For data visualizers, I thought it might be instructive to consider the upstream activity of data collection, which is a process fueled by questions. This article contains a mix of synthesis from folks like Sheila Heen, Erica Hall, Adam Grant, Dr. Tasha Eurich, Brandon Stanton, Rob Walker, Ximena Vengoechea, Rebekah Modrak and Jamie Vander Broek, and many others. It also reflects some techniques I’ve picked up after many years of trial and error conducting user research. 

Why bother exhibiting curiosity?  

Let’s base this discussion in our personal lives. Conversation IS our means of relating to others. A Harvard study of dating conversations (online chats and in-person speed dates, what user researchers refer to as dyads) revealed that people who demonstrated curiosity were more likeable. In online chatting situations, the folks who asked many questions got to know their partner better and were thus better liked. Among speed daters, those who asked more questions got more dates. In fact, asking one additional question of their conversation partner meant more second dates.

Note to hopeful online daters: follow-up questions are the most successful. They signal to your partner that they’ve been heard and that you want to know more. Plus, they’re often spontaneous and don’t require much preparation (provided you’re listening actively).

Where might we apply these findings professionally? What about during job interviews, networking at industry events, waiting for Zoom calls to start, or in proactive outreach to your less-frequent professional contacts?

But why are curious people more likable?

People like to talk about themselves. That same Harvard research found that 40 percent of everyday speech is spent telling other people what we think or feel—basically, talking about our subjective experiences. In fact, research shows that talking about ourselves, regardless of the platform, triggers the brain’s pleasure sensation.

Besides feeling good, asking questions also communicates humility—that you know the limits of your own knowledge. Inquisitiveness conveys a powerful combination of “soft skills”—empathy and curiosity—in addition to humility. Admitting what you don’t know gives others the chance to share their perspective AND can help shape your understanding.

Again, how can we apply these findings in our professional lives? Would it surprise you to learn that most people are too self-promoting during a job interview? Asking questions can help you better understand the contours of the opportunity. Even a question like, “what am I not asking you that I should have?” can reveal critical attributes when weighing decisions. The answers to these questions can help you evaluate prospective career shifts. 

You can be intentional about developing adjacent skills. Adjacent skills are those skills that border your existing capabilities and these can encompass “soft skill” development. Anne-Laure Le Cunff, founder of Ness Labs, recommends brainstorming as many potential new skills relevant to your current role as possible. I applied this advice in my own career when expanding my market research practice into user experience research. Brandon Stanton, the creator of Humans of New York (HONY), is one of my favorite examples of wildly-successful adjacent skills development. When he began the HONY project, he was focused on developing his photography skills, instead he honed the ability to build rapport and tell stories that have the power to change people’s trajectories and beliefs–and these are the skills for which he has become known.

“I wanted to photograph ten thousand people on the streets of New York City. I had the added goal of plotting these photos on a map. It seemed like the mission of a madman, especially because I had no training as a photographer. But the impracticality of the goal served a purpose. It got me out on the street. Day after day. Not only learning to photograph, but also to approach strangers, make them feel comfortable, and engage them in conversation. Over time, these peripheral skills would become more central to Humans of New York than the photography itself.”

— Brandon Stanton

What value is there in learning to ask questions?

Asking questions can unlock value. Demonstrating curiosity about others can demonstrate knowledge to prospective clients and promote bonding among team members. Asking questions can uncover and aid in avoiding project pitfalls. The act of questioning can:

• Spur learning and idea exchange
• Fuel innovation
• Improve performance
• Build rapport
• Mitigate risk
• Signal engagement

And, this is a virtuous cycle skill: asking questions improves emotional intelligence, which in turn makes us better questioners. Try this: the next time you catch yourself getting ready to make a judgement try asking a question instead.

There are typically two categories of goals in questioning: information exchange and establishing a positive impression. Understanding your objectives can help you choose the right mix of questions. What do you need to know? What do you want to do with the answers to your questions? Different goals necessitate different methods of inquiry. Quantitative questions are typically close-ended. Survey questions are often quantitative, with answer choices like yes or no or questions that ask you to rank or rate your options. Qualitative questions are usually open-ended. They allow for a broader range of—sometimes unexpected—answers. Design researcher, Erica Hall, explains the difference between qualitative and quantitative questions like this: a quantitative question might be, “How much money are people spending on dining during COVID?” while a qualitative question is, “How are people deciding what to have for dinner during COVID?” 

Another way to think about your objectives is in terms of the type of conversation you expect. Are you anticipating a cooperative discussion? A competitive one? A bit of both? Framing—things like setting, tone, group dynamics, etc.—is critical to the effectiveness of your efforts. Think about establishing a disarming environment for asking questions. For example, I have found that I am best able to have hard or sensitive conversations with my kids when we’re in the car. We are less distracted. Neither of us can leave the “room” and we are both facing forward, thus we aren’t forced to make eye contact. 

If the conversation is competitive and you anticipate reluctance, NYTimes best-selling author, Sheila Heen, recommends starting with the most sensitive questions first. Her techniques include using direct, close-ended questions and phrasing questions so that it is easy for your conversation partner to respond affirmatively. For example, if you think a supplier is going to miss a delivery date, you’d ask, “So, it looks like you’re going to miss the deadline?” It turns out that people are less likely to lie in response to a pessimistic assumption. Conversely, in a tense environment, close-ended questions (e.g., yes/no questions) work better because they don’t allow for much “wiggle room.”

If the conversation is cooperative, but you anticipate avoidance, start with the least sensitive questions first, to build rapport. Use open-ended questions to draw your conversation partner out, and again, use negative assumptions to frame tough questions. Casual questioning works better when building rapport than using a formal tone. People are more responsive if you give them an out (e.g., there are no “right” or “wrong” answers, you can change your responses at any time). An individual in a group setting may respond differently than they would one-on-one. Quiet or closed-off respondents can derail group sessions or leave important topics unexplored. With that in mind, a skilled facilitator can vastly improve a group session like a workshop or a design sprint. 

What about the inevitable awkward silences?

Though much-maligned, silence is extremely useful in conversation—especially when awaiting the answer to a question. An extended pause can mean that the person is still processing. Pausing can encourage a mindset shift from fixed to reflective—resulting in expanded possibilities for both sides. Sharing silence can be a means of reinforcing rapport. Silence can create space that can change the tenor of the conversation. Sometimes, especially in a difficult conversation, silence is necessary to give a person the grace to calm down. As such, avoid the inclination to interrupt or move on too quickly. This is much easier said than done! Giving someone a chance to speak without interruptions is a gift. It requires patience and self-discipline. In practice, if the answer you receive is something like, “I don’t know how I feel about this…” a gentle nudge that can be effective without interrupting is, “Because?” This approach invites your conversation partner to finish their thought. 

What if you find it difficult to ask questions of others?

Fellow introverts, you may need a little more prep time before a conversation, or an alternative format to in-person. One resource you can consult is the Question Formulation Technique (QFT). You can use this technique to interview candidates, evaluate prospective service providers, or even develop a podcast interview. The QFT steps are:

1. Develop a list of questions
2. Categorize the questions either open end (qualitative) or closed end (quantitative)
3. Determine how you plan to use the question and, if necessary, change closed to open
4. Prioritize your questions: what do you need to know? What will you do with the information you collect? What answers will have the greatest impact? How much time do you have?

