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Research Results Part 1: Defining Data Literacy

- January 8, 2016 in Impact

Thanks to the efforts of governments, organizations and agencies to make their information more transparent, the amount of open data has increased dramatically in recent years. Consequently, interest has arisen in the practitioners who develop data literacy, which they do often through international, collaborative networks of like-minded actors.

The work of School of Data has emerged in a context where different fields (from Information and Communications Technology (ICT) for change activism to data journalism curriculum creation in universities) have seen resources devoted to the transmission of skills related to data use in different journalism and advocacy contexts. ‘Data literacy’ has emerged as a term to refer to the umbrella of initiatives, though not without challenges (Data-Pop Alliance, 2015). What does the concept exactly mean?

‘Data literacy’ can be defined in terms of skills (‘the ability to use and analyse data’), and this can inspire different analysis on each component to those skills. However, attempts to define the term can also allude to the social transformations that can be sought through it, especially when seen through the lens of the history of literacy (Data-Pop Alliance, 2015).

Furthermore, once we accept a definition of ‘data literacy’, how does it coexist with discussions such as the difference between ‘statistical literacy’ and ‘statistical competence’ (“what every college graduate should know” vs “what we hope a business statistics student will retain five years later”, as Moore distinguishes –as cited by Schield, 2014–), or with the general concept of data awareness (as discussed by Rumsey, 2002)?

‘Data literacy’ as a concept stems from old visions of numeracy and information literacy; however, researchers who have examined current work in this field have categorized the approaches to define data literacy as the ability to read, work with, analyze and argue with data (Bhargava and D’Ignazio, 2014), as well as “the desire and ability to constructively engage in society through or about data” (Data-Pop Alliance, 2015). We consider both dimensions, skills and social engagement, are a good foundation to discuss the aims and practices of the School of Data community.

The underlying concept of data literacy that each actor holds will determine aspects of their methodology at the individual and collective levels. Inspired by the categorization done by Bhargava and D’Ignazio, in our interviews we asked participants questions to get insight on their visions of data literacy and the aims of their work. The following abilities were mentioned by two or more participants:

  • Knowing how to find information in different ways. This includes being able to track down sources of existing data, but also knowing how to collect it if it doesn’t exist yet.
  • Being able to apply critical thinking skills to data. This ranges from the ability to do data quality assessment or contextualizing specific information to other aspects of processes related to data-related work, such as the ethics of handling data.
  • Being able to ask questions to the data (and then finding an answer). Related to the last ability, different participants mentioned the ability to ask questions to data as one of the goals of data literacy trainings – even if they don’t go as far as finding the answers for them, though ideally they would.
  • Being able to find specific outputs (such as stories or visualizations) in data. Apart from the ability to ask and answer questions, a topic that recurred among participants from the field of data journalism was the importance of finding stories and other journalistic outputs.
  • Being able to use it to advance one’s own goals. Whether it is specifically more in-depth research, or generally better and more data-driven storytelling or campaigning, the link between data and action was evident in many of the interactions we had with the participants.
  • Feeling comfortable around data and working with it. At times as an intermediate aim to lead to the other abilities mentioned in this section, and at other times as an end in itself, many participants mentioned the importance of promoting comfort around data (and bringing down the psychological barriers that exist between people and data).
  • Being able to do basic statistical analysis with data. Even though more technical aspects of data literacy came up at different points (for example, the need to know how to clean data), the only one that was recurring was the ability to work with basic statistics.

Other general considerations

  • It’s a non-linear process. Two participants pointed out that it was important in their work not to view data literacy as a linear process, or a binary (“you are data literate or you aren’t”); they view data literacy as a process that involves very different actions depending on the context and needs of each individual (or group).
  • Data literacy can be promoted and assessed at the individual level, but also in groups (such as organizations or communities). When asked what data literacy looked like at the organization level, participants mentioned buy-in and engagement from different parts of the organization (including the senior staff). The proper allocation of resources to this type of work depends on an understanding of data work and its genuine possibilities.
  • An aim of data literacy work is to expand existing markets. In the case of data journalism, different participants mentioned data literacy work as a way to help journalists produce content that will bridge the gap between them and information they can act upon (a hypothesis based on solutions journalism, which is journalism that aims at covering solutions to social problems, for example). Also, as a way to increase the demand for open data.

It’s important to understand how the various actors in the field use the term ‘data literacy’ and in particular, how that impacts training and knowledge sharing goals. As the use of data becomes more ubiquitous in social change efforts, it is likely that the definition will continue to narrow and be as recognisable as terms like ‘computer literacy’.  

In our next post ‘Data Literacy Methodologies’ we will look at how data literacy practitioners reinforce their own definitions through their training and knowledge sharing practices.

