This was a personal project I made after the “Me Too” deluge in late 2017, when it seemed every day a news hit came out about a person being harassed, assaulted, raped, or worse. Most of this surge came after accusations began piling on Hollywood mogul Harvey Weinstein. I wanted to document the time and see the connections of those involved. Though the list is now extensive and, by most measures, sadly continuing, I focused on the three months after the Weinstein accusal in early October.

As legal accountability might take years, and was complex to parse given the speed of the daily news cycle at the time, I wanted to show a snapshot of the allegations—whether wrongfully or credibly accused—and present one big picture of the storm. The sheer numbers coming in revealed how pervasive sexual assault was. Some of the accused, like Senator Franken, did not get due process at all, while others denied claims and simply went back to working lucrative jobs after laying low for a while. I was thinking of journalistic fairness the whole time: to explore all sides and try not express opinions, and that the viewer should be able to see trends or patterns even though the visualization may be complex.

Structurally the design seemed to want to be a timeline, or maybe it was a tangled net, a curving downward spiral, or a vortex shape? Or was it a range of bars with colored gradients showing the level of abuse?

Brainstorming metaphors like Breaking the Dam, Watershed Moment, or Strength in Numbers in a bad sense seemed to fit; as more stories came to light, more (mostly) women broke their silence and shared their experiences.

So I started to build it out vertically—like one part falling and creating inertia to keep on going. Though I always want my designs to be visually inviting, I didn’t want this one to be too bright; like I was celebrating the accusers. Later, I layered in a few case factoids as more entry points, with bubbles at the bottom to show
punishment, contrition, or resolution, if any.

I settled on the title “Tipping Points” almost in a hopeful way—that showing this issue was not rewarding it, but at the very least acknowledging it. Five years later, it seems that the national conversation has now turned it into a partisan, weaponized gender issue. According to rainn.org, out of every 1,000 rapes, 994 perpetrators
will walk free, so it’s hard to say now if that moment in time was actually was a tipping point, or if it was just business as usual.

Heather’s article appears in Nightingale Magazine, Issue 2. You can still order your own copies of Nightingale Magazine, Issues 1 and 2 here, while supplies last!

The post SPOTLIGHT: Tipping Points appeared first on Nightingale.

But Cox explains that his project, Inside Airbnb, was simply in response to two of his beliefs: first, that housing is a human right that has been commoditized, second, that data might further the conversation. 

He launched Inside Airbnb in 2014, after teaching a youth workshop on gentrification in New York City’s Bedford-Stuyvesant neighborhood using data analysis and visualization. He began scrutinizing Airbnb’s publicly released data. On his website, users can download the most recent year of data for free. The data he collects includes details about hosts, like the host’s self-reported location, the number of listings, as well as the price and room type of each listing. With Inside Airbnb, Cox visualized this data into dashboards for each city, using Mapbox Studio and OpenStreetMap.

Two years after the launch, Cox released the site’s first major report with fellow data activist and independent co-author Tom Slee, who collects data of his own, separate from Inside Airbnb’s. Cox and Slee analyzed data that Airbnb had publicly released about its presence in New York City in December 2015 — and found that the company had removed over 1,000 from November listings before releasing the data. 

All of the removed listings were for entire homes whose hosts were renting out multiple entire homes, as opposed to only one home, presumably their own residence. These listings are the biggest concern to activists like Cox who fear they are being operated by commercial hosts, not residents sharing their own homes. Airbnb then presented the November data as an average day of Airbnb’s operations in New York City, with only a small number of commercial hosts, which Cox and Slee found to be untrue.

Now seven years into the project, Inside Airbnb has expanded to 85 cities and regions in over 25 countries. The website includes an interactive map and summary of listings for each location, along with downloadable data. In a pre-pandemic world, Cox would travel to speak at conferences about his findings. He fields academic and journalistic requests almost daily. He even met with Airbnb in February 2019, where they discussed a proposal to regulate home sharing in New York.

A bill requiring registration for short-term rentals has been discussed in the New York City Council, which held a hearing on it in September. Murray, who has been working on the legislation with the Coalition Against Illegal Hotels, gave testimony at that hearing.

Today, Cox is grappling with the scalability of Inside Airbnb as an open-source data project. He considers his work first and foremost as housing activism and wants the data to be free for activists to address issues in their own cities.

