Professionalising traditional and infrastructure research roles in data science

Table of Content

About the project
Who are we
Get in touch
Find out more

About the Project

In the ever-evolving landscape of data science, specialised roles have become integral to supporting interdisciplinary collaboration and guiding the adoption of open, reproducible, inclusive and ethical practices. This project aims to address the gap in the policy landscape that would standardise and strengthen specialised research infrastructure roles alongside the traditional roles in data science. The goal is to professionalise dedicated specialised as well as general roles for ensuring high-quality ethical research at institutional and national levels.

An image of the modern research environment filled with research engineers, community managers, research application managers and data stewards

The Turing Way project illustration by Scriberia. Zenodo. http://doi.org/10.5281/zenodo.3332807

What this project is about and why is it important

The National Audit Office report on ‘Challenges in using data across government’ highlights the current gap in data skills at several levels including storage, management, architecture, planning and governance. The majority of these skills are essential for traditional data science research roles, and even more important for professionalising modern roles such as research engineers, data stewards, community managers, research application managers and more. These modern roles are often termed research infrastructure roles and are becoming important alternative career pathways for researchers.

The skills gap identified by the National Audit Office is compounded by a lack of clarity in definitions for data science roles and their skill requirements. The National Data Strategy states that there is no widely agreed definition of data skills and the role descriptors are used inconsistently across different institutions. Therefore, to enable the upskilling of the current workforce, develop more national and international consistency in hiring practices for these roles, and identify the skills needed by the next generation of data professionals, we need to close this knowledge gap by developing clear definitions of roles in data science and the skills needed to perform these roles.

This project seeks to lead in this area in collaboration with experts and diverse stakeholders curating both traditional and modern data science roles and skills to move forward with their professionalisation. These curated resources will be communicated broadly to inform national policies.

For additional detail, please read the full Proposal for this project.

What we want to do

The objectives of this project are:

Curating and centralising definitions, role descriptors and skill lists for traditional and modern data science roles in collaboration with stakeholders from national and international institutions -- for use in policy, hiring and career development.
Publishing a position paper focused on the newly established Community Management team in The Alan Turing Institute's Tools, Practices and Systems Programme and making comparisons to other data science roles professionalised at the Turing. This will serve as a prototype for creating position papers on other modern and lesser established data science roles.
For the project leads to gain relevant skills by working with policy experts, networking with other awardees and collaborators, and utilising resources enabled by the Skills Policy Award in developing high-quality outputs that strengthen policies for the professionalisation of modern data science roles alongside the traditional roles in the UK.

Where would we engage with different contributors

We want to engage with different organisations and individuals to collect information, resources and policies about the data science roles created by different institutions in the UK and internationally.

Different contributors and collaborators will help us address some of the following questions:

what data science roles they have created, supported or worked on?
what roles, responsibilities and specific tasks do these roles involve?
what skills are required for these roles?
what job descriptors exist for creating these roles?
what career development pathway do these roles have?

If you have the answer to some or all of these questions, please connect with us and look out for upcoming workshops and networking events.

Who we are

This project very much encompasses key aspects of the Turing's Tools, Practices and Systems Programme (TPS) research programme that works towards supporting and demonstrating how teams of research infrastructure professionals can add value and impact to research projects.

Two TPS members leading this project are:

Emma Karoune

Emma works in the Tools, Practices and Systems Programme as a Senior Research Community Manager. She oversees community management in the Turing Health programme including working with the Turing-RSS Health Data Lab and the DECOVID project. She is a core contributor to The Turing Way (an open-source community-led guide to reproducible research), and a member of the Bookdash planning committee, helping to build resources and training for other researchers. Emma's research background is in archaeobotany and she has been leading a project at Historic England on FAIR data.

Find out more about Emma's research work here: Emma Karoune Turing Profile and Emma's orcid record.

Malvika Sharan

Malvika is a Senior Researcher in the Tools, Practices and Systems research programme. She is leading Open Research at The Alan Turing Institute and establishing a growing team of research community managers. She is a co-lead investigator of The Turing Way project – a community-led handbook on data science, that aims to make research reproducible, collaborative, ethical and inclusive for researchers around the globe.

Find out more about Malvika's research work here: Malvika Sharan Turing Profile and Malvika's orcid record.

They will engage all the members of the TPS programme who will have opportunities to input on this project and highlight the work that they are currently doing in this area. This work will be closely aligned with and conducted in collaboration with the Turing Skills Team, as well as other awardees of the Skill Policy Awards.

Project updates

See detailed project reports here

Multi-stakeholder workshop will be hosted at The Alan Turing Institute on 2 October 2023.
Skills framework for Research Community Managers
- Sharan, Malvika, & Karoune, Emma. (2023). Research Community Management - Skills framework. Zenodo. https://doi.org/10.5281/zenodo.8337627