster Communities of Practice in the Turing’s work.

RCMs are professionals responsible for fostering a collaborative environment where a diverse research and data science community can actively engage, get recognition and build shared agency over their work.

RCMs at the Turing embed open, inclusive and reproducible research practices in teams, projects and programmes they are involved in. Through collaboration, upskilling and resource development, RCMs build a shared understanding of research goals, roadmap and processes for everyone. They collaborate closely with different stakeholders and make implicit knowledge explicit so that everyone who wants to can participate.

Pre-print describing our work on professionalising community management in data science is out! Read it on ArXiv: https://doi.org/10.48550/arXiv.2409.00108

RCMs are uniquely positioned to connect disparate teams, initiatives, and resources across the organisation, fostering more resilient communities of practice that drive innovation, improve project outcomes, and create a stronger, more connected ecosystem with broader impacts.

Cite it as: Sharan, M., Karoune, E., Hellon, V., van Praag, C. G., Kayumbi, G., Bennett, A., Araujo Alvarez, A., Lee Steele, A., Batchelor, S., Lacey, A., Whitaker, K. (2024). Professionalising Community Management Roles in Interdisciplinary Research Projects. ArXiv e-prints, 2409.00108. https://doi.org/10.48550/arXiv.2409.00108

Explaining the science

RCMs combine a range of socio-technical skills including domain research expertise, scientific communications and stakeholder engagement approaches. Among others, their core responsibilities include ensuring access to skills and resources different people and groups within the project need to meaningfully participate and build something greater than the sum of its part. Together as a team, they build an interconnected system of open source and reproducible software, data, people and processes. By sharing knowledge as they develop in different projects, both in terms of scientific outcomes and socio-technical approaches applied to achieve them, RCMs break down the silos that traditionally exist in research environment.

All RCMs are members of the Tools, Practices and Systems Research Programme. They are active community members of The Turing Way -- an open research, open collaboration, and community-driven handbook on data science. Drawing from their engagement in The Turing Way, the RCMs facilitate the integration of reproducible, interoperable and collaborative processes in technical as well as the social infrastructure of the Turing's research and data science projects.

This includes, but not limited to:

Identifying the need of community workflow and processes in a project, curating best practices from The Turing Way and integrating them in their work.
Highlighting gaps in the current resources, writing new content required in their projects and engaging members from the Turing to share knowledge from their work openly via the handbook.
Presenting about the project and training new audiences in practices related to open source, reproducibility, collaborative research and ethics.
Welcoming members of the Turing project communities to engage in The Turing Way and contributing to the design of governance and decision making processes.
Facilitating and participating in discussions on research and community best practices throughout the project lifecycle.

Project aims

The Research Community Management teams at the Turing are crucial for ensuring that the research projects, processes and outcomes that are created in the Institute are maintained, sustained and made easy to build upon by others. As key members of the Tools, Practices and Systems research programme, RCMs advance and scale the bidirectional flow of knowledge, resources and evidence for high-quality research within the Institute. As a team, they ensure that research and data-driven AI solutions at the Turing use, build on and create open research and open source tools, practices and systems. They exchange expertise and knowledge around community management and research practices with each other, while providing peer-mentoring, networked support and space to learn from each other.

Through their connections with diverse stakeholders they connect the research with national and international data science communities. The goal is to make research and innovation more effective across the national and international data science ecosystem and advance community-oriented/community-led public interest technologies.

tps graphic

This image was created by Scriberia for The Turing Way community and is used under a CC-BY 4.0 licence.

Applications

The Turing Way

The Turing Way is an open source, open collaboration and community-driven handbook on reproducibility in data science and research. Dr Kirstie Whitaker, Director of Tools, Practices and Systems, and Dr Malvika Sharan, TPS Senior Researcher for Open Research and co-lead of the Open Research Community Building team, are the project leads. Anne Lee Steele is the Research Community Manager who facilitates collaborations across multiple community efforts in The Way Turing and beyond. Please see the impact report and contribute via the online GitHub Repository.

Arielle Bennett is TPS Senior Researcher for Open Source Practices and leads The Turing Way Practitioners Hub as part of the Innovate UK Bridge AI programme.

Health Grand Challenge

Dr Emma Karoune is the TPS Principal Researcher for Research Community Building and co-lead of the Open Research Community Building team. She works on multiple projects across Turing. She has provided community management expertise and support previously in Health focused projects DECOVID, and the Turing-RSS Health Data Lab. She is currently strategically embedding community management work in the Health Grand Challenge. She has also been offering her expertise to the AI for Multiple Long term Conditions - Research Software Facility and is currently an organiser of the Clinical AI Interest Group. She is a core team member of The Turing Way, and sits in the Planning Committee of The Turing Way Book Dash.

Professionalisation of Data Science roles and skills

Dr Emma Karoune and Dr Malvika Sharan were awardees for the Skills Policy Award in 2023 and have been leading community research on the professionalising data science roles project. This project has led to Emma now co-leading the People in Data project that aims to convene an open community of data professionals, which promotes a culture that values and prioritises data and recognises people that work in data roles as essential to research and leading the MRC funded Advancing Biomedical Science Data Science Careers project started in February 2025.