The Complete Guide to Writing Questions is another resource I’ve used, especially valuable when writing survey questions. Yet another option for building your question-formulation muscles is to practice active reading–which you can do by yourself and at your own pace, using your own library. Ask yourself pre-reading questions like, “What do I already know about this topic?” “Why would an instructor assign this book?” Summarize the text by writing questions in the margins. At the end of each paragraph practice asking the questions, “What does it say?” and “What does this mean?” or “Where could I apply this?” Write your own exam questions based on the reading. 

In terms of live interactions, in the pre-COVID world, I found networking at conferences drained my energy. To address this challenge, I learned to narrow my focus and pick out someone who looked uncomfortable with whom to strike up a conversation, usually by asking some questions I’d developed in advance. And, even though we have all become accustomed to video conferencing, you can still opt for other, less-intrusive types of interchange. One option is the good old-fashioned phone call. Like the kids-in-the-car example, a phone conversation can be less-intimidating. You can still hear people “smile” in their voice and this format may put your conversation partner more at ease–especially if the topic is sensitive. Live chats can sometimes be preferable to a written exchange, too. In an in-person conversation you can make mistakes and correct them in a way that you cannot in email or text. 

Though, text-based conversation has its benefits as well. Consider whether a text-based conversation or collaboration (e.g., using a virtual whiteboard or an activity-based, online research platform) would work–for even part of your questions. A text-based exchange may allow for interaction with folks who would be less likely to speak up in group settings or who are more comfortable expressing themselves in a format that allows for some on-the-fly editing. 

How else can you condition your curiosity?

I have found that self-reflection, or the act of asking myself questions, can help me overcome feelings of frustration and powerlessness. For example, Mariame Kaba (h/t Ann Friedman’s newsletter) offers these questions to ask yourself when you are outraged by injustice:

1. What resources exist so I can better educate myself?
2. Who’s already doing work around this injustice?
3. Do I have the capacity to offer concrete support & help to them?
4. How can I be constructive?

Similarly, the team at OpenMind has a tool you can use to ask yourself questions before navigating difficult conversations. Their Conversation Simulator gives you the chance to practice your skills in anticipation of your upcoming holidays with family, for example.

Data analysis cannot answer a question that you did not think to ask

Asking questions is a form of data collection. Most of what we’ve discussed so far are qualitative lines of questioning; these produce unstructured data. The alternative approach is quantitative inquiry, for example, sending out a survey. Those results are structured data. Quantitative approaches are thought by some to be more efficient or ‘cleaner’ to conduct. It is true that structured data analysis is often more straightforward. However, qualitative methods are more conducive to identifying faulty assumptions or prospective pitfalls. And, organizations are frequently surprised by how few customer or stakeholder interviews it takes to yield actionable insights. From a study cited in Harvard Business Review, the team harvested actionable insights about company performance after 18 – 20 interviews. In user experience research, we are often able to inform design and development decisions with as few as five users.

This same study found that client and manager priorities coincided only 50 percent of the time. The authors conclude that quantitative studies are usually written based on what managers think clients want. If you missed the mark on capturing those wants, the error is then compounded with techniques like ranking. For example, if the question asks you to rank requirements based on your own usage, but you are not the primary user of said functionality, the study results may suggest that you don’t care about something that you do indeed value, but for which you are not the primary user. Generative or exploratory steps can inform further quantitative options to help reduce the occurrences of questions you didn’t ask.

No one is omniscient. Yet, we are often making decisions with the best information we have available at the time. Asking questions to supplement our own understanding improves the quality of this decision-making process.

Now that you know how to ask questions, how can you pair that skill with listening?

Active listening can be transformative. Documentary filmmaker Valarie Kaur posits that, “We risk being changed by what we hear.” We are always listening to the thoughts in our own heads. Active listening requires us to quiet those thoughts. Listening, like allowing a person to speak uninterrupted, can change a narrative. One way to signal that you are listening actively is to repeat back a bit of what you heard the person say in a follow-up question. This essential practice gives the person a chance to clarify or correct their statement and it reinforces that you understood what they meant.

Journalist and author, Rob Walker, observed, “One of the wince-inducing rituals of my job as a journalist is transcribing interviews and listening to myself fail to listen.” As a user researcher who watches and listens to herself interviewing people regularly, I have made the same cringy observation in my own work. 

“…There’s always at least one moment when I miss a chance to pursue (or even step on or get in the way of) a source’s smart point or original observation by rushing to (try to) make my own. This is a failure of attention on my part—and a failure of humility, too.”

— Rob Walker

I have the opportunity to practice active listening frequently. When I cut someone off, it’s usually due to one of four things:

• I’m worried about the time (running over my promised allotment or feeling pressure to get specific information in the limited time window).
• I’m excited to add in something related to their point and I don’t want to forget it. It could help reinforce rapport (but not if I interrupt).
• I think I know what the person is going to say (and sometimes I’m wrong).
• I’m showing off (know-it-all syndrome). 

Look for low-stakes opportunities in your daily life to hone your active listening skills. Practice devoting your complete attention during phone calls with family and friends, with your kids, and in casual co-worker interactions (e.g., what did you do this weekend?).

How is listening foundational to productive negotiation?

Negotiating a deal or navigating conflict are skills which require training, according to The New York Times best-selling author, Sheila Heen of Triad Consulting. It is counter instinctual to give someone else the benefit of the doubt. Your best strategy for persuasion is to listen and learn. Developing your second-position skills—the ability to see someone else’s point of view—affords you:

• Insight into a person’s position and better understanding of their perspective
• Input on what’s fueling their feelings, what they care about, how much risk they’ll tolerate 
• Access to their feelings by either naming what you’re hearing OR sharing how you’re feeling
• An opportunity to shift your mindset away from getting an apology or advancing your agenda to obtaining a better understanding of what’s going on with your conversation partner

If the conversation feels difficult, it’s likely signifying something about you: you feel wronged by the discussion, you are reacting to the person themselves, or the content of the discussion is threatening your identity. If you need help identifying your own triggers, try asking yourself: “If I know nothing else about myself, I know that I am a BLANK person.”

Honestly, how coachable are you, really?

Seeking feedback is yet another way of asking questions. And receiving feedback is a different kind of listening. This reciprocity can be difficult. In a study by Sheila Heen and Douglas Stone:

• 63 percent of human resources executives surveyed said their managers were unable or unwilling to have difficult conversations
• 55 percent of employees said their review was unfair and inaccurate
• 36 percent of managers completed appraisals thoroughly and on time
• 25 percent dreaded evaluations more than anything else in their working lives

Yet, people who seek critical feedback tend to receive higher performance ratings for the reasons we’ve already addressed. When you ask for feedback you communicate humility and a personal desire to excel. Try orienting your mindset to receive feedback as coaching or advice, even if that was not the spirit in which it was delivered. Unpack the information with follow-up questions, if necessary. Validate the feedback with input from those whom organizational psychologist and keynote speaker, Dr. Tasha Eurich, dubs “loving critics.” When in doubt, ask for just one thing (e.g., what ONE thing is holding me back?). Alternatively, organizational psychologist and bestselling author, Adam Grant, recommends motivating your evaluators to coach you by asking them, “How can I get closer to 10?” In applications beyond performance reviews, for example if you regularly deliver high-visibility presentations, you might try sending out a regular email to collect top-of-mind questions the week prior in order to address the answers upfront and avoid being caught off guard.

