Article published In:
Information VisualizationEdited by Isabel Meirelles and Katherine Gillieson
[Information Design Journal 23:1] 2017
► pp. 6–18
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
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
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.
References
Andrejevic, M
(2014) Big Data, Big Questions: The big data divide. International Journal of Communication, 81, 1673–1689.
Bardzell, S
(2010) Feminist HCI: Taking Stock and Outlining an Agenda for Design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1301–1310). New York, NY, USA: ACM. 
Bhargava, R
Bhargava, R., Kadouaki, R., Castro, G., Bhargava, E. & D’Ignazio, C
(2016) Data Murals: Using the Arts to Build Data Literacy. Journal of Community Informatics, 121. Retrieved from [URL]
Boyd, Danah & Crawford, K
(2012) Critical Questions for Big Data. Information, Communication & Society, 15(5), 662–679. [URL]doi:
Crawford, K
(2016, June 25). Artificial Intelligence’s White Guy Problem. The New York Times. Retrieved from [URL]
Crawford, K., Gray, M.L. & Miltner, K
(2014) Big Data| Critiquing Big Data: Politics, Ethics, Epistemology| Special Section Introduction. International Journal of Communication, 8, 10.
Dalton, C.M., Taylor, L. & Thatcher, J
(2016) Critical Data Studies: A Dialog on Data and Space (SSRN Scholarly Paper No. ID 2761166). Rochester, NY: Social Science Research Network. Retrieved from [URL]
Diakopoulos, N
(2015) Algorithmic Accountability: Journalistic investigation of computational power structures. Digital Journalism, 3(3), 1–18.
D’Ignazio, C. & Bhargava, R
(2015) Approaches to Building Big Data Literacy. Bloomberg Data for Social Good. Retrieved from [URL]
(2016) DataBasic: Design Principles, Tools and Activities for Data Literacy Learners. The Journal Of Community Informatics, 12(3). Retrieved from [URL]
DiMaggio, P., Hargittai, E
. & others (2001) From the “digital divide”to “digital inequality”: Studying Internet use as penetration increases. Princeton: Center for Arts and Cultural Policy Studies, Woodrow Wilson School, Princeton University, 4(1), 4–2.
Blackburn-Dwyer, B
(2016) This Necklace Shows Just How Clean (or Dirty) Your Air Is. Retrieved December 30, 2016, from [URL]
Emerson, JTactical Technology Collective
& (2013) Visualizing information for advocacy. Bangalore, India: Tactical Technology Collective.
Freire, P
(1968) Pedagogy of the oppressed. New York: Continuum.
Gray, J., Bounegru, L., Chambers, LEuropean Journalism Centre & Open Knowledge Foundation
(2012) The data journalism handbook: how journalists can use data to improve news. Sebastopol, CA: O’Reilly Media.
Goldsmith, S. & Crawford, S
(2014) The Responsive City: Engaging communities through data-smart governance. John Wiley & Sons.
Harris, J
(2012, September 13). Data Is Useless Without the Skills to Analyze It. Retrieved September 12, 2016, from [URL]
Huron, S., Carpendale, S., Thudt, A., Tang, A. & Mauerer, M
(2014) Constructive visualization. In Proceedings of the 2014 conference on Designing interactive systems—DIS ’14 (pp. 433–442). New York, New York, USA: ACM Press.
Jacob, N
(2016) Boston Smart City Playbook — from the Mayor’s Office of New Urban Mechanics. Retrieved September 15, 2016, from [URL]
Keller, E.F
(1996) Reflections on Gender and Science: Tenth Anniversary Paperback Edition (Anniversary). New Haven: Yale University Press.
Julia Angwin, Surya Mattu, Jeff Larson, & Lauren Kirchner
(2016, May 23). Machine Bias: There’s Software Used Across the Country to Predict Future Criminals. And it’s Biased Against Blacks. Retrieved September 12, 2016, from [URL]
Landström, C
(2007) Queering feminist technology studies. Feminist Theory, 8(1), 7–26.
