Live Blog: School of Data – What is it?

This is a liveblog of a talk at the 2016 Data Literacy Conference, hoster by Fing.  This was liveblogged by Rahul Bhargava and Catherine D’Ignazio.  These are our best attempt to record what the speak was talking about – any accuracy errors are our fault.

Dirk Slater and Cédric Lombion are introducing School of Data by illustrating the challenges they face. It was originally launched in 2012, hosted out of the Open Knowledge Foundation, with idea that decentralized content would spread the idea around the world.

They realized several things: 1) online only was not enough. You need offline training as well. 2) Partnerships are necessary as well as translation into other languages if you have international aspirations. You have to go into the field and work with people who know the local context.


School of Data has members/partners, fellows, staff and a steering committee. They have a set of problems they have been working on.

First problem: People don’t know how to work with data. He shows an example of Ximena Villagran, a fellow from Guatemala, who developed flashcards to teach people how to work with Excel pivot tables.

Second problem: People don’t know how to run data projects. You have to have a methodology and a data mindset. For example, they have been working with Oxfam who has been pressuring governments to open data sets around French Banks’ subsidiaries in tax havens. Oxfam staff had spent two months hand-entering the data which, with some training, could have been completed in a day. School of Data worked with them to show how to streamline these processes.

School of Data has developed techniques like the data expedition workshop, and the data pipeline, to support folks learning how to work with data.

Problem 3: How do we scale this work? They only have a team of four staff members. They believe in face to face trainings, so they built and scaled a network. The people who are members are specialists in their audience and their context. They have people in the Philippines who are managing public resources but don’t have access to computers and email. In Zambia people are working on health. It wouldn’t be possible for one org to do this in one way, so working as a network is very important.

Problem 4: How do we share innovation?  Sharing innovation is hard, because this involves significant documentation.  Their summer camp helps start this, they have templates to support this, and the innovation fund that supports this via mini-grants.  Their goal is to document so others can use this more effectively.  The data viz card game is an example of this (based on the datavizcatalog site).  Developing this further required support and funding.

Cédric hands over to Dirk to discuss how to improve their data literacy efforts.

Problem 5: How can the School of Data network improve data literacy efforts? They found that the School of Data curriculum is used by many to do their trainings.  The “pipeline” is used by many outside of their network. The network has effectively become a community of practice.


Problem 6: How do we measure the impact of data literacy efforts? To do this they wanted to understand how the network practitioners understood data literacy. They got a huge range of responses from understanding a spreadsheet to using data how to solve problems. Dirk and Mariel standardized their definition to “The ability to apply and use information to make change.” In order to measure impact they wanted to understand ways of doing social change and also understand who is doing the change (activists? CBOs? NGOs? governments?) For the network, this is really varied. We collectively need to be better at driving institutional change.

Problem 7: Can it be sustainable? The network is trying to understand how it can be self-sustaining for the long term. The NGOs in the network can monetize and productize their trainings for example with more of a “fee for service” model. They feel they need to move to make new partnerships with schools, civil society efforts, development initiatives, and the private sector. School of Data can help connect open data transparency efforts and citizens, for example.

Cedric wraps up by offering School of Data as a social and technical resource to the audience.  They are trying to improve themselves as a platform to support their network of field operations. This contextualized work is molded as needed to suite the neets of each place.

Charles asks what their next challenges are. Cedric shares that the biggest one is spinning out of OKFN, and becoming completely financially independent.