Prioritizing asking questions and listening actively can promote a culture of learning

Contrary to the misperception that they will look like they don’t know what they are doing, leaders who ask inspiring questions signal their humility, which instills trust. Questions like: “Where do we have the opportunity to deliver more value to stakeholders than we have in the past?” model that questioning is valued, especially if these questions are posited openly and often. Domino’s Pizza famously demonstrated this skill when they asked customers how their pizza tasted. When customers told them their pizza tasted “like cardboard,” Domino’s launched a public campaign to show customers what they were doing to improve the taste. In this example, Domino’s also demonstrated the importance of sharing the answers to questions asked to both communicate that they were listening and to jumpstart idea generation. 

And, speaking of idea generation, rather than running idea brainstorms, consider assembling a multi-disciplinary group to brainstorm questions and rank them in order of potential outcome. This mini-design sprint approach establishes a collaborative rather than a competitive environment, resulting in a sense of collective responsibility. Organizations that can learn rapidly and apply what they’ve learned tend to survive and thrive. 

In addition to the abundance of applications we’ve discussed in our professional lives, like job interviews, networking, performance reviews, negotiating, and concept development or prototyping, on a personal level, honing your curiosity exercises a growth mindset and provides daily opportunities for learning, joy, and transformation. Take a moment to ask yourself: what is ONE application where asking questions and attending to the answers would enrich my life?

Many thanks to Katie Kilroy and Data + Women Ireland for encouraging me to develop this material (based on an old blog post) into a presentation, which served as the foundation for this article.

Additional resources:

If you listen to podcasts, pay close attention to questions the host asks. Anand Giridharadas, author of Winners Take All, demonstrates his Q+A skills in his newsletter The Ink (interview format).

If you need inspiration, Rob Walker’s Ice Breaker of the Week is a running, crowdsourced list of great questions. Nightingale has fun exercising our curiosity chops in our Three Questions With… section.

I synthesized ideas from several books in this article. These include: Radical Humility by Rebekah Modrak and Jamie Vander Broek; Difficult Conversations by Douglas Stone, Bruce Patton, and Sheila Heen; Listen Like You Mean It by Ximena Vengoechea; The Complete Guide to Writing Questionnaires by David F. Harris.

The post Curiouser and Curiouser: Crafting Questions and Attending to the Answers appeared first on Nightingale.

Catch up on the conversation with part one. In the spirit of collaboration, we want to hear from you! We’d love to hear your thoughts via the three questions we’re added to the bottom of this article!

Despite the growing prominence of data visualization, our practice is surprisingly light on methodology. While there are many methodologies across sectors, disciplines, and teams for building alignment, many of them are also siloed by role and skill. Similarly, audience research (focused on users, consumers, patients, or communities) is a common practice, but is often “owned” by a single role or department.

Building a shared understanding is a process and a team sport. Taking a more holistic approach to organizing multi-disciplinary teams will help you to craft more focused, intuitive, and equitable data visualizations and to arrive at a shared understanding of how to communicate your data in a meaningful way.

High-quality dataviz and information design does not have to remain solely in the realm of media outlets and celebrity practitioners. Empowered information is the result of a team of people that take responsibility to commit to the nuanced meaning of the data.

Information Empowerment is an attempt to join some high-level frameworks in order to improve impact. In doing so, you can begin to bridge the divides that exist between practices, roles, and the people that inhabit them. It is an end-to-end process that connects the dots from how your data is captured all the way to how it is communicated to your audience.

Okay, let’s take a look at what we mean:

Simple enough, right? By starting with a foundation of data literacy, your team expands its understanding of the data by collaborating with subject matter experts, then applies design thinking techniques to prototype their work and test its effectiveness. Through this collaboration, you leverage the strengths of your team to amplify the impact of your data and how well it communicates to your audience. Additionally, the whole team learns more about the data (and each other), which broadens their respective skillsets. This kind of reciprocal investment in the people and process inspires a sense of collective responsibility, not only for the quality of the work, but also for the outcomes.

We’re advocating for taking a more holistic approach when assembling the “team” and defining the project scope. In order to build an accurate understanding of the data, functional practitioners (e.g., designers, researchers, data practitioners) need to collaborate with subject matter experts (SMEs). The resulting collaborative environment creates a trust-based culture dedicated to a common goal and a guiding practice.

The above process is not necessarily linear, and the three core ingredients of Data Literacy, SME Collaboration, and Design Thinking can be applied in any order — and are often applied in parallel. This is not a bug — it’s a feature! The various steps may be shuffled or repeated in iterative cycles themselves; however it plays out, the goal is to dedicate your team to building a culture of understanding and a commitment to the ethical underpinnings of the data itself.

Leverage the strengths of the team to amplify your insights

To some practitioners, there’s nothing new here, but few teams leverage a defined process for empowering the influence of their work. Outlining a process for your team will help to keep the focus on your audience, their needs, and effective communication of the data. Information Empowerment can be applied to almost any kind of data use case (from business intelligence to research and development to data art and everything in between) and by teams of all sizes.

An early step in a data-driven initiative should include the identification of and outreach to subject matter experts who understand exactly what questions the data could answer, what the data means, how the data should or could be collected and socialized — and even how to refine project goals. Depending on the nature of the initiative, these resources could be internal (e.g., dashboard end users) or external (e.g., small businesses and community members).

Key to the concept is broadening our understanding of who constitutes a subject matter expert (a core tenet of Data Feminism). Data visualizations can be interfaces to expose injustice and inspire change. But, so can people. They bring context. They help prevent misinterpretation. For example, when data artist Jer Thorp was developing the Map Room Project, he reconsidered the potential for reinforcing damaging narratives related to neighborhood characteristics after consulting with Detroit artists, Complex Movements. 

The project encouraged visitors to consider multiple realities of where they lived. “On the maps they can come up with other ways to portray their neighborhoods beyond low-income.” Jer said. “Every map based on census data shows the poor neighborhoods in bright red…One of the guiding considerations came out of a meeting with Detroit artists from Complex Movements. They challenged us to consider how our project was reinforcing the master narrative. These institutional maps remove community from the commentary of their own lives. What other stories do the data tell? What about mapping the churches to illustrate the strength of the community?”

A common objection to SME collaboration in general, and design thinking in particular, is that it is time-consuming. The worry is that workshops, sprints, or research can elongate timelines and impact budgets. That may not be so. Graham Kenny, in Harvard Business Review, makes the point, illustrated by the case study organization’s surprise, that saturation — the point at which you stop hearing new insights — occurred after only 18-20 stakeholder interviews (in this example, the stakeholders were the SMEs).

Collaboration is not something that can be “tacked” on to a project mid-stream. It must be planned from outset. Reciprocity and role equality are necessary when collaborating with subject matter experts. Some subject matter experts, such as patients, nonprofits, and the communities they represent, can feel undervalued due to their lack of technological or methodological expertise. Likewise, certain analysts or scientists may not grasp the significance of design or their own expertise as a barrier towards other people’s understanding. Care should be taken to prevent team members from feeling disenfranchised, patronized — or worse, exploited — which can stem from a lack of understanding about the outcomes that resulted from their participation. In this process, every person should feel valued for the expertise they bring to the collective intelligence of the team.

In summary, Information Empowerment is a process that promotes collaboration to amplify meaning. By examining the context around the data and the real-world expertise that may accompany it, your team will instinctively make a more focused and human appeal. Who knows, you might even have fun doing it.

In the next installment, we’ll take a deep dive into Data Literacy as part of the larger methodology.

What do you think?