But the project does come with expenses like proxy servers, cloud storage for data and data transfer costs for when people download his data — all of which comes to a few thousand dollars per month, Cox said. He said he generally doesn’t pay himself. To support the project and himself, he works part-time in product development and management, and infrastructure in the art technology space. 

“How do I release free data because that’s going to help activists? But at the same time, I have expenses that I have to pay,” he said.

Besides funding the project personally, he is requesting payment to access archived data that is more than a year old. He recently removed archived data from his site — because he found that some were simply scraping it on their own instead of contacting him to request it. Today, access to one city’s archived data costs $300 for academics or other institutions doing research related to Cox’s mission. Commercial researchers or academics studying a topic unrelated to Airbnb’s mission pay $500 for that data, according to a pricing guide on Inside Airbnb’s website.

Data from the last 12 months is still free for all to use. ​​​​Activists, journalists and residents, as well as governments doing work aligned to Inside Airbnb’s mission can request access to archival data for free. But some cities and regions, like San Francisco, New York City, and Vaud in Switzerland, also pay him a few hundred dollars per month to access the data. Cox has also created an advisory board of activists and researchers, which aids with finding potential collaborators and funding sources for Inside Airbnb.

Given these hurdles, Cox said he would advise data activists to think about how they can garner community and financial support to scale their project if needed. Finding communities of civic technologists, like Beta NYC, is one way to find like-minded people to join a project.

He added that working with traditional advocacy groups who aren’t involved with data is equally crucial, since it brings data activists closer to communities.

Despite the time and cost of maintaining Inside Airbnb, Cox said he feels that the project is most “justified” when he sees cities use his data in the process of instituting housing regulations. He is also hopeful that more people in data fields will recognize that they can use their skills both for financial gain and societal improvement.

The post What Data Visualization and Analysis Taught One Activist about Airbnb’s Impact on Communities appeared first on Nightingale.

While California collects racial and ethnic data on a host of issues, from opioid overdose to COVID prevalence to academic outcomes for students, data for Native Americans is reported less frequently, or unreported due to small sample numbers and policies that hinder collection.

The problems with data collection facing the Yurok Tribe are not unique to California, nor are they specific to Native American populations. What the Yurok Tribe experiences exemplifies a broader issue that data analysts and visualization practitioners should confront. How can we analyze findings and visualize results when data for important communities are simply not reported?

This is the question we, a data storyteller and an epidemiologist, posed to ourselves as we set out last summer to work with the Yurok Tribe Wellness Coalition as part of a technical assistance program sponsored by the California Overdose Prevention Network, a program of the Center for Health Leadership and Practice.

The issues the Yurok Tribe face helped us better appreciate what so many groups contend with and allowed us to puzzle through what can be done to help a community aiming to confront modern challenges by leveraging data. Beyond simply obtaining broad data about Native American status, the Yurok Tribe also needs more specific tribal affiliation identification, which represents a political designation of the tribe’s sovereignty. Alas, this information, which can help the tribe provide necessary services while preserving important traditions, is rarely available.

Although the Yurok Tribe is California’s largest, at about 6,300 enrolled members, it simply can’t access crucial indicators of how members are faring. As Lori Nesbitt, the opioid program manager for the Tribe’s Wellness Coalition, observes, they often don’t get any data until a member dies from an opioid overdose, when it’s obviously too late to provide supportive and life-saving services.

Those of us who work frequently with data understand what’s at issue here: epidemiologists, statisticians, and analysts reporting racial and ethnic information are trained to suppress populations with small numbers, or aggregate several smaller groups together. Although these are accepted as good statistical practices, these approaches often fail to articulate trends at the micro-level, which challenge an array of communities in the U.S., including tribal populations, Native Hawaiians and Other Pacific Islanders, Middle Eastern and North African populations, and other ethnographic groups.

In short, the aggregate means we aren’t looking at the full story. As California Governor Gavin Newsom often observes, “We don’t live in the aggregate.” Disaggregating smaller populations (whether they are racial and ethnic groups, by tribal membership, or some other important feature) is a technique that analysts and data storytellers should include in their toolbox to advance health and equity, even if it bumps up against statistical practices. There are strategies for disaggregating data (combining multiple years of data, oversampling smaller populations) while maintaining statistical rigor.