AI for multiple long-term conditions: Research Support Facility (AIM RSF)

Sophia Batchelor is the Research Community Manager for the Patient, and Public Involvement and Engagement (PPIE) Theme in AIM RSF and Emma Karoune is coordinating the AIM ECR network. In this programme, the Alan Turing Institute, in conjunction with Swansea University and the University of Edinburgh, is developing data standards, disseminating best practices, and building community around researchers, patients and the public involved in AI for multiple long-term conditions research.

Innovate UK BridgeAI

Alexandra Araujo Alvarez is the Senior Research Community Manager for the Innovate UK BridgeAI. BridgeAI is an Innovate UK-funded programme with a mission to drive the adoption of Artificial Intelligence (AI) and machine learning (ML) in sectors of the UK economy with high potential for growth for AI. The priority industries for the programme are transport, construction, agriculture, and the creative industries. By doing so, BridgeAI aims to promote AI-driven productivity and efficiency gains, which will support the UK's transition to an AI-enabled economy.

Data/Culture

André Piza is the Senior Research Community Manager for Arts & Humanities. He is currently focusing on the Data/Culture project, which is a sandbox to boost re-use of data and tools in the humanities and arts, in ways that develop high-quality research and strong collaborative communities.

Environment and Sustainability Grand Challenge

Dr Cass Gould Van Praag is the Senior Research Community Manager for the Environment and Sustainability Grand Challenge (E&S GC). E&S GC aims to to catalyse the next big changes in addressing the climate and biodiversity crisis by leveraging data science and AI.

Data Centric Engineering

Dr Gabin Kayumbi is the Senior Research Community Manager for the Data Centric Engineering (DCE) programme. DCE is a strategic partnership between the Lloyd’s Register Foundation and the Turing to bring academic and industrial partners together to address new challenges in data-centric engineering

Academic Engagement Team

Denise Bianco collaborates with the RCM team to embed community management expertise in the Skill Team's work within the Connections Initiative (network of PhD students across the UK).

Widening Participation Team

Ayesha Dunk represents our connection with the Widening Participation team (previously the Academic Engagement Team) and will be designing the Summer Experience 2024 to engage young students with data science and AI. Ayesha is a chair of the data science education interest group and previously led the Data Science and AI Educator's programme, which aims to embed data science and AI training across a range of disciplines, help overcome barriers to data science and AI training practices by empowering domain experts to become educators and stimulate the development of open and inclusive learning materials and curricula. The project directly used the OLS' (previously Open Life Science) cohort-based training approach and reused organisation materials.

Turing-Roche Strategic Partnership (Previous)

The 'North Star' of the Turing-Roche five-year partnership is to enable the generation of insights to better understand patient and disease heterogeneity and its relevance to clinical outcomes at an unprecedented level of precision in order to improve clinical care. Vicky Hellon is designing and leading multiple community activities to engage researchers and stakeholders in the programme to work towards our North Star. In the process, she will help build strong connections and collaborations between The Alan Turing Institute, Roche and the wider community.

The Turing Commons Team (Previous)

Claudia (Clau) Fischer was a Research Assistant for Data Justice and Global Ethical Futures on the Ethics and Responsible Innovation Team at The Alan Turing Institute. At Turing, she worked on the Turing Commons project, as well as other projects which focus on the ethics of regulating data-based and AI systems. In this team, Clau helped strengthen TPS/The Turing Way's connection with the Turing Commons project while transferring community management expertise through her work.

Turing-Crick Strategic Partnership: Data Science for Biomedical Scientists Project (Previous)

The Data Science for Biomedical Scientists training project is funded by AI for science and government. Led by Malvika, training materials have been co-developed by Lydia France and Federico Nanni from Research Engineering Group and with the contributions from Arron Lacey, Kasra Hosseini, Alden Conner and The Turing Way community. Training resources from this project are targeted to the senior researchers to help them build a foundational understanding of AI and data science (currently written in the context of biosciences). Furthermore, researchers will receive accessible resources to help manage, supervise and facilitate open and reproducible research for the wider biology community. This project massively reuses The Turing Way chapters and builds on The Carpentries and OLS practices. See the project details and training materials on GitHub.

Early Detection of Neurodegenerative Diseases Initiative (Previous)

Dr Arron Lacey was the Senior Research Community Manager on the Early Detection of Neurodegenerative Diseases (EDoN) initiative led by Alzheimer's Research UK. He applied his experience in Machine Learning to help the EDoN initiative deliver on EDON's goal. EDoN aims to detect cognitive decline due to biological ageing before symptoms show in the brain, making current treatments more effective, such as by building a digital toolkit consisting of mobile apps, Fitbit and cutting-edge passive EEG monitoring to help detect signals of early cognitive decline.

AI for science and government (Previous)

In ASG, Community Management expertise from this team has enabled the development of communication outputs, including formal reports as well as impact stories, highlighting: the research contribution of the ASG programme, the unique role ASG plays in cultivating diverse endeavours and the influence of the Turing’s network-convening capability ASG's work. ASG has also funded The Turing Way project, which forms the main reference for this team.