Data Literacy

Introduction

In the State of Open Data published in 2019, data literacy was explored as one of the key challenges to the success of the open data movement. In 2022, the challenge remains, though there have been important developments and advances in data literacy. The purpose of this update to the original State of Open Data chapter is to discuss recent data literacy efforts worldwide, emerging data literacy frameworks, and ongoing challenges. 

Data Literacy: What and Why

The term data literacy has traditionally been used mostly in the field of education to denote the skill sets that educators and learners need to turn data into information and, ultimately, actionable knowledge. However, the rise of the internet and, in particular, open data, has led scholars such as Frank et al. to argue that data literacy has been placed firmly on the agenda for a far more extensive range of organizations and individuals.¹ 

Scholars and practitioners use different data literacy definitions and frameworks. For the purposes of the original State of Open Data chapter and continuing in this update, my co-authors and I start from a working definition from Bhargava and D'Ignazio² that describes data literacy as “the ability to read, work with, analyze, and argue with data”. Today, the OECD proposes data literacy as an essential skill for public sector innovation.³

The success of Open Data efforts depends heavily on the existence of an ecosystem of actors focused on driving the use of data through all aspects of society. In recent years, there have been several new efforts and developments in this space. 

The Global Data Literacy Consortium:

The Data Literacy Consortium is a community of practice for organizations seeking to share resources and expertise on data literacy. It was founded in 2019 as a collaboration by the IFRC (a data-driven organization dedicated to evidence-based decision-making), the Centre for Humanitarian Data, and FabRiders.⁴ IFRC’s Data Playbook, a collection of data literacy social learning resources, is one of the resources that inspired this community of practice.

Data Literacy in the United Kingdom:

The National Data Strategy of the United Kingdom poses data literacy as a skill everyone will require. In 2022, the country’s Open Data Institute interviewed government workers to understand the role of data literacy and data capacity building initiatives within government. The ODI analyzed several initiatives, including the Government Skills and Curriculum Unit, the Analysis Function, the Government Statistical Service, the Data Masterclasses, the Office for National Statistics, and the Data Science Campus. The institute concluded that fragmentation of data literacy functions is a concern. It also found a consistent definition of ‘data literacy’ lacking with multiple bodies duplicating work and functions.⁵ 

Data literacy still poses a challenge in the UK private sector too. In 2021, the Department for Digital, Culture, Media, and Sport published a policy paper, “Quantifying the UK Data Skill Gap”. It found that almost half of businesses (46%) have struggled to recruit for roles that require data skills, while the supply of data skills from universities is unlikely to meet this demand, particularly in the short term.⁶

North America’s Public Sector:

In 2022, the United States Data Foundation published a report on data literacy initiatives in the country’s public sector. The report discusses, among other things, the Department of Education’s data strategy for enhancing data governance, a key objective of which is a data literacy program. It also discusses a 2020 Data Literacy Program for the US Treasury Department’s more than 10,000 employees. Other government bodies with data literacy programs noted by the report include the US Air Force, the Centers for Disease Control and Prevention, the Federal Deposit Insurance Corporation, and the State Department.⁷ 

In Canada, data literacy has been an area of work championed by Statistics Canada, the national statistical agency. The agency published a report in 2019 proposing a definition of data literacy, while also analyzing its own competency frameworks and assessment tools.⁸ Statistics Canada has also published a series of learning materials to promote data literacy in the public sector.⁹

The World Bank’s Data Use and Literacy Program:

The World Bank’s Development Data Group started the a Data Use and Literacy program, which aims to promote data use. They have worked with 30 different countries since 2012. At the national level, the program works with officials in national statistical offices, line ministries, and national and subnational governments, as well as with stakeholders in other sectors.¹⁰ This program published a 2021 report titled “Data for Better Lives,” which highlights recent institutional efforts around the world to leverage data for development. Some examples include the United Nations Population Fund’s data initiative that aggregates data on violence against women in 27 countries in Asia and the Pacific to investigate low service access rates among gender violence survivors, as well as the use of geolocated traffic accident data in Nairobi through a public-private partnership to increase road safety.