1. Where have you seen evidence of converging disciplines or practices within your work, if at all?
2. Do you have an example of your project taking a different course as a result of the contribution of a subject matter expert?
3. How would you interpret the diagram above related to your current process at your organization or work?

Share your thoughts with us at nightingale@datavisualizationsociety.org.

The post Information Empowerment Bridges Expertise to Amplify Impact, Part 2 appeared first on Nightingale.

Jason comes from a design background. Mary comes from a user experience background. Jason is a ‘data IS’ person. Mary is a ‘data ARE’ person. Inevitably, during our work with Nightingale, we share thoughts on our day jobs and the perspectives of our authors. It was in these conversations that this theory began to form.

In the spirit of collaboration, we want to hear from you! We’d love to hear your thoughts via the three questions at the bottom of this article!

Humans are culturally conditioned to absorb a lot of information, combining different types of media and interaction patterns. Often accompanied by illustrations, photos, videos, and text, this information is intended to communicate complex ideas in a way that is clear and potentially interesting. 

Many of us use data to find some kind of objective truth. The collection and analysis of data has become a huge part of our business environment and culture, but collecting data is only as good as how we communicate it, so we regularly turn to data visualization to give shape and meaning to the information. 

The relationship between data and information can mean many different things to different people. We use data to inform across a variety of instruments and media, from dashboards and findings reports, to data journalism, digital platforms, and smartphone apps–all of these leverage data to create information.

Despite the growing prominence of data visualization, our practice is surprisingly light on process. While there are many methodologies across industry, discipline, and design, they are mostly siloed by functional area and expertise. In order to understand how to communicate data in a meaningful way, an end-to-end process needs to be adopted to present the full context of the information to its intended audience. We call this inclusive process Information Empowerment, but let’s take a step back first to explore some background.

If data is a foundational currency, how do you spend it responsibly?

Data is the foundation to gaining wisdom as a basic unit of information. In order for knowledge to manifest itself and influence outcomes, it needs to be understandable and easily communicated. Therefore, to evaluate, understand, and engage with our digital reality, we must improve our ability to interpret and communicate data. Our impact is rooted in data.

In order to communicate our data to an audience, we need to know who they are and speak to them in a language they understand. As Brookings Institute’s Alex Engler explains, “Even when well-articulated, the private sector applications of data science can sound quite alien to public servants. This is understandable, as the problems that Netflix and Google strive to solve are very different than those government agencies, think tanks, and nonprofit service providers are focused on.” In other words, there is no such thing as a general audience of “everyone.”

Converging principles

Across sectors and functional roles, there are many different principles that propose paths to sense-making. Among these are design thinking, co-creation, design for all, storytelling, and on, and on. Additionally, there have been many approaches for more equitable and intentional data handling often rolled into the heading of data literacy. 

Around the world, we see a commitment to user and customer-centric practices, and likewise, among data practitioners, recognition and acceptance of the complexity of data ethics have advanced. This sentiment is well expressed by visual storyteller Catherine Madden, “Data are people. Paid for by people. Collected by people. Analyzed by people. Shaped by people. Even with the best intentions data can’t be 100 percent objective, but we can prioritize equity at every step of the process and be transparent about the limitations.” So prioritizing for communication means putting people at the center of our ecosystems (customers, employees, residents, etc.) and appreciating the value of our human capital.

One of the groundbreaking ideas in Giorgia Lupi’s Data Humanism manifesto is the relationship between the data collected and the action taken by a human that is being recorded in the data. She elaborates, “Data represents real life. It is a snapshot of the world in the same way that a picture catches a small moment in time. Numbers are always placeholders for something else, a way to capture a point of view—but sometimes this can get lost.”

Likewise, anyone who has worked in data can tell you it can easily be misrepresented. Advances in data ethics, such as the intersectional approach by Catherine D’Ignazio and Lauren F. Klein in their book Data Feminism, are helping to expand our attitude towards data collection and to inform more inclusive data science practices based on core data literacy tenets. 

Data literacy poses a particularly stubborn obstacle to realizing many of these principles. Some data literacy challenges can be traced to deficiencies in physical, technological, and cognitive areas. Infrastructure problems arise from legacy systems, ever-changing technologies, and the demands of rapid upskilling which can lead to significant difficulty in comprehension and accessibility for the intended audience.

One way to address physical and cognitive accessibility is to borrow from architects and urban planners who strive to design for all. Data journalist, Mona Chalabi, practices this approach by “designing for the least-informed reader first.” And, economist Raj Chetty “goes to great lengths to make his research accessible. He’s not just speaking to other researchers…He’s presenting information in plain language, in a visual format that one can understand within seconds.”

Borrowing from other disciplines and sectors like these is a means to achieving a broader perspective. Jason and Mary each have experience employing a method called combinational creativity, which involves sourcing existing ideas, and our own consulting experiences, to develop a practical process we refer to as Information Empowerment.

In our next article, we’ll outline this process for combining these various approaches into a high-level framework to guide teams towards mitigating these challenges–so stay tuned–but first, we’d like to know…

What do you think?

1. How do you think about making an impact in your work? To what extent is data communication a goal for you?
2. What kinds of challenges have you encountered trying to make an impact in your work?
3. How have you borrowed from other industries or ideas to meet your objectives?

Share your thoughts with us at nightingale@datavisualizationsociety.org.

The post Information Empowerment is a Universal Theory for Data Design, Part 1 appeared first on Nightingale.

Even when well-articulated, the private sector applications of data science can sound quite alien to public servants. This is understandable, as the problems that Netflix and Google strive to solve are very different than those government agencies, think tanks, and nonprofit service providers are focused on.

Alex Engler, Brookings Institute

Against this backdrop, Sarah Williams, an associate professor at MIT’s Department of Urban Studies and Planning, has built a portfolio from civic empowerment. In December 2020, Sarah will release her first book, Data Action: Using Data for Public Good. She considers it “a manifesto for those who want to use data to generate civic change.” Recently, I interviewed her about her interdisciplinary expertise and the project work that informed the book. The following transcript has been lightly edited for clarity.

When did you start to think of yourself as a “data person?” Or do you?

Sarah Williams: I worked a lot on remote sensing and GIS (geo-informatics systems) very early on in my career trajectory. But I don’t think I ever thought of myself as a “data person” specifically. I always thought that I used data to answer questions that I was interested in. I think of myself as a landscape architect. I have a lot of interest in environment, climate change, and racial equity — that is, applying my skills as a data scientist on environmental and racial equity issues that shape our public landscape. I do think that I’ve been branded more as a data person because of my work at MIT and really trying to emphasize the need to use data to create policy change.

I also felt like there was a missing area, where when we talk about the ethics of data, or we talk about the use of data for both elevating certain positions but also oppressing, that there was perhaps this real hole in the current literature, so I became interested in this stuff. Maybe that’s how I became more of a data person as well.

You’ve worked in all different locations. There are various disciplines involved. Your projects have a variety of applications. I’m curious about the path from one to the next.

SW: I came into data science through geography. I was a computer science and geography major during undergrad. I think my projects have just been a combination of people reaching out to me and me reaching out to them. For example, I have a lot of work in the African continent, and that has to do with somebody very early on in my career asking me to get involved in a project with Nairobi. I developed a commitment to that region. At first, the goal was to improve the condition of the city of Nairobi, but then there was this realization that what we were doing in Nairobi could not only be applied to other cities in the African continent, but also in the global South in general. A lot of the work that I’ve done with informal transit really started there.

