Defining Data Literacy as Fundamental for All

Michelle Riordan-Nold


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In a nutshell, what we do at the Connecticut Data Collaborative (CTData) is this:  we help people find and use data.  As the old saying goes, you don’t know what you don’t know.  That’s why our objective is to change that, by alerting people to what they don’t know about how to understand and use data, and then helping them to do both.  It’s easier than you might think.

At the core is the concept of data literacy.  When you hear the term “literacy,” your mind might immediately jump to phonics flashcards and handwriting worksheets. Or perhaps you think of a financial literacy podcast you listen to for investing tips and retirement planning.

If this term elicits some brow-furrowing, you’re definitely not alone. When we conduct workshops and ask the question, “How many of you have heard the term ‘data literacy,’” about half of the hands go up. And even among those who’ve heard the term, it either elicits trepidation, or an uncertain gaze. 

People in the “data field” use “data literacy” as a handy term to refer to skills that we need to accurately utilize data at all levels, from data planning and collection, to data cleaning and analysis, to communicating and using results from data analysis. Some data folks use the term “data literacy” to refer to fairly advanced skills that only a small portion of the population will ever possess.

That, in our view, is too narrow a definition.  At CTData, a statewide public-private partnership in Connecticut that works with state and local government agencies, businesses and nonprofits, we are of the view that data literacy is an important and accessible set of skills that every person needs to possess.  

To us, data literacy is similar to language literacy. You don’t need to be able to write a poem in iambic pentameter to possess language literacy. Skill levels fall on a continuum—you can have a basic grasp of a language or be a Poet Laureate. Both exist on the same spectrum; one requires a more specialized focus on a particular subject.  

Likewise, we believe data literacy does not require advanced skills but rather reflects the accessible fundamentals for those who might not consider themselves “data people.”  Increasingly, whether at work or in our daily lives, data is all around us.  That underscores why fundamental data literacy ought to be for everyone.

The definition of data literacy that we use, and which permeates all of our educational activities, is this:  Data literacy is the ability to systematically and ethically ask and answer real-world questions with data. This includes: collecting and finding data, critiquing and interpreting data (being a critical consumer), and analyzing and applying data. 

Operating with this definition – framing data literacy as a basic, fundamental skill rather than an advanced, experts-only skill – is a distinction that makes a difference.

I often find myself explaining data literacy in this way:  You and I can’t help but come across data as part of our daily lives. We may be listening to the news and hear data points discussed as part of a story, or we might be considering hitting “share” on a shocking data visualization on social media. No matter the context, we need to be able to quickly assess the quality of the question being asked, the quality of the data source, the quality of the data analysis, and whether the conclusion(s) being drawn are valid. 

For many of us, decisions we make in a business or nonprofit organization often rely on data – and our understanding of that data.  The same is often true of decisions we make in our personal lives, such as assessing which community to live in, where to locate our business, or where we’d like our town to install a stop sign or build a new school. 

There is, of course, more advanced data literacy, akin to the Poet Laureate. Data literacy can also be the ability to develop complex research questions with large datasets and then craft them into an interactive data visualization.  But not being adept at the advanced level is not a reason to shy away from achieving basic knowledge and becoming adept at navigating the implications of data that we each encounter. 

Beyond that, we often hear of the ways companies like Facebook and Google are collecting data on us and using it to monetize the networks via targeted advertising. That’s just one more reason why understanding data should be a basic skill. 

Data is power, and we’re empowering people.  The thumbnail phrase we use is “data for everybody.”  That ought to be the standard.  Data should be accessible to everybody, across every demographic and every geography.  Access to data, and the ability to understand and use it, is a foundation we all can acquire. Data, not unlike democracy, should be of the people, by the people, for the people.  Every one of us.

Michelle Riordan-Nold is Executive Director of the Connecticut Data Collaborative (CTData), online at  CTData has been recognized by the Connecticut Entrepreneur Awards in the Education category, and operates the CTData Academy, which offer free classes to individuals and organizations to advance data literacy in Connecticut.