Letouzé, E
(2015) “Beyond Data Literacy: Reinventing Community Engagement and Empowerment in the Age of Data.” Retrieved from [URL]
Lohr, S
(2014, August 18). For Big-Data Scientists, “Janitor Work” Is Key Hurdle to Insights. New York Times.
Lupi, G., Posavec, S. & Popova, M
(2016) Dear data. New York: Princeton Architectural Press.
Maine Data Literacy Project
n.d.). Retrieved September 12, 2016, from [URL]
Maycotte, H.O
n.d.). Data Literacy—What It Is And Why None of Us Have It. Retrieved September 12, 2016, from [URL]
Mayer-Schönberger, V. & Cukier, K
(2013) Big data: a revolution that will transform how we live, work, and think. Boston: Houghton Mifflin Harcourt.
Merriam, S.B
Miller, S
(2014) Collaborative Approaches Needed to Close the Big Data Skills Gap. Journal of Organization Design, 3(1), 26–30. [URL]doi:
Neuhauser, A
(2015, June 29). 2015 STEM Index Shows Gender, Racial Gaps Widen. Retrieved September 12, 2016, from [URL]
O’Neil, Cathy
2016 Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy.
Pasquale, Frank
2015 The Black Box Society: The Secret Algorithms That Control Money and Information. Cambridge: Harvard University Press.
Phillips, A
(1991) Engendering democracy. University Park, Pa.: Pennsylvania State University Press.
Sandvig, C., Hamilton, K., Karahalios, K. & Langbort, C
(2014) Auditing algorithms: Research methods for detecting discrimination on internet platforms. Data and Discrimination: Converting Critical Concerns into Productive Inquiry. Retrieved from [URL]
Tufekci, Z
(2014a) Engineering the public: Big data, surveillance and computational politics. First Monday, 19(7). Retrieved from [URL] DOI:
(2014b) Engineering the public: Big data, surveillance and computational politics. First Monday, 19(7). Retrieved from [URL] DOI:
Tygel, A. & Kirsch, R
Walters, S. & Manicom, L
Welles, B.F
(2014) On minorities and outliers: The case for making Big Data small. Big Data & Society, 1(1), 2053951714540613.
Wickham, H
(2014) Tidy Data. Journal of Statistical Software, 59(10).
Williams, S., Deahl, E., Rubel, L. & Lim, V
(2014) City Digits: Local Lotto: Developing Youth Data Literacy by Investigating the Lottery. Journal of Digital and Media Literacy, 2(2). Retrieved from [URL]
Yin, R.K
Zimmerman, B.J
(2000) Self-Efficacy: An Essential Motive to Learn. Contemporary Educational Psychology, 25(1), 82–91.
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Goodwin, Sarah, Sebastian Meier, Lyn Bartram, Alex Godwin, Till Nagel & Marian Dork
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Luka, Mary Elizabeth & Koen Leurs
2020. Feminist Data Studies. In The International Encyclopedia of Gender, Media, and Communication, ► pp. 1 ff.
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Sander, Ina
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Seidelin, Cathrine, Yvonne Dittrich & Erik Grönvall
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Sorapure, Madeleine
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Sylvia, J. J.
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2021. C&T '21: Proceedings of the 10th International Conference on Communities & Technologies - Wicked Problems in the Age of Tech, ► pp. 336 ff.
Vacca, Ralph, Kayla DesPortes, Marian Tes, Megan Silander, Anna Amato, Camillia Matuk & Peter J. Woods
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Verdi, Ugo
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2021. Companion Publication of the 2021 ACM Designing Interactive Systems Conference, ► pp. 7 ff.
Wolff, Annika, Michel Wermelinger & Marian Petre
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2021. Creativity and Cognition, ► pp. 1 ff.
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Zhu, Xiaohua, Joseph Winberry, Kristen McBee, Ellen Cowell & Jonathan Stewart Headrick
2022. Serving the Community with Trustworthy Government Information and Data: What Can We Learn from the Public Librarians?. Public Library Quarterly 41:6 ► pp. 574 ff.
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