[Author’s note: The Digital Matatus Project is an open data effort that collects transit data from cellphones for use in mobile routing applications.]

I’ve also done quite a bit with criminal justice and criminal justice policy — looking at issues of equity and race. In fact, one of the chapters of my book covers the ways in which we can use data to help highlight some of the injustices that exist within our criminal justice system. That started as an area of interest and after I left grad school when I got involved in the Million Dollar Blocks Project and just kind of kept going.

[Author’s note: The Spatial Information Design Lab and the Justice Mapping Center sourced inmate residential addresses from Bureau of Justice statistics data and census data to show blocks where more than one million dollars is spent annually to incarcerate residents.]

Recently, I’ve been reinvesting in restorative justice work. Right now, we’re looking at a visualization project that examines prisoners rights, especially related to workforce — how much they get paid and some of the injustice involved in the way those jobs are created. There has been recent coverage related to prisoners fighting fires on the West Coast, but then they can’t actually become firemen after their incarceration.

I’ve also been involved in “data literacy” projects. Data literacy needs to be included in our school curriculum. We use data all the time, and it should be a skill that we learn, just like we learn math. City Digits focused on using data as a way to teach youth about issues in their community, while learning math at the same time. We relied on the kinds of data points that were most relevant to the particular community with whom we were working, tying the teaching to a real-world subject. We worked with the Bushwick School for Social Justice and we embedded data literacy within the math curriculum.

We used maps quite a bit because maps are oftentimes fractions, right? And, we taught ratios and percentages — for example, the percentage of African Americans in a community. We also decided to pick a topic related to a particular issue that the students wanted to investigate. With one particular class, we examined lottery tickets, which also involves math. We could look at the percentage of people who buy lottery tickets and cover not only how much money they spend on lotteries, but also the probability that they’ll win. That way, we could demonstrate how to collect data or where data comes from, but then actually take it to the end and show them, using math skills, how that plays out.

How do you get non-data people over the relevance barrier? How do you get them to engage?

SW: So you mean like how do we move them from, “This is a stat or a number” to something where they can take action? It’s absolutely about visualizations. I’ll say it over and over again, the communication strategy is the number one way that I get people to understand the power of data. In almost every project that has been the case. Consider the Digital Matatus Project where we collected data on informal transit systems in Nairobi. Everyone knew that data was important because they’d heard data was important. They knew the hype around smart cities meant you must have data. The city and the officials were kind of loosely interested in the project until we created visualizations of the concept and showed it as one comprehensive system that they could use to make decisions.

It just transformed that project and really created something that the government, NGOs — everybody — could use because now they could understand what that data meant and what they could do with it.

Visualization is the number one way that you communicate the power of data.

Sarah williams

I talk about this idea in Data Action. Very early on, statisticians knew that they needed visualization as a skill to communicate their efforts. Building interdisciplinary teams is critical to making powerful visualizations. You need policy experts in the field who help contextualize the problem. You need data scientists who can help process that information. And then the designers and the communicators who can transform and translate those insights to the broader public. One further team member of critical importance, though, is the community represented by the data itself. The community feedback is absolutely essential. I don’t know how many times I’ve been in a meeting where the stats are wrong, and somebody from the community could have told them that right away, had they just asked.

Tell me about your experience with the networks that develop and evolve to continue to support some of this community work?

SW: In Nairobi, we have a center for the development of open data for transport. We additionally have one in Latin America, called DATUM, which is also focused on development of data for informal transit. The Latin American network was informed by the work that we did in Africa. To step back for a second, these are the main bus systems in most of the world. It’s only Europe and the US and some parts of Asia that have more formal systems where data are collected and can be analyzed. In these informal systems, the data just do not exist. So when we did the project in Nairobi, we sparked interest from a lot of people who wanted to do their own data collection. We started to help them use our tools for their projects. Then, those people started teaching other people. And, through that, we built this network. Then, we actually raised funds to keep that network going. As a result, now on DATUM, there are tutorials, links to resources, and connections with other groups that have done the work.

This kind of data collection is hard during COVID, but we recently finished a project in the Dominican Republic, that was informed by what we learned on a project in Mexico City. Now, I don’t have to be personally involved — the network can be teaching other parts of the network and people from the Latin American context can be teaching each other.

Part of what we recommend as critical to this network is connecting to local universities — having the local communities do all the data collection and work with students or others in that process. We’ve created training materials that go through how to get started and who to connect with in your community. For example, on the transit work, getting buy-in from the local transit system owner was a major first step. Typically, they have a union. It’s not just the government that you need to talk to, but it’s also making sure that you talk to the drivers, the actual workers, as you get started.

Where are some opportunities you see for addressing inequity with data?

SW: We live in a world where we think data is everywhere. One of the things I talk about in the last chapter of my book is missing data. We have so much missing data, and that missing data tells you so much about what we’re interested in, what we care about, but also it can really lead to inequity. As practitioners, we talk a lot about showing observations in data as being inequitable, but what’s missing can be just as inequitable.

Ghost Cities was a project a funder brought to us. The guiding question was: how can we create socially-equitable real estate in China? These ghost cities that have been manufactured in China are going all over the world and they’re not equitable. They create huge risk in the real estate margins. We set out to explore how we could we address it with data.

[Author’s note: Researchers scraped data from from Chinese social media open access API’s, including Dianping (Chinese Yelp), Amap (Chinese MapQuest), Fang (Chinese Zillow), and Baidu (Chinese Google Maps) to evaluate community viability and score foreclosure risk on the Ghost Cities project. The model identified areas without amenities and allowed the team to map these over-developed locations.]

How have you been able to open policy dialogues or get invited to those tables?

SW: A lot of my projects are kind of bottom up. On the Digital Matatus Project, we didn’t have the data we needed to answer the questions. But, we were constantly building dialogue on transportation. And, on the Ghost Cities work, which was also bottom up, I really had to go after it, really leverage my connections and start talking to people in China. But, the biggest door opener was when we made a website where people could visualize our analytics and play around with them.

After trying to get a sit-down with academics and real estate agents and getting nowhere, the visualizations helped a ton to allow for that dialogue to happen. It was absolutely a marketing vehicle. In all of the data visualizations that I’m doing, I’m advocating for something. My bias is all over it. It’s fine to just say it’s a marketing thing. It’s a communication device. It is also a transparency device. It can build trust. In Ghost Cities, I allowed the Chinese government to explore the data and the model behind my work. There was instant trust — that doesn’t always happen when dealing with government bodies.

Alright, now tell me a bit about the book; let’s give Nightingale readers a preview.

SW: I frame the book with a historical perspective – examples of how we use data for good and bad, so that when we talk about good and bad uses of data, the meanings are clear. I hope that people use the book as a methodology for how they can create change using data.

There are three really important components to that:

1. I advocate for collecting your own data and using data that’s out there creatively, bringing both qualitative and quantitative data together.
2. Sharing and visualizing are critical.
3. I also emphasize that building interdisciplinary teams is the most effective way to create data for policy change.

I end the book with a discussion on the future of data and society, asking some larger questions such as: “Are we data colonialists?” Data access is being consolidated, and not just by the government anymore, making regulation more difficult. Private companies play a large role in decisions that are being made with data. I hope the book challenges people to consider the ways in which they can use data for action in their own communities.

[Author’s note: Data colonialism refers to the process of appropriating data for the purposes of extracting value rather than to, as a government might, establish societal safeguards.]

