This White Paper was written by Rahul Bhargava, Erica Deahl, Emmanuel Letouzé, Amanda Noonan, David Sangokoya, and Natalie Shoup, in collaboration with Internews Center for Innovation and Learning and the MIT Media Lab Center for Civic Media. It was launched September 29, 2015 in New York City for the Beyond Data Literacy Workshop.
The term ‘data literacy’ has gradually emerged as a mainstream term and potential buzzword of the ‘Data Revolution’ discussions, as experts, policymakers, and advocates began considering what it would take to enable citizens to make better use of the vast amount of data available to them. Policymakers have advocated for more data science skills-training programs. Schools and non-profit organizations (such as Code for America, Girls Who Code, School of Data, etc.) have emerged to tackle the digital divide by providing coding programs and technical curricula for vulnerable populations, specifically for women and minorities. An increasing number of data journalists are using and writing about data. Open data and civic technology advocates have organized hackathons for civic hackers to use technical skills and foster new conversations on data for social good.
Despite its growing popularity as a much-needed “bottom-up” solution, data literacy is ill-defined or ambiguous at best. Are current conceptualizations of ‘data literacy’ adequate—or do they put too much emphasis on technical requirements and fail to challenge deeper structural and more politically controversial issues? What does it mean to be “data literate” in an age where data is everywhere— and how does it differ from being literate? Why and how should it be promoted? How might ‘data literacy’ promotion empower individuals and communities to keep governments accountable, solve local problems, and navigate their own data ecosystems? In a world of ubiquitous digital connectivity and rising inequity, should we in fact be concerned with and talking about data inclusion instead?
We first discuss ‘data literacy’ as an emerging concept within a much longer historical narrative of literacy promotion. History sheds light on how defining and promoting literacy—who was literate and who was not—has been often entrenched with the constructs and perpetuation of power structures within societies—at odds with the notion of literacy as a necessarily empowering and enlightenment force. There is a risk that the same processes may play out in the age of data, at a speed and scope commensurable with those of the spread of data as a social phenomenon.
We define data literacy as “the desire and ability to constructively engage in society through and about data.” Five observations emerge from this definition:
- “Desire and ability” highlights technology as a magnifier of human intent and capacity.
- “Ability” underlines literacy as a continuum, moving away from the dichotomy of literate and illiterate.
- “Data” is understood broadly as “individual facts, statistics, or items of information.”
- “Constructively engage in society” suggests an active purpose driving the desire and ability.
- And “through or about data” offers the possibility for individuals to engage as data literate individuals without being able to conduct advanced analytics.
This definition—as well as the nature of data itself—encompasses elements and principles from each of these sub-kinds of literacy (such as media, statistical, scientific computational, information and digital literacies), moving away from medium-centred definitions of literacy towards a more encompassing one.
In utilizing a definition of data literacy that builds on the elements of current sub-categories of literacy and expands beyond particular media—and their technocrats—we describe four key pillars that form its foundation: data education, data visualizations, data modelling, and data participation.
Our exploration of data literacy pushes us to further consider what it would mean to be “literate in the age of data” and denote four core pillars in literacy promotion:
- Data literacy promotion must be agile and adaptive, focusing on helping foster adaptive capacities and resilience rather than teaching platforms and technical languages that are bound to become out-dated.
- Data literacy promotion must build on the key features and pillars from all core sub- categories of literacy, viewing literacy as a continuum.
- Data literacy promotion must involve empowering people to navigate their current ecosystems and societies in ways that are meaningful and effective for them.
- Data literacy promotion must involve providing multiple pathways for people with different data literacy needs and capacities to interact within a complex system.
At the center of the rationale and attention around data literacy promotion should be the goal of empowering citizens and communities as free agents. This can only be achieved by considering data literacy as a significant means and metric for social inclusion—where data literacy as defined and conceptualized above is promoted for and via greater social inclusion—or, more appropriately, data inclusion.
Here we highlight the following three critical challenges in designing data literacy programs:
- Making Big Data smaller, on scale where most or many more people are willing and able to engage than is the case today
- Understanding the importance of context and utilizing elements of human-centered design;
- Understanding and leveraging the power of words and language in communicating and visualizing data
As we revisit the larger context of the Data Revolution in the last section and concluding remarks in the light of data literacy and social inclusion, it becomes clear that if this Data Revolution is to bring about positive change, it has to be an evolution towards social inclusion in the age of data – towards data inclusion. If a ‘business-as-usual’ framing for the Data Revolution continues unabated, our efforts toward greater data literacy may reinforce existing power dynamics that promote social exclusion. This transitional period is the opportune time to create a path towards empowerment. Data literacy focused on building data inclusion offers a doorway to understanding, interpreting, and managing data-driven decisions and arguments for all people.
Supporting data literacy is not primarily about enabling individuals to master a particular skill or to become proficient in a certain technology platform. Rather it is about equipping individuals to understand the underlying principles and challenges of data. This understanding will in turn empower people to comprehend, interpret, and use the data they encounter—and even to produce and analyze their own data. This can only be achieved by considering data literacy becomes a means toward a necessary reinvention of community engagement and empowerment—towards what we term data inclusion.
Watch our coinciding video, which is our first video in the series on Big Data and development, on “What is Data Literacy?”
Watch our second video in the series entitled “Entering the Age of Data: A Focus on Data Inclusion”.