But if we can’t disaggregate, we’re left with incomplete information, and these blank cells in tables and empty spaces on graphs are often visualized by an asterisk, indicating suppressed data. The National Congress of American Indians’ Policy Research Center says it well:

“American Indians and Alaska Natives may be described as the ‘Asterisk Nation’ because an asterisk, instead of a data point, is often used in data displays when reporting racial and ethnic data due to various data collection and reporting issues, such as small sample size, large margins of errors, or other issues related to the validity and statistical significance of data on American Indians and Alaska Natives.”

However, beyond issues of data analysis, there are important historical and contemporary factors at play — namely the genocide and oppression of Native Americans which pre-dates the founding of the United States of America. During our project, we learned from our Yurok Tribe partners how this history and its legacy plays out today, even through our data systems. The U.S. Census, for example, did not count Native Americans until 70 years after the inaugural census in 1790 (to learn more, check out this timeline from the U.S. Census Bureau and this commentary from the Pew Research Center). And in a more modern example, CNN’s election coverage this past November reported out results from Native Americans as a group they termed, “something else,” which was offensive to people of all racial/ethnic backgrounds, particularly Native Americans and other communities of color.

The end result is a paucity of data, and, put simply, you can’t visualize an asterisk. If the data are not there, how are we to know and visually describe how these populations are faring?

Through our project, the Yurok Tribe Wellness Coalition sought to better understand what data were being collected on Native Americans (and specific tribes) by public agencies across Humboldt and Del Norte counties, where the tribe is located, so that data reporting can be improved to better support the Yurok people and prevent opioid overdoses. We partnered with the Coalition to conduct interviews with public agencies (social services, health, law enforcement, education) to learn more about their data systems and practices.

What did we learn?

1. Tribe-specific data — and data on Native Americans in general — is not regularly collected by the eight public agencies who participated in our assessment.
2. Data sharing policies are in place between non-tribal and tribal entities, but they are underutilized.
3. Despite the challenges, public agencies are interested in partnering with tribes to improve data collection and reporting. All agencies think there would be benefits to the larger community through better data collection and sharing.

So what broader lessons can be drawn from this project? Simply being aware of who’s not measured is an important first step. Next is to talk to the tribes, and other populations, who may be made “invisible” in data about how we can do better. It’s only in partnership that we can start to make data more representative of all groups.

As the census count wraps up in the United States, we’ll soon analyze results and create illuminating visualizations summarizing the findings. As we do, however, it’s important to account for those who are simply not counted, or who are undercounted by federal, state, and local agencies who have no data, or don’t report the data they do have.

In the coming months and years, as census data are compiled, released, analyzed, and visualized, and as we fret over and visualize COVID-19 findings — including now, the need to obtain racial/ethnic breakdowns for vaccination data — let’s keep in mind who we don’t count, or who we undercount. Let’s remember that we’re often not able to visualize information about Native Americans and the hundreds of tribes in the United States, as well as Asian Americans, Native Hawaiians, and Pacific Islanders — such as Hmong, Filipinos, Cambodians, Fujians — and many more groups that we typically combine together into broad racial and ethnic categories. We need to advocate for them and for the release of their data, recognizing that the results from such data activism can catalyze social change and empower these communities to improve issues of dire importance like drug overdose.

The post Asterisk Nation: One Tribe’s Challenge to Find Data About its Population appeared first on Nightingale.

In our current reality, the chaos seems to be getting stronger: The earth is littered with trash, water is polluted, people are neglected, violence is everywhere, and disadvantaged groups of society are collapsing. We say: “Not on our watch.”

Women Weaving Reality

This May, we started a solemn yet uplifting exploration of the fortitude and violent oppression of women in the last decade. As the new decade has been primarily occupied with the COVID-19 pandemic, we had one key question in mind: what is the impact of COVID-19 on female-centered political activity worldwide?

We set a timeframe from February 1, 2020 to May 16, 2020 as the “COVID-19 Pandemic Burst”. Why? On January 30, 2020, the WHO declared the coronavirus a global emergency, while several countries confirmed the rise of COVID-19 cases and began to apply countermeasures and health emergency plans. On May 15, 2020, there were more than 4.4 million confirmed cases worldwide.

Through the medium of data visualization, we hope to shed light on the stories of women fighting for their rights in the midst of the COVID-19 pandemic burst, of women who are seeking to be heard across social distances and outside lockdowns.

