The term data literacy has become an integral part of a wider discussion about data revolution as policymakers and various expert communities began considering what it would take to enable people to make better use of the information around them. Many ideas were generated as a result. Policymakers have advocated more data science skills-training programs. Education institutions and non-profit organisations have tackled the digital divide by providing coding programs to the masses, especially vulnerable groups such as women and minorities (e.g. Women Who Code, School of Data). Open data and technology enthusiasts have used hackathons not only to create solutions but also hone the skills of civic hackers and promote new conversations about data as a social good.
However, despite the growing popularity, data literacy has no common definition. Consequently and perhaps unsurprisingly, many have taken the opportunity to offer their version of the truth. For instance, Data-Pop Alliance defines data literacy as "the desire and ability to constructively engage in society through and about data." David Crusoe of Harvard University provides a more expanded definition. According to him, "data literacy is the knowledge of what data are, how they are collected, analyzed, visualized and shared, and is the understanding of how data are applied for benefit or detriment, within the cultural context of security and privacy." Another interesting definition is provided by the Oceans of Data Institute, which states that "data-literate individual understands, explains, and documents the utility and limitations of data by becoming a critical consumer of data, controlling his/her personal data trail, finding meaning in data, and taking action based on data. The data-literate individual can identify, collect, evaluate, analyze, interpret, present, and protect data."
The many definitions of data literacy available on the web and in academic literature contrast sharply with the paucity of research on the scale of the phenomenon. In Europe, a recent study by Qlik went some way toward filling this gap, having found that less than 20% (922) of the surveyed respondents (n=5,291) are data literate. Geographically, data literacy rates are highest in Spain (25.3%) and lowest in France (12.2%). Appearing in the middle are three other countries investigated by the study: the UK, with 20.6%, Sweden (15.4%) and Germany (13.5%). The study also found that big companies (>500 employees) have the highest data literacy rate (47.1%). In terms of age, employees in the 45-54 bracket have the highest percentage of data literates (19%), which is followed by the 35-44 year olds (18.2%) and 25-34 year olds (17.4%). The majority of respondents (65.3%) are willing to invest more time and energy into improving their data skill set, and 52.3% said they look more closely at how data is being used to make sure they are getting real facts and not manipulations.
Besides Qlik no comprehensive quantitative research into data literacy in Europe has been carried out to date. That's why PoliVisu wants to address this evidence gap by running its own survey, targeting in particular public sector actors working in transport and urban planning across all member states. The survey covers all the main aspects of data literacy, from definition and skills to governance structures and existing applications. As the topic is under-researched, policymakers may use the results for comparative purposes in order to improve existing organisational practices, while the academic community may see it as a stepping stone to future research. Whatever the reason, we hope that survey findings will be of interest to all stakeholder groups. Responses will be accepted until end of March 2018. Visit this page to submit yours.