Professor Kerina Jones
Biomedical Sciences
Telephone: (01792) 602764
Room: Cellular Office - 305
Third Floor
Data Science Building
Singleton Campus

Kerina is a Professor of Population Data Science at Swansea University Medical School. She is the Associate Director for Information Governance and Public Engagement (IG&PE) to ensure data protection and to maximise socially-acceptable data utility across the various Swansea University-based Population Data Science initiatives, including: the SAIL Databank, Administrative Data Research Centre Wales, and the HDRUK collaboration. Her work spans the spectrum of Ethical, Legal and Societal Implications (ELSI), recognising the importance of social acceptability. Kerina established an active Consumer Panel to advise on research and developments in Population Data Science.

The Population Data Science initiatives hosted at Swansea University are world renowned. Kerina is internationally acknowledged as having an essential and unique leadership role in these initiatives, by focusing on innovative data governance models and public engagement to enable person-based data to be used effectively and safely. This is a rapidly developing field with changes to regulatory & governance frameworks and evolving societal perceptions. Kerina leads an innovative research programme centred on IG&PE that includes work to inform cross-centre data sharing and how emerging data types, such as genetic data, and free-text data, can be used safely in conjunction with health and administrative records.

Kerina led the active Innovative Governance working group of the UK Farr Institute from 2013 until its conclusion in 2018. At the outset, the balance was tipped towards being overly protective at the expense of innovation and learning to improve health through population data science. This left both regulators and the research community confused and ill-equipped to work harmoniously when they needed clarity and collaboration. Her group pioneered innovative practical solutions for using people’s health data safely and in a socially-acceptable way. The members are held in high esteem and continue to work collaboratively to advise and influence the developing data governance landscape to promote the safe reuse of data. 

Kerina is the founding Editor-in-Chief of the International Journal of Population Data Science (IJPDS), an electronic, open-access, peer-reviewed journal focussing on the science pertaining to population data, and publishing articles on all aspects of research, development and evaluation connected with data about people and populations.

Areas of Expertise

  • Data linkage: research
  • Data linkage: methodologies and governance
  • Information governance for data-intensive research
  • Public engagement


  1. Jones, K., Ford, D., Ellwood-Thompson, S., Lyons, R. A Profile of the SAIL Databank on the UK Secure Research Platform International Journal of Population Data Science 4 2
  2. Jones, K., Heys, S., Daniels, H., Ford, D. Exploring barriers and solutions in advancing cross-centre population data science International Journal of Population Data Science 4 1
  3. Jones, K., Daniels, H., Squires, E., Ford, D. Public Views on Models for Accessing Genomic and Health Data for Research: Mixed Methods Study Journal of Medical Internet Research 21 8 e14384
  4. Jones, K., Heys, S., Tingay, K., Jackson, P., Dibben, C. The Good, the Bad, the Clunky International Journal of Population Data Science 4 1
  5. Jones, K., Daniels, H., Heys, S., Ford, D. Public Views on Using Mobile Phone Call Detail Records in Health Research: Qualitative Study JMIR mHealth and uHealth 7 1 e11730

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  • PM-348 Data to Decisions

    The module gives students an understanding, not only of the importance of using data, but of doing so safely and effectively to inform decision-making for population health and well-being. It covers five staged themes (forming a repeating cycle) and one cross-cutting theme: Stages: 1. Data provenance and collection 2. Data sharing platforms, formats and management 3. Data-intensive research 4. Evidence-based policy and practice development 5. The application of data in decision-making, which loops back to point 1. Cross-cutting theme: 6. Data in context This cross-cutting theme covers data governance, and the legal, ethical and societal (ELSI) issues in the safe use of person-based data for research, development and evaluation initiatives leading to evidence-based decisions. As well as the benefits of data use, it brings in harm that occurs when data are misused, and the harm that occurs to individuals and burdens to society when data cannot be used effectively. This module introduces students to the fundamental concepts, theories and applications of data use within a population health context. It explores the practical issues of dealing with large amounts of routinely collected health data, and the ways these data can be used to in evidence-based medicine. Topics will cover data linkage, data analytics, data governance, bias in data, emerging forms of data and innovations in data visualization.

  • PM-349 Global Population Health: future opportunities and challenges

    This module consolidates global issues on the social, economic, political and environmental determinants of population size, structure and population health in both, high income countries as well as low and middle income countries from a multidisciplinary approach including social sciences, epidemiology, demography and public health. Topics include the relationship health and economic change; social support, social capital and health; policy responses to inequalities in health; prospects for mortality and morbidity change; urbanization and its implications for health, poverty, population change and inequalities; the `double burden┬┐ of disease and its consequences; the roles of nutrition an obesity for health of populations; emerging and current infectious diseases; the global burden of mental health disorders; and priorities for health improvements for low income countries. Throughout the module, students are encouraged to consider potential future opportunities and challenges for global population health.

  • PM-401 Science Communication

    This module will encompass a range of communication modes, from presentation of science to the general public to making a pitch for funding to `investors┬┐ The module will be run as a series of online seminars to prepare, firstly, for a short 3 minute thesis-like presentations to both a professional and non-professional audience. This will be complemented by preparation of short, New Scientist-style articles by each student on the topic of their presentation. Students will be assigned a topic that is appropriate to their degree title. For example, a Medical Geneticist could address recent advances in gene therapy. Subsequently, their task will be to produce a pitch to attract investment to commercialise their research. In the latter half of the module, the focus will be on skills-training for writing a scientific paper, preparing the ground for their project dissertations.

  • PMGM13 Ethical, Legal and Societal Issues (ELSI) in Applied Genomics

    This module will provide students with an understanding of the legal, regulatory & governance frameworks associated with medical genomics and the use of genomic data. It will equip students to explore and evaluate the main ethical, legal and social issues (ELSI) involved in: genomic testing and the wider implications for the patient and their families; precision medicine; and the use of genomic data for population research.

  • PMGM18 Critical Literature Review

    This module will allow students to carry out a critical and in-depth evaluation of previous research based on a specific subject related to genomics

  • PMIM02 Health Data Modelling

    Health data scientists are expected to work with diverse data sources. Modelling data encompasses setting up database models and analysing the data using statistical models. The objective of this module is to raise the awareness of students about the various processes of data modelling and the key operations involved in the data processing of large and diverse datasets. Module leader is Dr Joanne Demmler

  • PMIM202 Health Data Modelling

    Health data scientists are expected to work with diverse data sources. Modelling data encompasses setting up database models and analysing the data using statistical models. The objective of this module is to raise the awareness of students about the various processes of data modelling and the key operations involved in the data processing of large and diverse datasets. This is a core / compulsory module and worth 20 Masters level credits. Module leader is Dr Pete Arnold


  • The Caldicott Principles; an effective model for information governance or a bureaucratic anachronism? (current)

    Other supervisor: Dr Jodie Croxall
    Other supervisor: Prof Kerina Jones
  • Living with Multiple Sclerosis and Anxiety: Determining reasons for anxiety amongst people with MS and possible methods of support' (current)

    Other supervisor: Prof Kerina Jones
  • The development and evaluation of a computer-based tool for assessing web-based information on medicines. (awarded 2019)

    Other supervisor: Prof Kerina Jones
    Other supervisor: Prof Gareth Jenkins
    Other supervisor: Prof David Skibinski
    Other supervisor: Prof David Skibinski