Viz for Social Good Interview: Neil Richards, Japan Food Bank winner
Neil did a great job with the Viz for Social Good Japan Food Bank project. Now he shares some insights that might help other volunteers practicing data visualization for the social good.
by Joshua Korenblat, 2019–20 Viz for Social Good Education Lead
Japan Food Bank wanted to raise awareness of rising poverty rates in Japan.
See the project brief that Japan Food Bank shared with Viz for Social Good.
Check out Neil’s Tableau Public project, which is interactive.
What were Japan Food Bank’s goals for this project?
Japan Food Bank’s (JFB) goals were two-fold, firstly to raise awareness of levels of poverty in Japan through visualization, and second to include a call to action so that viewers might help and get in contact.
As a volunteer with Viz for Social Good, what were your own goals, purpose, or mission while working on this project?
I wanted to focus on the poverty rate in particular — how this had increased in every prefecture of Japan, and how the rates themselves varied across each region.
What challenges did you face?
There were a number of available data sources — I always like to have a large amount of data at my disposal because a single small dataset restricts the quantity and variety of stories to tell. The challenge then was to find the dataset that worked for me. Additionally, I wanted to create a tilemap. Having decided that I had the opportunity to show the poverty rate increase across each geographical area, I determined that a tilemap would be ideal but I knew I would have to create one myself since I wasn’t aware of one in existence. A final challenge was my lack of knowledge of Japan’s geography. I was aware of the shape of Japan and its two main islands of Honshu and Hokkaido but I didn’t know how its different regions were laid out (I hadn’t heard of “prefectures” before!)
How did you resolve those challenges?
I designed my own hex map. This is something I have a lot of fun doing, through downloading hexagonal graph paper and sketching my own designs until I was happy I had the best approximation. Because this was a new concept for Japan (unlike better-known hex maps such as the USA) I was aware that it would help my readers a lot more to have the traditional Japan map for cross-reference. The final design decision was to allow the map to diagonally “cross” the landscape shaped design from bottom left to top right, allowing the top left for title/instruction and the bottom right for the reference “real” map.
Reflections
What is one thing you learned about storytelling with data from this project?
I learned that when the specific goal of your visualization is to come up with a call to action then it’s important to focus on one simple story well-told. If we want people to gain awareness of poverty issues in Japan and ultimately contact JFP or donate, then we just need to focus on one poverty measurement and tell the story well, rather than pack a visualization with different facts telling the same story.
And what else?
In particular, finding a story that was national (as opposed to regional) meant that I was able to keep the geographical scope as wide as possible (i.e. covering the whole of the nation of Japan)
What intrigued you about this project?
The main intrigue for me was to visualize Japan in hex map form. I learned plenty about the map and islands of Japan while creating my visualization!
What confused you in this project?
It took me a while to find an angle. There was more data than I needed, with a number of data sources. This is a good thing, but it made it harder initially to make a start while I considered how I could find a story and which data I would need.
What would you do with more time, knowledge, or resources?
I’m really happy with the final visualization. With more time/resources I could have considered adding to it, perhaps devising a longer form visualization with more information (additional charts). But I don’t always think that’s necessary.
Consider the following questions related to this project…
How did you see this project with fresh eyes?
I’d already seen a few submissions before I made a start. So my fresh eyes told me that there were stories emerging about the rise of food banks in Japan and poverty levels in general. I, therefore, knew that if/when I dig into the data I should be able to find something.
What might you have been assuming at the beginning of the project?
I think I was expecting a more divided Japan. I thought I would learn that poverty was an issue in deprived areas but not an issue in more well-off areas. In many ways, I didn’t learn as much as I thought I might about the demography of Japan, because the story the data ended up telling me was that the rising poverty rate was an issue across the board.
What matters most about this project, to its stakeholders and to you?
I think the most important thing is to put yourself in the place of the intended audience. In this case that was quite easy because I am probably an ideal candidate — an educated user from a well-off country who may not be as aware as he should be about poverty issues in a country over the other side of the world. It made it easier to tell the story and try and meet the stakeholders’ brief because the data and the findings from it were new to me too. Finding a story that resonated with me made it easier to tell as if my audience were people like me and therefore also helping meet the stakeholders’ brief
What’s the benefit of being an expert in working with data? What’s the benefit of being naïve?
