Data Literacy

Data Literacy

Being data literate means being able to read, create, understand, and communicate with and about data. Data literacy is both a technical and a conceptual skill — it is not just about being able to use data tools, but about understanding what data means, where it comes from, and what its limitations are. As datafication increasingly shapes all areas of social life, data literacy is becoming a critical capacity for citizens, workers, and communities.

How Organisations View Data Literacy

Many organisations and businesses frame data literacy in narrow, instrumental terms — as a workplace tool for making data-driven decisions. This includes:

• Reading and assessing data sources — evaluating where data comes from and how reliable it is
• Data-driven decision making — using predictive analytics and performance metrics to guide business choices
• Productivity and efficiency — measuring outputs and monitoring performance through data
• Embedding data literacy into organisational culture — building capacity across teams and leadership levels

Sources like DataCamp (2021) break data literacy down into levels — from conversational to fluent — and map roles across organisational hierarchies from frontline workers to senior leadership. While useful, this approach has a significant limitation: it treats data primarily as an organisational resource and neglects the broader social and political dimensions of data in everyday life.

What Is Missing from the Organisational View

The organisational approach to data literacy lacks a critical insight: how data is embedded into everyday life well beyond the workplace. It tends to over-emphasise data literacy as a workplace culture or productivity tool, and undervalues questions of power, ethics, governance, and social impact. A more complete conception of data literacy must address these dimensions too.

Critical Data Literacies

Burgess et al. (2022) develop a more expansive framework that situates data literacy within processes of datafication and everyday culture. They argue that literacy is both formal (educational, institutional) and informal (everyday, social). Everyday data literacy provides a framework for understanding how people learn about and respond to the logics, infrastructures, and flows of data under conditions of widening datafication.

Burgess et al. (2022) identify five key characteristics of data literacies:

• Multiple, not singular — there is no single, standardised data literacy; different contexts, communities, and individuals develop different literacies
• Both conceptual and technical — data literacy involves understanding what data is (conceptually) as well as how to work with it (technically)
• Critical — data literacies must interrogate power, question assumptions, and examine the social contexts in which data is produced and used
• Social — data literacy is a resource for public connection, civic participation, and collective belonging; it is not just an individual skill
• Dynamic — data literacies change over time as technologies, platforms, and social norms evolve

Data as Part of Everyday Life

Data pervades everyday life across multiple domains:

• Data and work — the measurement of labour, productivity, and efficiency has a long history; datafication extends this with algorithmic performance monitoring and surveillance
• Data and the self — individuals are encouraged to track themselves through fitness apps, sleep monitors, and mood journals, while simultaneously being tracked by platforms and governments
• Social media and algorithmic literacies — platforms are fundamentally data-driven; understanding how algorithms work, how content is ranked and filtered, and how personal data is collected and used is essential for navigating digital life

Importantly, as Burgess et al. (2022) note: "Datafication can invite new forms of data literacy, but it can also diminish others." Not all engagement with data builds understanding — some forms of datafication can obscure, mislead, or create new vulnerabilities.

Everyday Data Literacies in Practice

Burgess et al. (2022) define everyday data literacies as "an emerging set of practices and data cultures that can contribute to oversight and agency within disciplining systems. But equally, everyday data literacies create new opportunities for social learning and collective activism, as well as for the amplification of malicious intent and action." This dual potential — for empowerment and for harm — makes critical engagement essential.

Literacy and Power

Pinney (2020) argues that data visualisation specifically can be a vehicle for developing data literacy and addressing uneven literacies across society. Literacy has historically been an enabler of social change — it raises questions about power and enables those with less power to ask critical questions of institutions and systems. However, literacy alone is not sufficient; related capacities including competence, skill, know-how, and expertise are all important dimensions of engagement with data.

Why Data Literacy Matters

Ultimately, data literacy is about more than individual technical skills. It is about:

• Understanding the impact of data on our world — social, political, economic, and cultural
• Grasping how and why data pervades everyday life — the logics, incentives, and infrastructures behind datafication
• Developing the capacity to question, resist, or transform data systems when they cause harm or reproduce inequality