What is Data Literacy?
Data literacy is an emergent field in Science and Technology Studies. In a world where entire economies, communications infrastructure and media ecosystems are datafied, current understanding of data literacy’s centrality to everyday life remains variable. Such an environment therefore presents pressing challenges and opportunities for the Arts and Humanities.
Definitions of data literacy are contestable – until now somewhat reliant on data science and social science approaches.
Mandinach & Gummer (2013) define data literacy as the ability to understand and use data effectively to inform decisions; composed of a skill set and knowledge base that enables individuals to transform data into actionable knowledge.
These skills include knowing how to identify, collect, organise, analyse, summarise, and prioritise data; how to develop hypotheses, identify problems, interpret data, and determine, plan, implement and monitor courses of action.
Fostering citizen empowerment through the use of ICTs remains a key objective in the era of Big Data, driven by expectations that new technologies facilitate more responsive governments, and access to information engenders economic growth as well as creative and social fulfilment. This is a key expectation of open data policies since the launch of the Open Data Charter at the G8 summit in 2013. However, whereas corporate Big Data has managed to engage these expectations, the creative and social aspirations have yet to be realised.
Despite well-intentioned efforts of the G8 to open their data for public scrutiny, the skills used to meaningfully engage with data remain excluded from the education system. The ability to filter databases and datasets, identify and isolate noteworthy information from raw data, translate mathematical abstractions into insight that might inform decisions at different levels of society, all remain out of reach for most citizens. To compound this exclusion, the teaching of Science and Mathematics appears to favour instrumental aspects of the discipline (Chevallard, 2013) to the detriment of critical and creative approaches to data, essential for integral education in increasingly data-centric societies.
For creative industries increasingly driven by the digital economy, further challenges and opportunities are presented.
Atkinson and Whatley (2015) observe, ‘digital preservation and presentation of archival materials dramatically impacts upon the nature and notion of access’, radically altering the experience of creative expression (and its consumption) in a range of creative arts: film, dance, spatial design and beyond.
Open data policies demand critical levels of understanding in creative practice, beyond utility. For Singer (2016), ‘data art is a full-fledged and maturing artistic practice’, at the intersection of art, design and activism. Data-artists work in diverse fields, producing new visuals and representations, recombining bits to build something new out of everyday experience, and using data to reflect contemporary society. Creative and civic opportunities for this practice are truly staggering, but for Singer, it is only through improved ‘access to and public involvement with data we can increase understanding of important issues […] and provoke behavioural and systemic change’.
An Arts and Humanities approach to data literacy, therefore, needs to embrace the role of access, social commentary and strengthening local democracy at its heart, where creative innovation might be considered to have value beyond mere visualisation; but also to acknowledge the role such visualisation plays in engendering data literacy and public awareness.