Other research

Home > Other research

[Living With Data literature review bibliographies]

Interest in how the public perceives ‘data practices’ has grown recently. Indeed, understanding public views is said to be at the heart of initiatives like the government Centre for Data Ethics and Innovation (CDEI) and the independent Ada Lovelace Institute (Ada) in the UK. Consequently, research into public understanding and perceptions of datafication has flourished in recent years, and this has advanced understanding of these matters.

The emerging literature on public understanding and perceptions of datafication needs reviewing to help us identify next steps for research in the field. We need to synthesise existing evidence, evaluate whether patterns emerge, assess the claims that are made on the basis of existing research, and identify limitations and gaps that future research can address.

Living With Data is currently undertaking such a review, which will inform our own research. We are reviewing original empirical research (including academic and grey/non-academic literature) into public understanding and perceptions of, attitudes towards and feelings about data practices and related phenomena (such as AI and facial recognition) published between 2015 and 2019.

Because of the proliferation of research on this topic in recent years, we have limited the research that we review in this document in the following ways:

  1. By dates: given the fast pace of change in our field of enquiry, we review literature published between 2015 and 2019 (inclusive) only.
  2. By geography for grey literature: because of the proliferation of surveys and polls in our field of enquiry in recent years, and because grey literature often aims to have a national impact, the grey literature we review is UK-focused (either UK-only or based on international research which included the UK). Relevant research has been undertaken elsewhere in the world but we do not include it in our analysis. There is less academic research that is UK-focused. Because of this, and because academic research contributes to an international conversation, we include selected international academic literature.
  3. By populations researched/research subjects: we exclude literature about children’s understandings and perceptions of data practices because the study of children (and digital media) is a specialist field outside the remit of our own research, although studies of adults’ perceptions of data practices relating to children are included.
  4. By domain, especially with regard to research about public perceptions of health data: research into public perceptions of uses of health data and the ethics of health data re-use is more advanced than in any other domain. As a result, more is known about public perceptions of datafication in health, and high quality syntheses have already been undertaken, for example by Understanding Patient Data (2018). We therefore focus this review primarily on domains other than health. 
  5. By subject matter/focus: a large proportion of the research into public attitudes and perceptions that has been undertaken focuses on privacy, surveillance and security. We largely exclude this from our review, except where there is an obvious focus on attitudes to data practices included in the research.
  6. Existing evidence syntheses and reviews: A small number of evidence syntheses and reviews have been published in ths field. Some of these cover publications outside our timeframe (eg Bakir et al 2015 draws on publications from before 2015). Others cover domains that are not our focus (eg Understanding Patient Data 2018 on health data). For these reasons and in order not to reproduce work already undertaken, we do not carry out analysis of the literature covered by these syntheses in this document.

The research and reports that we review in this document were identified through two main search strategies:

  • We carried out a systematic search of online citation databases, using multiple keywords relating to how people feel about data practices and what happens to their personal data. We focused this search primarily on Web of Science;
  • We carried out a manual search that began with grey and academic literature with which we were already familiar, and then snowballing out (eg searching bibliographies, relevant websites, observing Twitter discussions and building on word-of-mouth recommendations).

We assessed the literature that we identified through these processes iteratively, according to one principle inclusion criteria: does it report empirical research about how people feel about data practices and what happens to their personal data? Answers to this question are likely to be subjective, and so is the existing knowledge which formed the starting point for the manual search. Searching databases also has limitations: different databases show different results from searches (see Martín-Martín et al 2019 for a detailed discussion of this), searches will only produce results from the Web of Science databases to which the host university subscribes, and of course, search keywords shape what is and is not found. In short, all literature and evidence searches are partial, and ours is no exception.  In the final, published research review, we will discuss these issues in greater detail.  

Please click on the link below to view our bibliographies. If you think we have missed anything, please email us on  livingwithdata AT sheffield DOT ac DOT uk to let us know.

[Living With Data literature review bibliographies]

References cited

Bakir, V., Cable, J., Dencik, L., Hintz, A. and McStay, A. (2015), Public Feeling on Privacy, Security and Surveillance. DATA‐PSST and DCSS Project Report.  

Martín-Martín, A., Orduna-Malea, E., Thelwall, M. and Delgado-López-Cózar, E. (2019) ‘Google Scholar, Web of Science and Scopus: which is best for me?’ LSE Impact Blog,

Mayer-Schoenberger, V. and Cukier, K. (2013) Big Data: a revolution that will transform how we live, work and think, London: John Murray Publishing.

Understanding Patient Data. (2018). Public attitudes to patient data use: A summary of existing research.