Mapping youth well-being worldwide with open data

Ryan Swanstrom is a blogger at Data Science 101. This post originally appeared on DataKind’s blog.

How does mapping child poverty in Washington DC help inform efforts to support child and young adult well being in the UK and Kentucky?

Back in March 2012, a team of DataKind volunteers in Washington DC worked furiously to finish their final presentation at a weekend DataDive. Little did they know, the impact of their work would extend far beyond DC and far beyond the weekend. Their prototyped visualization ultimately became a polished tool that would impact communities worldwide.

DC Action for Children’s Data Tools 2.0 is an interactive visualization tool to explore the effects of income, healthcare, neighborhoods, and population on child well-being in the Washington DC area. The source code for Data Tools 2.0 and open data sources have since been used by DataKind UK and Code for America volunteers to benefit their local partners. There is now potential for it to reach even more communities through DataLook’s #openimpact Marathon.

See how far a solution can spread when you bring together open data, open code and open hearted volunteers around the world.

What a difference a DataDive makes

DC Action for Children, a Washington DC nonprofit focusing on child well-being, needed help understanding how Washington DC could be one of the most affluent and wealthy cities in the United States, yet have one of the highest child poverty rates. Could mapping child poverty help uncover patterns and insights to drive action to address it?

A team of DataDive volunteers, led by Data Ambassador Sisi Wei, took on the challenge and, in less than 24 hours, created a prototype that wrangled data in a multitude of forms from government agencies, Census and DC Action for Children’s own databases.  The 24-hours then evolved into a multi-month DataCorps project involving many DataKind volunteers. The team unveiled a more polished version to a large and influential audience in Washington DC, including the Mayor of DC himself! They then completed the final enhancements to create Data Tools 2.0, which is now live on DC Action for Children’s website.

The project has since released the source code on Github, and the team has continued to collaborate and advance the project to where it is today. In fact, if you’re local, check out the August 5th DataKind DC Meetup to join in and continue improving the tool.

This story alone is incredible and speaks to the incredible commitment of these volunteers and the importance of having a strong partner like DC Action for Children to implement and utilize the work as an integrated part of its mission.

And that’s usually where the story ends. Thanks to DataKind’s global network though, the impact of this work was just starting to spread.

A Visualization Goes Viral

Because the visualization used open data (freely available data for public use) and open source software or code (freely available code that can be viewed, modified, and reused), other volunteers could quickly repurpose the work and apply it to their local community.

DataKind UK London DataDive

The first time the visualization was replicated was in October 2014 for The North East Child Poverty Commission. The Commission had a similar challenge of wanting to better understand child poverty in the North East of England. A team at the London DataDive reused the code from DataTools 2.0 and created a similar visualization for the North East of England. This enabled the team to quickly produce valuable results that “thrilled” NECPC. One of the team’s Data Ambassadors continued to work with the organization and has since migrated the visualization to a different platform in Tableau.

DataKind UK Leeds DataDive

In April 2015, DataKind UK hosted another DataDive in Leeds with three charity partners, Volition, Voluntary Action Leeds and the Young Foundation, to tackle the structural causes of inequality in the city. All three charity teams came together to create a visualization tool that allows people to explore features of financial, young NEETs (Not in Education, Employment, or Training) and mental health inequality. But they did not recreate the wheel—they leveraged past work and repurposed code from DC Action for Children. Read more about the event in this recap from DataDive attendee, Andy Dickinson.

Beyond the DataKind Network

Now, it’s great to see a solution scale within an organization’s network, but it’s even more impressive to see it scale beyond, in this case, into Kentucky and maybe one day India or Finland.

#HackForChange with Code For America

In June 2015, the city of Louisville, Kentucky teamed with Civic Data Alliance to host a hackathon in honor of the National Day of Civic Hacking. Kentucky Youth Advocates, a nonprofit organization focused on “making Kentucky the best place in America to be a kid,” wanted to visually explore the factors affecting successful children outcomes across Council Districts. There is a large variance in child resources throughout the city, which is having an effect on child well-being. The volunteers repurposed the original code and used local publicly available data to create the Kentucky Youth Advocates Data Visualization, which is now helping the city of Louisville better distribute resources for children.

#openimpact Marathon

DC Action for Children is also one of the projects selected for the #openimpact Marathon hosted by DataLook. The goal of the marathon is to get people and groups to replicate existing data-driven projects for social good. So far, there is interest in replicating the Data Tools 2.0 visualization for child crimes in India and another potential replication for senior citizens in Finland. There is no telling where this visualization will end up helping next. Get involved!

Ok ok, but what is the impact of all this really?

Aren’t these just visualizations? Yes, as any good data scientist knows, data visualizations are not an end in and of themselves. In fact, it’s typically just part of the overall process of gaining insight into data for some larger end goal. Similarly, open data in and of itself does not automatically mean impact. The data has to be easy to access, in the right formats, and people have to apply it to real-world challenges. Just because you build it (or open it), does not necessarily mean impact will come.

Yet visualizations and open data sources are often a critical first step to bigger outcomes. So what makes the difference between a flashy marketing tool and something that will help improve real people’s lives? The strength of the partner organization that will ultimately use it to create change in the world.

Data visualizations, open data and open source code alone are not going to end child poverty. People are going to end child poverty. The strength of the tool itself is less important than the strength of an organization’s strategy of how to use it to inform decision-making and conversation around a given issue.