106 Days, 1,761 Events, 104 Active Countries

From its inception, 2020 has been plagued by the ongoing COVID-19 pandemic, infecting 76.8 million individuals (and counting) worldwide and disrupting our livelihoods, economies, and political freedoms. Its impacts have been exacerbated for women and girls across every sphere, including health, the economy, security, and social protection. However, despite lockdowns and social distancing measures, women are marching against femicide, protesting government responses to COVID-19, and raising their voices to fight for human rights and equality.

Over 106 days of the COVID-19 pandemic burst, the Armed Conflict Location & Event Data Project (ACLED) collated 1,761 events of female-centered political activity, primarily in Central and South America, South and East Asia, and the Middle East. These included demonstrations featuring women as well as political violence targeted against them.

During that period, 1,101 ‘Peaceful Protest’ events were reported worldwide, making up 60% of total events. In comparison to the same period in 2019, the number of protests almost doubled. Interestingly, many of these protests occurred despite lockdown or curfew measures, demonstrating that political activism is still a priority during the pandemic.

However, not every protest was peaceful. Some involved clashes with police while others resulted in vandalization of property. According to an ACLED report, women experience disproportionately excessive force, more than in similar events that don’t feature women. In addition to demonstrations, there were 474 events of violence against women, a third of which occurred in Mexico. Alondra Torres’ experience was one.

“We don’t need you to praise us, just let us do our job.”

Health workers face violent attacks in Mexico

Alondra Torres, a doctor from Jalisco, Mexico, was walking her dog on the morning of April 15th when a person threw diluted bleach at her face for wearing her uniform. She suffered conjunctivitis and contact dermatitis as a result.

In the midst of the coronavirus pandemic, resistance, aggression, and discrimination against employees in the health and social sector have dramatically increased. Because 7 out of 10 health and social care workers are women, they are disproportionately targeted. Dozens of incidents against them were reported during the COVID-19 Pandemic Burst, including nine attacks, one abduction, and three fatalities.

In Mexico, female nurses have been hit by stones, kicked off public transport, and have had hot coffee and bleach poured on them amidst fears that they might spread coronavirus. One nurse, Melody Rodriguez, was blocked from entering her village on the way home from work because she “came from a source of infection.”

“They symbolically represent the disease itself and the cure,” says María del Carmen Montenegro, from the Faculty of Psychology at the Universidad Nacional Autónoma de México.

While the Mexican government has taken steps to condemn these attacks and protect health care workers, female health workers are simply asking for respect. “We don’t need you to praise us, just let us do our job,” said Rodriguez.

“Why are you beating me? I am trying to survive!”

Police brutality threatens to transform the health crisis into a human rights crisis

On April 8th, street vendor, Alanyo Joyce, was packing up her fried chicken stall just before the 7:00 p.m. curfew imposed as part of Uganda’s lockdown measures. The next thing she knew, she was burning. A law enforcement officer had kicked a pan of boiling oil onto her, causing severe burns on her face, chest, and arms. In Uganda, women who are trying to maintain their livelihoods during the pandemic are being punished. Another woman, after being chased and caned for selling fruits and vegetables, cried out: “Why are you beating me? What crime have I committed? I am trying to survive!”

Similar reports came from other countries in the region, including Kenya, Liberia, Nigeria, and Zimbabwe. In Kenya, three police officers whipped women at the Mitunguu market while enforcing social distancing. In Liberia, a pregnant woman was beaten by drug enforcement agents for violating a 3:00 p.m. stay at home order.

These alarming assaults are part of a larger trend of excessive force and abuses by police enforcing COVID-19 countermeasures. Human Rights Watch has condemned security forces in the region. “It is shocking that people are losing their lives and livelihoods while supposedly being protected from infection,” said Otsieno Namwaya, senior Africa researcher at Human Rights Watch. “Police brutality isn’t just unlawful; it is also counterproductive in fighting the spread of the virus.”

While the enforcement of countermeasures is important in helping stem the spread of coronavirus, the use of violence threatens to transform this health crisis into a human rights crisis.

“Now, it’s society’s turn to change.”

