Developing the Management Studies Community: Data Science Workshops

Supported by SAMS, BAM Ebusiness & Egovernment SIG, Coventry University, Queen Mary University of London, Newcastle University Business School,

Organisers: Prof. Maureen Meadows, Dr Panos Panagiotopoulos, Prof. Savvas Papagiannidis

This is the 2nd of the three data science workshop organised. For more information about this event series, please click here.


The event is free to attend. As there are limited spaces you need to register before attending. To register please email: Prof Maureen Meadows . Thanks to the generous support provided by SAMS and the BAM Ebusiness & Egovernment SIG we can offer a number of travel bursaries to doctoral students (first-come-first-served basis).

Doctoral and Early Career Researcher Symposium

New forms of data, data science and data analytics have reshaped social science research over the past years. Rapid growth has been spurred on by the proliferation of complex and rich data in science, industry and government, which are potentially available for research. As a result, (big) data analytics are no longer the preserve of engineering and computer science students, but as big datasets are increasingly becoming common in most domains, analytical skills have become essential to most fields of study and practice, and certainly to social science and Business School students. These trends have set new expectations about research questions, data collection and analysis methods as well as the general skills of doctoral students in social science research. Social science doctoral programmes have responded to the challenge of integrating new methods at the intersection of the computational and social sciences with new programmes and communities. Beyond these specialised programmes, the vast majority of doctoral courses have not caught up methodologically with advances in the area or are not able to harness the potential fully.

Location: The Techno Centre, Coventry University Technology Park, Puma Way, Coventry CV1 2TT (MAP)
Room: CC1.3

Programme: Thursday 11th of May 2023

11th of May

09.00 – 09.30

Arrival and registration (Ground floor, Techno Centre)
Coffee (Room CC1.3)

9.30 – 09.45

Welcome by the workshop organisers

09.45 – 11.00

Dr Kit Windows-Yule, University of Birmingham: "Data Science: Case Studies, Hints and Tips"
Kit Windows-Yule is a Turing Fellow, a two-time Royal Academy of Engineering Industrial Fellow, and an Associate Professor in Chemical Engineering, working jointly with the School of Physics and Astronomy’s Positron Imaging Centre.

11.00 – 11.30

Coffee Break

11.30 – 12.30

Dr Martin Wain, Associate Director, RSM UK, and Dr Jo Ferrie, Senior Lecturer in Sociology at Glasgow University: Future Proofing the Social Sciences: Skill Gaps and Support for Data Driven Research
Martin Wain is an experienced researcher and project manager with expertise in designing and applying qualitative and quantitative data collection and analytical methods. Jo Ferrie is known as a pioneer in the teaching of research methods at the University of Glasgow as founding Director of Glasgow Q-Step. She has delivered a training vision that meets student's needs and an evidence base of training needs data shared across the Doctoral Training Partnership of 16 universities. Martin and Jo (with Simon Gallacher, John Macinnes and Technopolis Group) are co-authors of ‘Scoping the Skills Needs in the Social Sciences to Support Data Driven Research’ (ESRC, 2022).

12.30 – 13.30


13.30 – 14.45

Dr Huma Shah, Research Centre for Computational Science and Mathematical Modelling, Coventry University: Validating citizen scientists’ data collection: a perspective from an EU funded project on GDPR compliance
Huma is Director of Science (Co-Investigator) in the EU Horizon2020 research and innovation project CSI-COP. Coventry University lead the international nine-partner CSI-COP team winning 'Best Innovative Privacy Project' in the inaugural PICCASO Privacy awards in December 2022. CSI-COP applies a citizen science approach investigating tracking-by-default and GDPR compliance in websites and smart phone apps (see and

14.45 – 15.00

Coffee Break

15.00 – 16.15

Tackling data science problems in research: Group discussion and networking

16.15 – 16.30

Wrap-up and Close