Non-profit Organizations in Latin America:

In Latin America, Mexico-based nonprofit SocialTIC launched Small Data in 2019. Small Data is a data literacy initiative aimed to promote the skills needed to find, create, and use data to solve local problems. A resource and case study series accompanying the initiative’s launch highlighted examples of organizations using open data to solve everyday problems, deviating from the idea that big data analysis is an essential part of data literacy initiatives.¹¹ 

The United States Academic Data Information Literacy Project:

This initiative is from 2015, however it was not mentioned in the first Data Literacy chapter of the State of Open Data. The Data Information Literacy Project is a research initiative undertaken by the Institute of Museum and Library Services in the United States. Research teams from Purdue University, the University of Minnesota, the University of Oregon, and Cornell University are working to develop a Data Information Literacy curriculum for higher education institutions.¹² 

The Private Sector Data Literacy Project:

Data literacy initiatives have also emerged in the private sector. One example is the Data Literacy Project,¹³ started by Qlik, Accenture, Cognizant, Experian, Pluralsight, the Chartered Institute of Marketing, and Data to the People. The Project shares a series of resources and stories for companies seeking to promote data literacy among their employees. 

Emerging Data Literacy Frameworks

The last few years have also seen the emergence of new data literacy frameworks and methodologies. The Eckerson Group, a data analytics consultancy firm, published its Data Literacy Development Methodology in 2021. The methodology seeks to promote data literacy at individual and organizational levels and proposes a Data Literacy Body of Knowledge, a collection of skills and knowledge that data literacy initiatives should promote among participants as an organizational instrument that helps to plan and assess the data capacity building processes in organizations.¹⁴

There are other projects. In 2022, the Digital Technologies Research Centre of the National Research Council Canada published a report authored by Stephen Downes. This report, entitled “Data Literacy,” poses an in-depth analysis of different data literacy frameworks (competency, evaluation or assessment, and teaching frameworks), highlighting their models, workflows, and methods.¹⁵

In 2020, University of Brighton reader Aristea Fotopoulou published an academic article that proposes a data literacies conceptualization to strengthen the work of civil society organizations in the field. Her contention is that data literacies, as opposed to the singular data literacy, is a more productive framing to consider how these literacies arise in the contexts of civic cultures and how they can progress in tandem with critical awareness about the power aspects of data.¹⁶

Fresh Challenges in Data Literacy

The COVID-19 pandemic became a test bed for hypotheses about data literacy, challenging assumptions about its role in society. As the pandemic unfolded, some academics saw data literacy as a powerful way to fight health misinformation. For instance, the Partnership in Statistics for Development in the 21st Century (PARIS21) published a report titled “Advancing data literacy in the post-pandemic world”, arguing that the pandemic highlighted the lack of data literacy among citizens around the world.¹⁷ 

However, Lee et al. challenged this assumption after studying how pro- and anti-mask groups in the United States had deployed data visualizations on social media in 2020. They found that both groups made drastically different inferences from similar data and concluded that “calls for media literacy - especially as an ethics smokescreen to avoid talking about larger structural problems like white supremacy - are problematic when these approaches are deficit-focused and trained primarily on individual responsibility”.¹⁸ 

Other challenges still remained since the original State of Open Data chapter on data literacy. It recommended that a focus be placed on the value of openness in fighting inequality rather than focusing solely on the value of data analysis. “Equity must be placed at the center of data analysis, and practitioners must actively push for reflection on the inclusion gaps in the data and the harm these gaps can bring,” we wrote. 

Our original recommendation remains and has been reaffirmed by University of Cardiff’s Data Justice Lab researcher, Fieke Jansen. In her article, “Critical is not political: The need to (re)politicize data literacy”, Jansen writes that for data literacy to achieve its citizen empowerment potential, it “should learn from other disciplines that have a more thorough analysis of dismantling power structures, engaging with inequality and encouraging political participation”.¹⁹