Why Become a Data Literate Citizen?

Data affects our lives in ways once considered science fiction; the dystopia presented in George Orwell’s “Nineteen Eighty-Four: A Novel” and Cory Doctorow’s “Little Brother” is a real possibility. The amount of data generated and collected grows exponentially; it is a data tsunami with these characteristics: variety, velocity, veracity, and volume.

In ancient Egypt the high priests and priestesses performed the most important rituals and managed the business of the [data] temple in furtherance of the pharaoh’s decrees. The veils of the high priests and priestesses of data, secluded inside stone-walled temples, will be pulled back to expose mere mortals like ourselves.

Unlike Dante Alighieri’s “The Divine Comedy” in which he passes through a gate bearing the inscription “Lasciate ogne speranza, voi ch’intrate”, colloquially translated as “Abandon all hope, ye who enter here,” the situation is not hopeless.1 We can use data for good if we possess the requisite skills, motivation, and intention. Similarly, we will be able to recognise misuse or flawed, erroneous interpretations of data.

What is Data Literacy and Why Should I Care?

Data literacy is a mindset and developing a data-first attitude is vital if we desire to be data literate citizens.

The Industrial Revolution marked the transition from an agricultural and artisan centric society, in which work was organised at the individual or family level, to a factory centric society, in which manufacturing processes rather than people led to a shift in the types of skills required to participate, survive, and thrive.

Similarly, the Information Revolution marked the transition to a society in which the value of data not only as a resource but a commodity was recognised, largely through technological advances. The traditional factors of production (capital, labour, land, raw materials) have been augmented by information, specifically data.

The latter transition is currently propelling our knowledge-based society towards new skills to understand the world around us as we transition, yet again, from the Small Data Era into the Big Data Era.

Reading, writing, and arithmetic became increasingly important skills at the dawn of the Industrial Revolution. As reading, writing, and arithmetic are to general literacy (the 3Rs), data skills (acquisition, cleansing, extraction, transformation, analysis, visualisation, interpretation, and communication) and its allied skills of discrete computer programming and domain knowledge are to data literacy (the 3Ds) today. We need all six skills, unified by critical thinking skills, to be a data-literate member of society.

Traits of a Data Literate Citizen

Data literacy is a journey not a destination. We cannot realistically expect to master these traits without mindful, consistent and significant effort. The good news is just as we acquired general literacy skills, we can attain data literacy with time and practise.

A data literate citizen possesses the mindset, knowledge, and skills in pursuit of answering specific question(s), if possible, and communicating those insights to stakeholders, including theirself.

As the number of data sources increases, as the amount of data collected and stored increases, as access to these data sources increasingly opens to the public, the ethical use of data must be foremost in our mind. Licensing terms of datasets, covering use and distribution, must be honoured. Awareness of potential pitfalls when working with data can reduce the likelihood of misinterpreting results. We have a responsibility to “advocate for the effective use of data…through active and competent use of the language of data,”2 says Ben Jones.

Working with data requires a certain degree of numerical and graphical literacy, respectfully called numeracy and graphicacy… to either explore data or communicate the main insights we obtained to other people.

– Alberto Cairo, Knight Chair at the University of Miami

Whether working with small datasets or massively large datasets, there is a common set of data skills we can apply to the data analysis process: acquisition, cleansing, extraction, transformation, analysis, visualisation, interpretation, and communication. Descriptive and inferential statistics, computer programming, plus sufficient contextual domain knowledge round out the requirements to become data literate. Anyone can learn to read and speak this new language called data which frequently are imperfect and incomplete. Consequently, utilising data resourcefully, identifying opportunities to improve the data and implementing such improvements, enhances value and derived insights from associated analyses.

Big data needs big brains; big data needs the curious brains of an artist to make a difference.

– Jose Miguel Cansado, General Director of Alto Data Analytics

In addition to data skills, Jose Miguel Cansado says a data literate citizen must cultivate the human skills of curiosity (how to find, search, and filter relevant data), communication (how to advocate, influence, and present ideas which create change), creativity (how to innovate and articulate solutions to solve problems), empathy (how to connect with other people to understand their needs), imagination (how to visualise abstractly), and leadership (how to get other people to take action).3

Curiosity is at the epicentre of the other human skills. It is curiosity for influencing that drives communications; it is curiosity for solutions that drives creativity; it is curiosity for the human condition that drives empathy; it is curiosity for ideas that drives imagination; it is curiosity for results that drives leadership.

In other words, the most important skill is asking the right question – to understand human issues, to imagine the possibilities, to create and articulate solutions, to convey the message and insights with the right visualisations to make them actionable.

Data Literacy Foundations

Whether your interest is academic, personal, or professional, the Data Literacy Foundations series will introduce you to the fundamentals of data literate citizenship.

With the next installment of Data Literacy Foundations we start our journey of becoming a data literate citizen.



  1. Alighieri, Dante. “The Divine Comedy.” Project Gutenberg
  2. Jones, Ben. “17 Key Traits of Data Literacy.” 16 January 2019. Data Lteracy
  3. Cansado, Jose M. “Human Factors in a Data Scientist.” 19 July 2017. TEDx Talks