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Our Data Literacy Research Findings

- January 8, 2016 in Impact, Update


In 2015 School of Data started its first research project to understand data literacy efforts around the world. In the lead up to the publication of the final report, we’re publishing a series of blog posts to share our findings. The goal is to provide them in an accessible format, benefitting both data literacy practitioners and a wider network of peers. Hopefully, this examination of techniques and methodologies currently employed by actors within and outside the network can provide with a pool of knowledge to be used in building and developing data literacy efforts.

For this research project we aimed to examine the effectiveness of current data literacy efforts, particularly in relation to social change work. This research is specifically aimed to empower the School of Data Steering Committee to take strategic decisions about the programme going forward and along with the School of Data network members, build on the successes to date.  We specifically looked to answer the question: What are the recurring topics when speaking about data literacy in social change/justice work?

We have conducted a series of semi-structured interviews with data literacy practitioners, and desk research to collect data and literature on data literacy. This has been analysed with the goal of improving data literacy practice in the short term, informing efforts to provide data literacy in the long run.

In the coming weeks we will be sharing our findings here under the following topics:

  1. Defining Data Literacy – January 8th
  2. Data Literacy Methodologies – January 14th
  3. Measuring the Impact of Data Literacy Efforts – January 21st
  4. Which Business Models for Data Literacy Efforts? – January 28th
  5. Improving Data Literacy Efforts – February 4th
  6. List of resources we used during our research – February 11th


Mariel Garcia provided research assistance and Dirk Slater from FabRiders provided research advisory. Guidance for their work was provided by Marco Pires, School of Data Coordinator; Milena Marin, former School of Data Coordinator and Katelyn Rogers, Project Manager at Open Knowledge International.

We are especially thankful to the following people who advised us during this process:

  • Javiera Atenas (Management Science and Innovation Department, University College London, United Kingdom),
  • Becky Faith (Department of Computing and Communications, Open University, United Kingdom),
  • Rahul Bhargava (Center for Civic Media, Massachusetts Institute of Technology, United States),
  • Silvana Fumega (University of Tasmania, Australia)
  • Fabrizio Scrollini (Iniciativa Latinoamericana por los Datos Abiertos, Uruguay).

The following people were gracious enough to provide us with insightful interviews that helped us develop our research:

  • Allen Gunn, Aspiration;
  • Ariel Merpert, Chequeado;
  • Emma Prest, Data Kind UK;
  • Eva Constantaras, Internews;
  • Fabio Campos, Oi Futuro;
  • Gabriela Rodriguez;
  • Jason Norwood-Young, Raymond Joseph and Jennifer Walker, Code for South Africa;
  • Juan Manuel Casanueva, SocialTIC;
  • Maya Ganesh, Tactical Technology Committee;
  • Natalia Mazotte, School of Data Brazil;
  • Nisha Thompson, Data Meet;
  • Rahul Bhargava, Data Therapy;
  • Rebecca Kahn, P2P University;
  • Ye Sheng, IREX;
  • Zara Rahman, the engine room.

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What was the School of Data Network up to in 2015?

- December 28, 2015 in Community, Impact

The School of Data Network is formed by member organisations, individuals, fellows and senior fellows around the world

The School of Data Network is formed by member organisations, individuals, fellows and senior fellows around the world

We just can’t believe it’s already the end of the year! I mean, every year you see people saying the months passed by so fast, but we really mean it! There was a lot going on in our community, from the second edition of our Fellowship Program to many exciting events and activities our members organised around the world.

Let’s start with folks at Code4SA. They coordinated the activities of three open data fellows and are organising the first physical Data Journalism School of the continent! Isn’t that amazing? They’re actually creating a space for people to work together with on-site support on data journalism skills. This is the first time this happens in the School of Data network and we’re really proud Code4SA is taking the lead on that! But they didn’t stop it there. They also participated in the Africa Open Data Conference, coordinated trainings and skillshares with NU & BlackSash and ran two three-day Bootcamps (Cape Town and Johannesburg). “One of our biggest challenges this year has been establishing a mandate to work with the government”, said Jennifer Walker, from Code4SA. “On the Data Journalism School, the challenge is really getting everything in place, the newsroom, the trainer etc.”

The group will pursue the project of setting up the first data-journalism agency in Macedonia (Dona Dzambaska - CC-by-sa 3.0)

In Macedonia, this group will pursue the project of setting up the first data-journalism agency in the country (Dona Dzambaska – CC-by-sa 3.0)

In Macedonia, our friends at Metamorphosis Foundation had their second School of Data Fellow, Goran Rizaov. Together with Dona Djambaska, senior School of Data Fellow (2014), they organised four open data meetups, and two 2-day open data trainings, including a data journalism workshop with local journalists in Skopje. They also launched a call for applications that resulted in Goran supporting three local NGOs in open data projects. They also supported the Institute for Rural Communities and the PIU Institute with data clinics. And if that was not enough, Dona and Goran were special guests speakers at the TEDxBASSalon.