Data Action: Using Data for Public Good will be available from the MIT Press in December, 2020, and can be purchased from a variety of retailers.

For more information about Sarah Williams’ projects such as Million Dollar Blocks: background on the architecture and justice and the pattern, as well as details about the scenario planning used by the project team. Here is an online visualization of Chicago’s Million Dollar Blocks.

Here is some additional detail about City Digits: Local Lotto.

More about the Ghost Cities project can be found here and here is a video explanation of their amenity model.

Derek Poppert provides a useful primer on public tech here. And, WIRED has a recent take on anticipated industry growth here.

The post Generating Data Action: How an MIT Professor Hopes Data Can Empower Civic Change appeared first on Nightingale.

What differentiates truly amazing visualization is its comprehensibility — that you don’t need a dataviz background to understand its meaning. The Map Room Project has exactly that effect: once you see what the data are telling you, you can’t unsee it.

Launched first in St. Louis, the Map Room was an interactive exhibit that encouraged community members to engage with local maps through the lens of their own lived experiences. I learned about the project nearly two years after it occurred from an article by Shannon Mattern, a professor at The New School. What struck me was when Mattern, who writes about media spaces and infrastructure, reported a theme: that “nearly all participants discovered that historical redlining maps, which deeply carved racialized patterns of development and resource allocation into the city’s fabric, had an enduring legacy, conditioning so many other, lasting spatial patterns.” I was excited not only by the interactivity of the installation, but also by the collectiveness of an experience that mingled institutional, communal, and individual data.

“What we saw in St. Louis was that, when you bring those gates down, it can work for everybody.”

—Jer Thorp, Map Room creator

The idea for the Map Room Project was first conceived by data artist Jer Thorp in 2013, while he was working for the Office for Creative Research (OCR). In 2017, he partnered with Center of Creative Arts (COCA) to bring the St. Louis Map Room to fruition. COCA defined the project as “a community space for exploring and creating original, interpretive maps of the city that reflect[ed] the personal stories and lived experiences of its residents.” The project fused elements of technology, art, activism, and community engagement. It was hosted in a vacant school gymnasium. Accessibility was central to this choice; it needed to be on a transit route, close to walkable neighborhoods, and in a space open and welcoming to the public.

Thorp explained to me that the Map Room was designed to help people read civic data critically and broaden their perspective. “So much civic data is geospatial. People are not good at finding their own routes through data. If you look at a map, you and I are usually going to look at exactly the same point: where each of us are.”

The project encouraged visitors to consider multiple realities of where they lived. “On the maps they can come up with other ways to portray their neighborhoods beyond low-income.” Jer said.

“Every map based on census data shows the poor neighborhoods in bright red. It’s like, ‘Thanks for reminding me.’” One of the guiding considerations came out of a meeting with Detroit artists from Complex Movements. They challenged us to consider how our project was reinforcing the master narrative. These institutional maps remove community from the commentary of their own lives. What other stories do the data tell? What about mapping the churches to illustrate the strength of the community?”

In fact, the resulting maps depicted a range of themes like archiving memories, documenting history, chronicling visitors’ lives, and acknowledging social inequities and injustices. Thorp’s goal was for visitors to leave the exhibit with a new understanding of the stories and the narrative informed by the data.

The St. Louis Map Room ran for a month and was visited by 29 groups who created 100 square feet of maps reflecting aspects of their own local context. Participants included diverse groups of students, activists, community organizations, and city planners and other city employees. “We had a group of planners that were kind of blown away,” Thorp recalled. “It’s hard for them to see what lived experience looks like. The Map Room was like a one-stop-shop to see all different perspectives of lived experience. It’s not that they’re uninterested, it’s just that the way we present the data and the available platforms — there’s a lot of gatekeeping. What we saw in St. Louis was that, when you bring those gates down, it can work for everybody.”

In a sense, the St. Louis Map Room was motivated by disillusionment. As Thorp explained, “The Open Data revolution never really happened. One of the reasons for that is that we expected people to interact with data and use it in the ways we have been trained to. The gulf between the ways that [data practitioners] interact and the way that people want to is too great. For most people the data are impenetrable. They are only for people with rarefied skills. Open Data did more for people who already had data privilege. We’ve expected people to come to our table. Data practitioners should be expected to build community data literacy.”

“For most people, the data are impenetrable. They are only for people with rarefied skills.”

—Thorp

Emmett Catedral was a COCA Program Manager during the St. Louis Map Room exhibit. His background as a teaching artist provided valuable experience as the Map Room facilitator. In his role, he conducted approximately 30 mapping workshops with groups of community activists, church members, students, urban planners, health care workers, educators, and others. When he wasn’t running workshops, he was providing context for visitors with questions about the resulting maps on display. He told me he was repeatedly surprised by visitors’ reactions to the sheer physicality of the maps in scope and scale. “They come in with a sort of availability bias. We see what’s available to us. They’d talk about how well they knew the city, but when we examined the map they generated, there were no dots in North City, a low-income Black community. They were confronted with their own lack of knowledge and the relative smallness of their lives against this 10′ x 10′ map.”

At the same time, people were curious. Certain data layers really struck a chord, like the 1930s redlining map, the income variances, rates of high school graduation rates, insurance rates for adults over 18, and unemployment and crime rates. Examination inspired conversations — sometimes for the first time — about these topics. There were always a few participants that really wanted to further engage with the data layers. “They’d ask, ‘Where are these maps? Where can I see them after? I want to share them.’” The only barrier to further independent engagement was that they didn’t know where to find the data sets or how to make the data layer visualizations.

Removing obstacles like lack of awareness, access, and expertise is central to creating meaningful engagement with the potential to extend impact beyond a single experience. It affords a perspective into the daily lives of others. The St. Louis Map Room provided the attending mapmakers with reciprocity. “People want to engage,” said Catedral, “but you have to hand them the crayon. People will contribute when you give them the opportunity. Even the most disengaged-looking middle school kids got down on their hands and knees and participated. Once they could give of their own stories, they were so open to then learning and understanding what the data sets said.”

Some people came in with a sense of the power of mapping. Emmett shared the story of a group of curriculum planners who sought to use data to contradict the false narrative that St. Louis city schools were “all bad.” The map they produced highlighted the geographic divide between St. Louis City and St. Louis County. In it, they highlighted schools in the city that drew students in from the county. “They had a mission,” Catedral remembers. “They came in to show that it wasn’t just their opinion. They knew data would help them change people’s perspective.”

“People want to engage, but you have to hand them the crayon.”

—Emmett Catedral

The resulting collection of St. Louis maps now lives in the civic archive, fulfilling another of Jer’s goals for the project. They reside in the same place as the Home Owners Loan Corporation (HOLC) redlining maps, whose impact is still evident more than two generations later. “In making maps, communities and individuals can find power. Their maps are as important as the others in the archive, if not more. These community maps have equal standing.”

The St. Louis Map Room success inspired an Atlanta expansion in 2018. It was developed by Professor Yanni Loukissas and his students at Georgia Tech. The author of All Data Are Local, Loukissas specializes in data in context. His team adapted the original technology into a portable system called Map Spot that enables map-making pop-up experiences. With Map Spot, organizers project geographic areas and participants trace them as a foundation to which they can then add their own context. They have the option to apply preloaded data layers from a variety of sources. As Yanni described to me, “It starts with people tracing elements of the projection that are important to them. Then, they begin overlaying their personal experiences: things like, ‘Here’s the route I use to get from home to school.’”