Thankfully, DC Action for Children has been a tremendous partner and is using Data Tools 2.0 as a key part of its efforts to improve the lives of children in DC. It’s exciting to see the tool now spreading to equally impressive partners around the world.

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Visualization: The future of the World Bank

This visualization of the World Bank Borrowers today and in 2019 isn’t the most technologically sophisticated visualization we’ve ever posted but it is a stark illustration of what the future of the World Bank looks like.

As Tom Murphy writes over on Humanosphere:

The World Bank’s influence is waning. Some point to the emerging Asian Infrastructure Investment Bank as evidence of the body’s declining power, but it is the World Bank’s own projections that illustrate the change. Thirty-six countries will graduate from World Bank loans over the next four years (see the above gif).

The images in Murphy’s gif come from a policy paper titled “The World Bank at 75” by Scott Morris and Madeleine Gleave at the Center for Global Development. The paper provides a thorough data-driven analysis of current World Bank lending models and systematic trends that will shape its future. From the paper:

The World Bank continues to operate according to the core model some 71 years after the founding of IBRD and 55 years after the founding of IDA: loans to sovereign governments with terms differentiated largely according to one particular measure (GNI per capita) of a country’s ability to pay. Together, concessional and non-concessional loans to countries still account for 67 percent of the institution’s portfolio.

So when the World Bank looks at the world today, it sees a large number of countries organized by IDA and IBRD status.

And what will the World Bank see in 2019, on the occasion of its 75th anniversary? On its current course and with rote application of existing rules, the picture could look very different, with far fewer of those so-called “IDA” and “IBRD” countries.

But does this picture accurately reflect the development needs that will be pressing in the years ahead? Or instead, does it simply reflect an institutional model that is declining in relevance?

It is remarkable how enduring the World Bank’s basic model has been. The two core features (lender to sovereign governments; terms differentiated by countries’ income category) have tremendous power within the institution, which has grown up around them. The differentiation in terms has generated two of the core silos within the institution: the IBRD and IDA. And lending to national governments (what we will call the “loans to countries” model) is so dominant that it has crowded out other types of engagement, even when there has been political will to do other things (notably, climate-related financing).

So while the model has been laudably durable in some respects, it is also increasingly seems to be stuck at a time when external dynamics call for change.

This paper examines ways in which seeming immoveable forces underlying the World Bank’s work might finally be ripe for change in the face of shifting development needs. Specifically, we offer examples of 1) how country eligibility standards might evolve; and 2) how the bank might move further away from the “loans to countries” model that has long defined it.

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Data-driven policy visualizations from Central and Eastern Europe

Last year the Open Society Foundations’ Think Tank Fund published an online portfolio of a set of projects they supported from 2010 to 2013. The projects are all applications of data-driven policy in Central and Eastern Europe. The portfolio includes:

View the accompanying report here.

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Visualizing Online Takedown Requests: Challenge Winners!

Alexandra Papas is Community and Events Coordinator at

In our latest challenge, designers and creative coders visualized Google’s Transparency Report with the aim of adding context or insight to our understanding of the openness of the internet. In the report, Google discloses the number of requests received from copyright owners and governments to remove information from their services. Of the fantastic projects that were submitted—check them all out in our gallery—judges selected projects that best made sense of the complexity of the data, offered innovation in approach and design, and compelled us to explore more.

Congratulations to Frontwise with their winning project Google Online Takedown Requests Browser. Judges appreciated its beautiful design and the ample functionality to discover patterns and trends, including filters by dataset, time period, copyright owner, and target domains. Additionally, the organization by time and volume and distribution between an outer ring and inner ring of the monthly overview of requests and targeted domains or products presented the data neatly and effectively.

Simon Schulz is awarded second place for Country Based Google Transparency Report. As the only project to offer a detailed breakdown of the data by country rather than a more summary approach, judges felt the project provided an important point of view, one that could be a nice complement to the Transparency Report itself.

Prism by Felix Gonda takes third place for its focus—breaking down the volume of the data by country of origin, reason of request, and Google’s products—and fluid interactivity that allowed easy exploration and comparison. Judges also noted its polish and creative solution.

Frontwise, Simon, and Felix will receive $3250, $1250, and $500 respectively for their great work. Thank you to Google, our jurors, and all participants!

Want to try your hand at another project? Take a look at our Visualizing Hospital Price Data challenge, offering $30,000 in prizes. We look forward to seeing your work!

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Visualization: A Week’s Worth of Twitter Employee Tweets

Via The Verge:

There’s a huge amount of public data available on Twitter, and a new data-visualization tool really hammers that home — developer Santiago Ortiz has mapped out the relationships between every Twitter employee based on their tweets to each other. Ortiz used Twitter’s API to pull all the tweets authored by Twitter employees for a one-week period, and then filtered those tweets by only those made between employees. The visualization Ortiz created is almost overwhelming in its depth of detail: hovering over a user’s avatar shows all the tweet-connections made by that person during the week, and clicking the avatar zooms in on that person and his or her contacts. Even more dramatically, you can click a “play” button to see a fast-forwarded view of every connection as it happened throughout the entire week — you can see small one-on-one coversations quickly branch to include more and more people. You can even click one user and drag to another to see a stream of any conversations the two individuals had.

All of the information the developer used is publicly available, showing the potential for mapping networks and public conversations by using Twitter’s API. Say goodbye to at least 10 minutes of your day and click the image below to play with the visualization.

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