Open Knowledge Spain and Open Knowledge Greece also were busy coordinating School of Data in their respective countries. In Spain, Escuela de Datos participated in a data journalism conference leading workshops for three days and a hackathon. They also ran monthly meeting with people interested in exploring data; they call it “open data maker nights” and also our own “data expeditions.” They will have a couple of meeting early January to set the goals for 2016. Greece organised an open science training event and also servers as the itersection between open data and linked data, coming from people working at the University of Greece.

In France, Ecole des Données has organised three activities in Paris: a local urban data laboratory, a School of Data training and the Budget Democracy Laboratory, both for the city hall. They also developed a DatavizCard Game and coordinate a working group around data visualisation. Our French friends also took part in a series of events, such as workshops, conferences, debates and MeetUps. You can check out the list here. In 2016 they want to do more collaboration with other countries and will participate in the SuperDemain (digital culture for children and families) and Futur en Seien 2016 events.

Camila Salazar & Julio Lopez, 2015 School of Data Fellows, organised a series of workshops in Latin America

Camila Salazar & Julio Lopez, 2015 School of Data Fellows, organised a series of workshops in Latin America

Across the Atlantic we arrive in the Latin American Escuela de Datos, coordinated by SocialTIC, in Mexico. Camila Salazar and Julio Lopez, two fellows from the class of 2015 did amazing things in the region, such as organasing 23 training events in four different countries (Ecuador, Costa Rica, Chile and Mexico), reaching out to more than 400 people. Julio is working with the Natural Resource Governance Institute on a major project about extractives data (stay tuned for news!) and Camila was hired by Costa Rica’s biggest data journalism team at La Nación, on top of developing a project about migrant data in the country. They’re on fire! You will hear more from them on our annual report that’s coming out early next year. “Our biggest challenge now will be having more trainers comming out of the community”, said Juan Manuel Casanueva, from SocialTIC.

Escola de Dados (Brazil) instructors and participants in a workshop about data journalism and government spending data, in São Paulo

Escola de Dados (Brazil) instructors and participants in a workshop about data journalism and government spending data, in São Paulo

Heading down to South America we see that brasileiros at Escola de Dados, in Brazil, are also on fire. They organised 22 workshops, trainings and talks/events reaching out to over 760 people in universities, companies and even government agencies. Two of their intructors were invited by the Knight Center for Journalism in the Americas to organise and run the first 100% in Portuguese MOOC about Data Journalism, with the support from the National Newspaper Association and Google. In total, 4989 people enrolled for the course which was a massive success. They also organised a data analysis course for Folha de S.Paulo, biggest broadsheet newspaper in the country. Next year is looking even better, according to Natália Mazotte, Escola de Dado’s coordinator. “We will be offering more courses with the Knight Center, will create data labs inside Rio de Janeiro favelas and will run our own fellowship program”. Outstanding!

We have so much more to share with you in our annual report that’s coming up in a few weeks. 2015 has been a great year for School of Data in many, many aspects and we are eager to share all those moments with you!

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Data literacy research: update and OGP sessions

- October 27, 2015 in Impact

Announcement: We will be presenting the preliminary findings of our data literacy research at the OGP convening in Mexico City. We are leading a knowledge café session on this topic on CSO day (Tuesday the 27th at 2, classroom C9) and participating on mySociety’s panel on research and digital democracy during the Summit (Wednesday the 28th at 4, also at classroom C9). We’ll be happy to see you there! 

As we shared a few months back, School of Data is working on a research project to understand data literacy efforts around the world. We are using a framework which is informed by the principles of action research. We have conducted a series of semi-structured interviews with relevant stakeholders, and have collected literature, existing research and resources that help illuminate effective methodologies that are in use. This is currently being analysed and written up with the goal of improving data literacy practice in the short term, informing efforts to provide data literacy in the long run.

