Data, Empathy, Design, Information, and Experience: Saying Hello to 2020
If our aim is to inform the average person, we should engage them with informative experiences
It was 2015 when my first data journalism project was awarded one of the most important prizes, the Data Journalism Award, best infographic of the year, small-newsroom category.
Needless to say, that award gave me incredible confidence in what I was doing. It pushed me to invest in exploring new forms and practices to inform visually, especially in a social setting. Almost five years have passed, and I think it is time to take a metaphorical step back to observe what I did and do with a little bit of distance, to foster a reflection that might be useful to inform my next steps in the data world that may be useful for the DataViz community.
I usually work and write on visual journalism projects made of small data, which does not require a computer elaboration in order to be understood by humans (in the online context) and this obviously has an influence on the approaches and methods I rely on in my projects. The online world is probably the fastest context that currently exists and in which many people now are immersed, involved, and overwhelmed, so how do we affect our readers, engage, and hopefully inform them? It depends. To answer, I experimented with diverse strategies, media, techniques, tools, and approaches that led me to finally shape the concept of informative experiences. It is not a real answer, I know 😊, but a different lens under which looking at the design of information, involving also a holistic and human-centered perspective.
What I call informative-experiences are those projects that tend to shorten the distance between the concepts of information and experience. While information is indirect, it is written or told by somebody else, experiences are direct, and they affect and touch us personally. Moreover, when we live an experience, there is a greater probability that we will remember it.
Just to be clear, everything we interact with produces an experience. Everything passes through our mind and body; but what I am trying to describe is when we should design having in mind the whole experience in which our projects are consumed: context, time, medium, cultural context, etc. As information designers, we should take into consideration not only quantitative data and their visualizations, which are just a small part of the complexity but many other contextual, human, qualitative factors.
Let me explain it better through a couple of examples:
The People’s Republic of Bolzano is a project that we (my team and I) published in 2015, which aims to dismantle the idea of an “invasion” of Chinese people, or even the existence of a Chinatown, in Bolzano, Italy where I live. The first migrants from China arrived here in the 1970s and in 2015 there were 633 people or 0.6% of the citizenship (Astat, 2014). While the data are very clear, many citizens were concerned with the perception of the increase of Chinese people and businesses in the city. Data appeared weak to shorten the shift between perception and reality. There are many reasons behind this biased perception: socio-cultural factors, the sensationalism of the local press, and the role of online media for instance. Sarah Trevisiol, an anthropologist that was part of our design team, helped us to tell what data can’t say by providing intimate video interviews with Chinese people living in Bolzano; richly personal stories, dreams, perceptions, fears, reflections, etc… in other words: qualitative data.
Once the web project was published, we made several interviews to evaluate the efficacy of the data and the video's impact on people’s perceptions… long story short, the majority were surprised by the high skills that some of the protagonists of the videos have in speaking Italian.
A fact they didn’t expect, and we, too: the videos were originally meant to debunk cultural stereotypes on Chinese culture, not to impress people with language skills. We took the latter for granted since many of the Chinese people we interviewed grew up and were educated in Italy. It was a surprising side effect that in the end worked much more than other strategies to push those people to reflect on the inaccuracy of their stereotypes. In that case, qualitative data worked effectively toward the goal, affecting and surprising the audience, touching people, so providing an experience, which impressed them.
A similar reflection emerged in another project I made for KnowAndBe.live in Milan, in 2018, with the specific aim to trigger a bottom-up request on one of the most avoided topics: cancer. The reasons why people refuse to get informed about that disease are varied, among them the many clichés that connect it to death, as well as a traditional scientific communication, very often data-based. Again, quantitative data revealed their limits to motivate people in getting informed on cancer and raise awareness of cancer prevention, as emerged by the early researches led by KnowAndBe.live.
For these reasons, I designed an experience that combined a gamified approach with a participatory data physicalization, which asked participants to guess on cancer-related data (i.e. “How many people in Italy get a cancer diagnosis every day? 100, 500, 1000, 2000, 5000, >5000” ). The act of guessing instills a doubt, especially when the answer is not known, arousing a strong curiosity that pushes participants to learn the right answer after they guessed. This gamified approach, together with the physical dimension, returned a more playful and light experience where people interacted with, and finally pushed them to learn the answers, which we provided through an informative booklet.
Then we interviewed participants after the experience, in order to collect insights on their participation. We found that the majority of the participants realised that they didn’t know the cancer statistics. At the same time, they were quite astonished about their knowledge gaps.
Even in this case, we moved quantitative data from the main to a secondary role of our projects, turning it into raw material, rather than the protagonist of the project. I think it’s time to move beyond the beautiful visualizations, which celebrates a certain self-referential data culture. If our aim is to inform the average person, we should involve them in the design process, or at least understand their concerns, cultural levels, behaviours, desires, etc., to design things that they are able to grasp and engage with. We can’t expect an average audience to take time in decoding complex and beautiful visualizations, but we can design the conditions to aim for that by pulling more UX process into the data visualization practice.
On these reflections, I founded Sheldon.s tudio, the first studio focused on the design of informative experiences, which aims to foster a better-informed debate and society. How? Through an interdisciplinary workgroup, made by social scientists such as sociologists and anthropologists, but also journalists, computer scientists, to return a wider audience as many facets as possible of the reality, relying on quantitative and qualitative data, toward less biased and more fitting to reality perceptions, for the sake of democracy.