The benefit of being an expert in working with data is in knowing what’s possible. It becomes easier to get a feel for whether or not it is possible to curate the data to find the dataset you need to tell the story. However an expert in being naive is that you think of the story first and are not intimidated by the data, you won’t necessarily restrict yourself to what seems like a simpler solution. That’s why collaboration works so well in VFSG hackathons and events — the best idea and the best solution doesn’t have to come from the person most expert in data (the chances are, it won’t!)
What questions do you still have that have no immediate answers?
Probably the biggest unanswered question is the “why” rather than the “what” — we don’t always need to know that as data visualizers, and we often don’t know. In this case, I don’t know enough about recent socioeconomic conditions in Japan that would explain the results I visualized.
In what ways did you move away from what you already knew?
In most ways — I chose to challenge myself with a new chart type about an issue I knew little about! This is always a goal of mine in data visualizations, while I still consider myself a beginner who is learning with every creation. That’s why community projects like VFSG represent such great opportunities to improve skills as well as all the benefits for the end client.
How did you slow down and consider the needs of the client?
This is mostly in the form of the non-chart elements of the viz. It’s so easy to concentrate on the main chart (in my case, the map) but the context and explanations are key so as to make sure the message is communicated properly. Specifically, the call to action elements are important for the client but it’s important that they are not just randomly placed on the visualization, but they allow the reader to travel through the full visualization and provide context for the map.
Educational resources
What can we learn from Neil’s project and apply toward our own work? We can use this Viz FlightCheck, adapted from Stephen Few, to articulate why this project works. These lessons can then help us understand the types of choices we can make when designing a visualization for the social good. As educational theorist John Dewey noted, real learning happens not just in the making, but in the reflecting that happens after making.
As described by Stephen Few, a viz works when it’s Informative & Emotive. To reflect upon this viz or FlightCheck it before you publish one yourself, simply look and read your project, and then connect the dots on this rubric. Overall, you’ll want the rubric to show 4's all the way down. You can write down adjacent to this assessment where you need improvement, and where you went above and beyond.
I added Collaborative to the mix because the question of How to make a viz will always be collaborative. After all, you’ll be seeking feedback from other people. And data viz requires not just collaborative teams, but collaborative people. You need to be willing to wear many different hats, as a reporter, writer, analyst, and designer, for instance. By circling all of the roles you played in the project, you can better identify how you work on these complex projects.
How would you evaluate Neil’s data viz project using this rubric?
Overall, I’d say Neil’s project is Informative (useful, complete according to the client objectives, perceivable, truthful, and intuitive). It’s also Emotive. The tilemap is aesthetically pleasing and the unusual arrangement of small multiple charts creates a pleasing display of variety within unity. The photograph gives us a portrait of the stakeholders involved in the data visualization. People care a lot about faces, so it’s always a good idea to put a pictorial face on an abstract data visualization.
Here are some additional resources that are helpful for Viz for Social Good and storytelling with data from mission-driven organizations.
5 Simple Techniques for Powerful Data Storytelling, Brit Cava
Here, Brit Cava offers a simple pattern for telling relatable, engaging stories that humanize data.
Sharpen your Data Storytelling, RJ Andrews
RJ Andrews, the author of Info We Trust, shows how we can learn about data storytelling by looking at the storytelling patterns offered outside of data visualization, from museums, films, and posters.
TED Talks, Chris Anderson
The reason TED Talks work: they don’t feel like reports. Even in a data-rich presentation, a little bit of drama can go a long way.
Are you interested in how data viz can support the purpose of mission-driven organizations? Would you like to pitch in to make a difference and practice your data viz skills? If you join Viz for Social Good, you’ll join a global community of people at all levels of experience, and you’ll get feedback on your work and the chance to have your work used by an organization. While the Japan Food Bank project is now closed, many future collaborations are on the horizon. Become a volunteer with Viz for Social Good on behalf of Furniture Bank.