Japan’s Flower Demo Movement blooms for the last time on International Women’s Day 2020

Sunday, March 8, 2020, marked International Women’s Day, a day of celebrating women’s achievements and a gender-equal world. This year’s theme was “I am Generation Equality: Realizing Women’s Rights”, and despite the pandemic, it was the most active yet, with 393 events spanning 56 countries. From marches in Pakistan and Mexico to demonstrations in Kyrgyzstan and Turkey, thousands of women took the streets demanding greater rights and denouncing violence against women. Japan was the third most active country with 42 ‘Peaceful Protests’, all of which were part of the Flower Demo Movement.

The movement began in March 2019, when a series of acquittals in four sexual assault cases sparked outrage over the legal standard for sexual assault and rape in Japan. In one case, despite the court recognizing that a father physically and sexually abused his daughter, he was acquitted because there was doubt as to whether she was incapable of resisting.

Since then, on the 11th of every month, women gather holding flowers, a symbol of empathy, to speak about their own experiences of sexual violence and urge reforms to Japan’s criminal code. The purpose of the movement can be summarized in the words of Akiko Matsuo, one of its core organizers, “Talking about our unchangeable past will surely change the future.”

The Flower Demo Movement has spread to all 47 prefectures and regions in Japan, with around 1,500 people coming together monthly on average, and has already begun to galvanize reform. For example, the Ministry of Justice announced that they will establish an investigative commission to deliberate penal code revisions pertaining to sexual crimes.

Moved to coincide with International Women’s Day, flower demos occurred in 42 prefectures and cities in Japan on March 8, 2020. It also marked the first anniversary and final gathering of the official Flower Demo. “Today marked an end of a chapter of the (movement), but it is not the end,” said Minori Kitahara, an author and one of the organizers of the demonstration. “Now, it’s society’s turn to change.”

“Who knows what women can be when they are finally free to become themselves?”

When the first reports of COVID-19 cases reached us, we didn’t expect it to spiral into a global pandemic that would profoundly alter our everyday lives. While some of us are struggling with the isolation, household concerns, or the mere discomfort of wearing masks everywhere we go, others, particularly women in countries engaged in sociopolitical crises, are facing severe gender-based discrimination and violence during this time.

With lockdowns and quarantines, we thought there would be less political activity in the COVID-19 Pandemic Burst. We thought wrong. Women were strikingly more active during this challenging period than in the similar period last year. From a two million strong march on International Women’s Day in Chile to protests against femicide in Turkey, women continued to fight for gender equality.

On the flip side, we thought our world would come together in the interest of protecting fundamental human rights, security, health, and economic development. But again, we thought wrong. The world kept turning and violence did not cease despite the pandemic. Violent attacks by gangs in Central and South America, sectarian violence in India, armed conflict in Africa and the Middle East, and other isolated incidents resulted in 360 fatalities in just 106 days.

While the data do demonstrate both uplifting and alarming trends in political protests and violence, respectively, it should be noted that certain events featuring women are not reflected. First, the ACLED data capture political events featuring women or women’s issues and political violence targeting women, but not all the events involving women, nor all political violence against women. The data exclude domestic violence or other forms of non-political violence against women, which intensified. Second, the data do not include all countries, most notably the United States and other Western countries, meaning there was likely more activity than is represented. Third, the fatality numbers are not definitive (and may be disposed to media and political manipulation), nor were all fatalities necessarily women.

In this journey, we have strived to add our voices to the continued fight for the safety, health, education, and empowerment of women and girls globally. Beyond the insightful data, we were inspired by the heroic and shocking stories as a tool for awareness, active engagement, and even self empowerment.

As the pandemic continues to plague the world past our predefined “Pandemic Burst”, we believe that it is possible to keep women and girls worldwide safe from it while promoting and protecting their fundamental rights. What the last few months have shown us is that women should not have to sacrifice themselves and their rights in this pandemic.

Women should be free to protest against gender-based inequality and violence; to work on the frontlines of the pandemic without fear of discrimination or retaliation; to be leaders at all levels of government; and to be themselves. But as the days of the pandemic go by and women continue to be oppressed, harassed, and killed, we should all decide: “Not on our watch.”

We would like to dedicate this project to Justice Ruth Bader Ginsburg, an unyielding advocate for Women’s Rights and a hero to both of us.

The post “Not on our watch.” The Spirit of Women Activists and the Political Violence against Them during the COVID-19 Pandemic Burst 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.

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