Accessibility and personal narratives are still cornerstones of the experience. As in St. Louis, the goal was to equip people to think critically about data, to prepare them for data encounters on other interfaces. However, maps are limited. They aren’t meant to do the work of a timeline. Yanni said, “One of the reasons I love the Map Room is that it doesn’t require any knowledge to use. Oral histories can work in parallel with events and location data.”

Loukissas considers mapmaking the beginning of a conversation and the Map Room a safe space for data-informed questions. “The Map Room is about building connections and bringing people together. It’s the beginning of the process. How do we get people to think differently? For example, crime and school data. Why are those linked? The Map Room is a place to have those discussions.” Historically, the Map Room has been facilitated in educational contexts, discourse typically associated with schools, libraries, museums, community centers — places that Loukissas says encourage us to think about social and civic good. In fact, Thorp hoped the Map Room might inspire a new type of such civic space. But, if mapmaking is the first step, what comes next?

In this case, the next step was to move outside (literally) to identify gaps and collect and model data. After three years on pause, Jer and Yanni are taking the Map Room to Savannah, Georgia.

Yanni told me about a new series of Map Rooms they are setting up in Savannah. “People brought a variety of different concerns, like air and soil pollution. They’ll come to us, point to the map and say, ‘I smell this in this area.’ Then we can start turning on the data layers that we have. Data can be used as evidence to make a claim about something that you care about. We ask them, ‘What data would you like to have?’ Then we think about where we can get that data and we look online. If it’s not available we collect it, for example in Savannah, we’re installing sensors to collect particulates in the air.”

“The Map Room is about building connections and bringing people together. It’s the beginning of the process.”

—Yanni Loukissas, developer of Atlanta Map Room

Scrolling through the visitor-generated maps from the St. Louis Map Room project expanded my understanding of redlining and the multigenerational reach of systemic racism. It transformed what was for me an abstract concept, thanks to my privilege, into something visceral. Now, I can not unsee the still-firm grasp of 80-year-old policies. Maps illustrate what systemic racism looks like in ways that that phrase alone cannot.

For example, in researching this piece, I came across these racial dot maps that highlight persistent segregation in four cities I have lived or live in. It’s been twenty years since I lived in Brooklyn. In retrospect, gentrification seemed like it was just beginning in my neighborhood then. In Milwaukee and in Chicago, the divide between the East and West and the North and South sides was evident. And, in Detroit, the so-called comeback story — justifiably offensive to many lifelong residents — is heavily intertwined with gentrification. Much of the City’s neighborhoods are vulnerable to potential resident displacement. As we are now witnessing in a new way through the lens of COVID, neighborhoods matter critically to fundamental aspects of people’s lives, like their economic opportunities, their access healthcare, and even the impact on their life expectancy.

Maps are not the only interfaces to expose injustice and inspire change. Interestingly, Jer Thorp considered St. Louis Map Room facilitator Emmett Catedral an interface. “Without Emmett, the thing that happened wouldn’t have. He prevented people from misinterpreting the data and encouraged their examination.” Catedral agreed that the creative and collaborative mapping workshop involved participants uniquely, commanding “rapt attention” in a way that would not have been possible had he conducted a lecture-style tour of a room full of maps instead, for example.

Yanni Loukissas devoted a chapter of his book to evaluating Zillow and its relationship to gentrification. In it, he explores the tension between housing data rooted in a consumer context and individual preference versus its broader civic context. He wonders whether building friction into the interface — in this example, visibility into housing values over time — could change real estate culture.

Loukissas wrote, “Local perspectives on data can awaken new forms of social advocacy. For where data are used, local communities of producers, users, and even nonusers are affected. … We must do more to actively care for our data and any vulnerable subjects that they represent. When such work is degraded or undervalued, it perpetuates a long history of degrading care.”

What happens to the Map Room project during COVID-19? The limitations dictated for safety can compromise accessibility. It is no longer desirable to bring large groups together to huddle closely together to trace and draw on a map. COVID is frequently described as an indoor disease. During pandemic, sharing markers is a challenge. Keeping surfaces clean is difficult. Despite these challenges, how might this mapmaking continue? How might such community building continue? The pandemic itself and people’s experiences are spatial. Loukissas offered a range of ideas, including developing an archive of pictures people submitted, thinking about ways to make maps without a projector, and “evening Map Rooms outside, projected in the street, and traced with chalk would be really cool.”

Opportunity narratives — helping clients identify and frame possible pathways to address complex challenges — are a cornerstone of my work. Techniques that encourage collaborative input and produce tangible byproducts are essential to this framing. The Map Room Project serves as a leading practice in how to activate engagement that prioritizes data accessibility, local context, and diverse perspectives. Jer Thorp and Yanni Loukissas applied their skills to level the playing field. It is incumbent upon us to use ours to continue to broaden understanding (our own and others) and reduce inequity.

Below are a list of resources for more information on the topics covered.

Open source map room information can be found here.

Read Jer Thorp’s account of the project here.

Here is a video from the exhibit.

Here’s another piece about the St. Louis Map Room from Shannon Mattern.

For more detailed information on racial covenants, refer to the University of Minnesota’s Mapping Prejudice site.

For information on data feminism and using data to challenge power, see this.

Here is a report from the University of Minnesota’s Center for Urban and Regional Affairs about gentrification in Minneapolis and St. Paul.

Here is a report about gentrification in Atlanta produced by the Housing Justice League and referenced in Yanni Loukissas’ book.

Here is another perspective on gentrification.

Here is an affordable housing approach from Singapore.

And, finally, more discussion about interface design and racial bias.

The post Indelible Impressions: Why You Won’t Forget the Map Room Project appeared first on Nightingale.

As a data visualization designer, I think about the pieces I’m working on as the visual equivalent of articles or stories. I love reading and writing using words, but I also love reading and writing using shapes and visual alphabets. Keeping in mind the people who will see and read my visualizations is essential, especially because most of my potential readers are not data visualization experts and may need keys and support to read these visual stories.

Over the years, I’ve created pieces for all different types of readers, but they all had a common characteristic: they were adults. A few years ago I was asked to use data visualization to communicate with children. I loved this challenge from the start and I’m going to talk about what I learned and the unique characteristics of this project here (thanks Nightingale for hosting my words!).

But before that, I’d like to quickly explain how I got there. I’ve been designing data visualizations as a freelancer since 2015 and I’m extremely interested in visual experimentation as a way to communicate to readers, and to engage them (when the usage context justifies it). A collaboration that allows me to explore my interest for this kind of experimentations is the one I have with La Lettura, the cultural supplement of Corriere della Sera. I design static data visualization pieces for them, combining informative content with data art: I’m in fact asked to visually experiment while communicating topics and stories.

Designing a Sky Map

Some years ago they asked me to design something different from the projects I usually work on: a “Sky Map” that would combine cartography, data visualization and illustrations to depict our world as seen by the eyes of an airplane pilot, with different boundaries and reference points to navigate the world. The visualization was inspired by Mark Vanhoenacker’s book Skyfaring. A Journey with a Pilot.

I had never mixed data visualization and illustrations before, so that project was a very interesting starting point. I’ve always loved to draw, but I stopped doing it when I started working as a designer and was losing confidence in my illustration skills. (I still don’t consider myself a professional illustrator.) In fact, at the beginning I didn’t think I would have been able to work on the illustrations and I had contacted a very talented friend of mine asking her if she had time to work on it with me (Debora Guidi). But she wasn’t available and I decided to give it a try myself. I’m very happy about that decision now!

