The speakers were amazing and well prepared and the visualization tools were indeed incredible.
All four panels seemed to have only two target audiences in mind, mainstream newsrooms and highly literate consumers.
Geo-location and mapping are NOT the only visualizations possible
Most of the visualizations presented were based on location and mapping tools. While geo-location is indeed a great way to represent data, it is not all about location. Additionally, most of the mapping tools presented were extremely complex, to the point where I could not understand half of the maps that GIS analysts Tiia Palvimo and Aki Kaapro presented.
Why is data visualization useful if at all?
The entire conversation never touched on the main point of data journalism and visualization. Why is this important, and what is the goal? None of the speakers touched on the actual results of data visualization: does the audience understands the topic better? Do newsrooms actually conduct any surveys on what people get our of visual representation of data? If you need a PhD to understand a map, then would it be better to just look at a spreadsheet?
How do we make data relevant?
I have been discussing the open data project in Kenya with several colleagues and one of the things that the KODI illustrate very well is that open data is not synonymous with interesting data. To make open data a real tool for democracy and transparency data has to be made not only digestible but also interesting. And this is exactly what journalists should do and the best way to do it is by putting a face on that data, or to build a story around it. This aspect was completely missing from the entire session.
How to we transform journalists into data analysts?
When dealing with open data in developing countries, the primary issue to be solved is not the visualization, but the prerequisite understanding of what the data is saying and being able to interpret the data in a way that would lead journalists to understand where to look and what is the reality behind the data. This is one of the main reasons why Internews has been doing training for journalists not only in using the data, but also in analyzing the data before they are able to visualize it. Ultimately you can visualize all the data you want, in very fancy or simple ways, but the work of the journalists on the ground does not start of finish with the data, but with the ability to extract (and convey) more information with it.
Technology and visualization are NOT always the best way to make data open
The disappointing aspect of the entire session was the extreme focus on technology tools. It was clear that the only audience the organizers had in mind was a highly educated, internet literate audience with internet access. What about the largest part of the population in places like Africa that does not have access to internet and even less access to education? Is it open data not for those people? Can we only consider open data visualization and the role of media as related to the use of new fancy technologies?
I find that there were so many missing topics in the conversation and too much focus on the technology, the data visualization tools, and not enough on why data visualization is important and who are we targeting for its use. If the ultimate goal of data visualization is to influence decision-making processes, we should include a larger audience, since helping people in making better informed decision is ultimately also a goal for media and journalists.
Apart from the lack of the above mentioned topics and discussions, two speakers stand out in the Data Journalism and Visualization session: Farida Vis, Research Fellow in the Social Sciences, Information School at the University of Sheffield, UK and Maya Indira Ganesh, director of the Evidence and Action Program at Tactical Tech. The former for the incredible research that showed how journalists are actually using social media and the behaviors that people displayed through Twitter during the riots in England last year.
Maya was notable for the very thoughtful speech about key challenges activists face when working with data visualization, by focusing on a project with sex workers in India. Maya presented some very interesting lessons learned on how best to turn information into evidence and tools and tips for visualizing data as part of a strategic campaign.