While we are still in the process of putting the final touches on our research paper, we want to share a few facts from our preliminary findings…

  • Context: much data literacy work is independent from tools, and has to do with the ability to understand the context of data. How it came to be, where it is to be found, how it can be validated, what lines of analysis are worth exploring.
  • Data pipeline: The School of Data data pipeline has been the most recurring concept in interviews, even among actors outside the School of Data network. This finding has prompted us to start digging deeper into how this concept came to be and why the data literacy community finds it useful.
  • The role of soft skills: The level of comfort and confidence of beneficiaries when working with data is mentioned often, which could be an indication of the importance of looking beyond data literacy and into pedagogical resources to ensure data literacy work is designed around tactics that promote such environments (or “academic mindsets”, as described in one of the interviews.
  • Beneficiaries: The people we interviewed are either focusing their efforts on getting journalists to make better use of data in their reporting, or organisations and individuals to make better use of data in advocacy that will lead to social change.
  • Experiential methodology: Often it’s about providing people with a dataset and getting them to develop a story from it; other times, it’s hands-on training addressing different parts of the data pipeline. Most interviewees so far have made an emphasis on the importance of actually identifying and working with data sets.
  • The length of each data literacy process varies. Larger and older organizations favor intensive, long term processes with relatively few beneficiaries; smaller and younger organizations or individuals favor short-term trainings to reach larger audiences.

We will keep you all posted as this process evolves. That said – if you want to add some input, it’s still a good time to take the survey. If you’d like to get in touch with the people behind the research, you can reach us at dataliteracy [at] fabriders [dot] net.

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How can we improve Ghana Government Services?

- May 18, 2015 in Fellowship, Impact


Since returning back to Ghana after more than eight years away, I have heard many recollections from family, friends and strangers about their exhausting experiences visiting government institutions and agencies for various services. Whether it is following a government-given mandate to move from handwritten passports by a given date, renewing an almost-out-of-date driver license or obtaining a work permit for some people seeking to work honestly.

Ideally government institutions will have structures in place to encourage improved performance. However in many emerging nations where government resources are stretched or inadequate, such systems are not instituted even when they exist.  In such a situation, what role can ordinary citizens and non-government institutions play? I have thought about things I can do as an individual to make these experiences better and on many occasions, nothing tangible has occurred. Many of these government agencies struggle to respond to their customers, tax-paying citizens and residents. From what I can see, there are two main factors on which this issue persists:

  1. Government agencies have no incentive to improve the standards of the services they are offering
  2. Users of government services have no collective and reliable information to highlight the poor quality of service provided by such institutions




What if there was a way to incentivize these institutions openly to improve the quality of services they offer? What if users of these services, journalists and government had a reliable resource that easily and consistently showed the performance of agencies we rely on for keys services? Can we build a data-driven tool or service that consolidates these deficiencies together to encourage and demand change? I believe we can!

Creating a crowd-sourced Government Agency Rating system could be one avenue to tackling this. Such a system will produce a rating based on selected factors that reflect the quality of services of these institutions. Factors could include quality of website, ease of payment, presence of online service and duration of service. Ideally, data about these factors will be sourced from a large pool of individuals who use these services for various reasons. Eventually, this data could be collated into an interactive visualization open for public use.



The goal of this project will be to provide access to data about government services to stakeholders. They will then have a reference point to discuss the performance of any service and demand improvements where needed. This means that the system must:

  • Identify the main stakeholders and how they will use such a system on a regular basis
  • Create a structure to efficiently collect data
  • Demonstrate the credibility of the rating system
  • Encourage the use of the system through open access and visualization
  • Train stakeholders on how to effectively use such a system for maximum impact



Ghana as an emerging nation is still learning ways to utilize open data to drive civic and social policies and decisions. Aside creating the relevant infrastructure on which data literacy and engagement can thrive, we must create a culture where individuals and organizations are invested in utilizing and providing data. I believe starting with a simple data-driven approach that targets a major pain point for many Ghanaians creates an opportunity to understand the Open Data landscape while also showing stakeholders the power of demanding and driving a more Open Data culture. I believe the Government Agency Rating system could be a start in fostering this.

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Get better feedback from your data training events!

- November 13, 2014 in Impact


“What do we require to evaluate our programs? How do we show that our program is making a difference? Why is getting feedback important for data trainers? How can we get feedback from training events?”

Last week we hosted a School of Data skillshare with our M&E gurus Rahul Ghosh (Open Knowledge) and Oludotun Babayemi (School of Data Fellow) to explore these questions, and share some methods and toolkits for gathering feedback from training events. This skillshare was tailored to data trainers from the School of Data network, but is also general enough to provide some of the basics of feedback collection and useful methods and tools that can be adapted to other contexts.

This is a one-hour video to learn all about feedback collection from Rahul and Olu:

Learn the basics of feedback collection with slides

Olu and Rahul prepared these slides with corresponding notes and resources. We hope that this will be useful for you when you run your next training event.


Slide 4: Why collect feedback for training events

Slide 5: Feedback collection methods

Slide 6: Types of data collection designs


Slides 9 – 11: Pre training feedback forms & guide

Slides 13-15: Post training evaluation forms & guide

More details:

This presentation has detailed speaker notes. Open the slide deck to see them.

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