Airplane pilots use reference points called waypoints to define their routes. Some waypoints have very nice and evocative names, such as MOON or GNOME or WHALE. I decided to use this aspect as starting point to add an illustrative element to the map and I’ve drawn some of them.

I was particularly focused on finding a style for the illustrations that would work in concert with the data visualizations — I visualized data about airplane passengers by country and airports — and I worked a lot on the palette and the shades to obtain such a result. Sky Map is a project I’m still very fond of. First, it pushed me to use illustrations as communicative and informative layers and now I love mixing drawings and data visualization when I can. Moreover it allowed me to look at the world — and then to illustrate it — from a totally different perspective: I saw it and then depicted it with different eyes, borrowing an airplane pilot’s glance (and — fun fact — I love traveling but I definitely don’t love airplanes, so it was an interesting change of perspective!)

And finally, I’m very fond of it also because it brought me a beautiful, entirely different opportunity.

A few months after the publication of the piece I was contacted by a publisher: they had seen the way I had combined illustrations and data visualization and they asked me to try something similar for a children’s book.

‘Planet Earth’: an infographics children’s book

The aim of the book, which was titled Planet Earth: Infographics for Discovering Our World, was to depict our planet combining infographics and illustrations. I was extremely excited about the idea of working on an infographic children’s book: shifting my focus from adult readers to kids would allowed me to look at things — again — with new glances and from a new perspective (such a refreshing one!) so I accepted the proposal almost immediately.

Even so, I was conscious of the fact that there would be challenges. First of all, I had never designed data visualizations for children before: I mentioned how keeping the audience in mind is essential for my job and in this case I needed support to better understand how to talk to my potential readers. Many of my visualizations — as the ones for La Lettura for instance — explore topics in their complexity layering different levels of information: they are the visual equivalent of a long article and they need time to be read.

I don’t think this is a problem when the usage context allows it: I think there is a wide range of possible approaches to designing data visualizations that depend on context, readers and communicative purposes. But such a “long reading” approach wasn’t the right one this instance. I remember a lot from my childhood, including the things I didn’t understand (I perfectly remember the first time I saw division on a blackboard at elementary school: I immediately thought, “Will I really be able to understand such a thing?”). Similarly, I wanted to entertain the young readers with something interesting, easily understandable and enjoyable.

This is why I decided to work on Planet Earth with Chiara Piroddi, who is the co-author of the book. She is a psychologist, expert in Developmental Neuropsychology and her role was extremely important because she helped me design visualizations that could be understood by our young readers. During the design process I used to send her my ideas and sketches for the potential visual representations and she was able to tell me if she thought they would be understandable for children. I think that without her support I would have oversimplified the project, afraid of designing unreadable pieces. I wanted to work on clear but also evocative and organic shapes and her feedback helped me in finding a balance.

We also worked together on the main structure of the book, which provides information on our planet from different points of view: from the atmosphere to the ocean depths, showing data on animals, plants and the environments.

Then she focused on the research phase: she extracted data from official sources and encyclopedia and we worked together to clean them and select the information to be visualized. In the meantime — while she was looking for the data — I started defining the overall style of the book: the second challenge.

Defining the style of a project is always a challenge, and this time I particularly wanted to work on the connection that a children’s book can create with readers.

I’m constantly interested in such connection with the readers. I strive for an emotional component when designing for adults, but I think that working on a book for children particularly requires giving a lot of space to this aspect. It’s important to create an emotional relationship with young readers in my opinion, trying to turn on the spark of joyful connection that a child can have with a book: I curated shapes, colors and the overall composition to try to turn on such connection.

Remembering

In general, I often find it useful to start from a personal point of view when I begin a new project: I “start from myself” trying to put myself in my potential readers’ shoes. For this reason, in my design process I dedicated a lot of time to remembering. As child I loved to lose myself in the pages of books and I remember that I really loved certain illustrated books because of the colors, the shapes and the details. This is why I spent an afternoon re-looking at my old children’s book — my parents still keep them — flipping through the pages and re-feeling all the positive emotions that they used to bring me (that they still bring me, actually). These positive feelings — and the feelings I get from the visual elements in particular — were the starting point for my own work.

The first aspect I focused my attention on was the illustrative element. I’m not a professional illustrator and I wanted to make sure that my style would have been approved by the publisher.

I already knew that they liked my illustrations for the Sky Map, so I used them as starting point. I hand-drawn the illustrations (with a black pen — I always use the same one) scanned them and then colored them with Photoshop.

I love soft shades and light colors, but this time I “pushed the saturation button” a little bit more than usual, inspired by my old children’s books. I defined a main palette of ~10 colors and I used them to create different shades.

Designing data visualizations for children

I then worked on combining them with the data visualizations. I wanted to design elements that were understandable but also visually evocative at the same time. There are certain shapes I love — I’m often inspired by the shapes of nature such as leaves, flowers, jellyfishes (I’ve been inspired by a cabbage lately) — and I kept such shapes as base also in this case and then I simplified them.

I worked on small compositions of infographics and illustrations. Drawing soft and clean visualizations helped me in creating a dialogue between the hand-drawn illustrations and the vectorial infographics: I didn’t want the two elements to clash, but rather to have a harmonic relationship.

Again, Chiara Piroddi’s role was essential. She helped me understand if my visuals would have been clear enough for a young public. A very useful suggestion that came from her is that — with data visualization being a new language for most children (and not only for them actually) — creating a familiarity connection with the shapes was important: for this reason there are some shapes and visual models that recur often in the chapters, to help children get used to them. I worked on creating a consistent alphabet and then on constantly helping the readers in using it.

This is why I’ve designed both small legends for each chapter, and also — at the same time — a unique legend in the first pages of the book, so that they could have all the tools to visually read the information and slowly learning how to use them.

This was a great opportunity to work on the emotional component of visualizations and visual elements and on how this component can help me — as designer — in creating a connection with the readers. And I had the chance to see some children’s reactions during a few workshops I’ve given. I guided them in designing compositions of infographics and illustrations inspired by the book and their enthusiasm, care and interest were truly heartwarming.

I’ve talked about the importance of keeping our readers in mind: working on this book allowed me to think about that focus during all the design phases. And this constant reminder has been absorbed and then consolidated in my current design process. This book made me also reflect on the importance of starting from a personal point of view to design a project that can create a “connection.” I’ve started from my memories and I used them to design shapes and elements with the purpose of explaining topics, communicating stories and contents but also engaging the readers. The coexistence of these factors is very important for me, also when I design visualization for adults: using the communicative potential of shapes, colors and compositions to create engagement and understanding.

And talking about potentials, I think that data visualization can be a very useful tool to communicate information and contents to children. Giving a shape to numbers is a good way to transform their abstractness into something that young readers can actually count, measure and compare. Numbers can carry with them interesting and meaningful stories and visually translating them can help bring these stories to light. I loved bringing some of our planet’s stories to light and narrating them to children.

P.S. While writing this article I was forgetting to mention two important aspects!

1. Caffeine was a major support for this project: Chiara Piroddi and I only had four months to create the book and we spent a few nights awake working on it. Time was another significant challenge!
2. The publisher asked us to design a mascot who would have guided the children in discovering the different environments, from space to oceans. I’m a longtime fan of tardigrades because they’re simply amazing and they can basically survive everywhere. So I didn’t think too much about who our mascot could have been

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