Article published In: Information Visualization
Edited by Isabel Meirelles and Katherine Gillieson
[Information Design Journal 23:1] 2017
► pp. 6–18
Creative data literacy
Bridging the gap between the data-haves and data-have nots
Catherine D'Ignazio | Emerson College, USA | MIT Center for Civic Media, USA | Boston Civic Media Consortium, USA | Public Laboratory for Technology and Science, USA
Available under the Creative Commons Attribution (CC BY) 4.0 license.
For any use beyond this license, please contact the publisher at rights@benjamins.nl.
Published online: 20 July 2017
https://doi.org/10.1075/idj.23.1.03dig
https://doi.org/10.1075/idj.23.1.03dig
Working with data is an increasingly powerful way of making knowledge claims about the world. There is, however, a growing gap between
those who can work effectively with data and those who cannot. Because it is state and corporate actors who possess the resources to
collect, store and analyze data, individuals (e.g., citizens, community members, professionals) are more likely to be the subjects of data
than to use data for civic purposes. There is a strong case to be made for cultivating data literacy for people in non-technical fields as
one way of bridging this gap. Literacy, following the model of popular education proposed by Paulo Freire, requires not only the acquisition
of technical skills but also the emancipation achieved through the literacy process. This article proposes the term creative data literacy
to refer to the fact that non-technical learners may need pathways towards data which do not come from technical fields. Here I offer five
tactics to cultivate creative data literacy for empowerment. They are grounded in my experience as a data literacy researcher, educator and
software developer. Each tactic is explained and introduced with examples. I assert that working towards creative data literacy is not only
the work of educators but also of data creators, data publishers, tool developers, tool and visualization designers, tutorial authors,
government, community organizers and artists.
Keywords: empowerment, data literacy, data visualization, inequality
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