We are psyched to present to y’all a guest blog post from the inimitable Brian Dalessandro. For those of you that may not have been at our NYC Parks DataDive this past fall or at our last NYC meetup, Brian worked with the NYC Parks department as a DataKind Data Ambassador to figure out how their block pruning programs were working.  Lucky for us he wrote about his experience throughout this project, and we’re happy to share this great data-for-good journey with you all. Enjoy!

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When my former boss was retiring, he gave me some simple career advice. He said, “be sure to stop and smell the roses.” For some reason, I was expecting something more profound — after all, here was a man who had led such a successful career. It wasn’t until recently that I truly grasped the depth of his message.

I recently started volunteering as a Data Ambassador for an incredible organization called DataKind. Their mission is to match talented data scientists with non-profit and government organizations that have huge troves of data but lack the resources to analyze it. As a Data Ambassador, I was matched up with NYC Parks. Not only are they the ones to thank for the fabulous upkeep of Central Park and all the other glorious city parks, but they’re also responsible for each and every tree that brings shade, color and oxygen to our concrete-heavy metropolis.

Years ago, NYC Parks created a program for taking better preventive care of the city’s trees. This program involves a regular schedule of pruning and grooming large trees in an effort to reduce the risk of damage from storms and high winds. For years, the department kept a record of which blocks were pruned, as well as how many times they had to dispatch a crew to remove fallen branches and upended trees. Armed with all of this data, they approached DataKind with the following question: “Does pruning trees in one year reduce the number of hazardous tree conditions in the following year?”

If you are a regular reader of the m6d blog (admit it, you are), and/or a savvy advertiser, you might recognize that NYC Parks is asking a fundamentally causal question: “Does pruning cause a reduction in hazardous tree problems?” As a data scientist for a digital advertising company, I’m accustomed to fielding this type of question. A couple of years ago, we blogged about how we were able to estimate the causal impact of ads by analyzing our impression logs. When I signed up with DataKind, I naturally gravitated to this project, given both my desire to help the city I love and my experience analyzing these type of problems.

The project started with a few hours devoted to downloading, cleaning, merging and analyzing data. With the blessing of m6d, I was able to use our high-powered server infrastructure to run some intensive modeling, which produced some very interesting results. I found that pruning the trees at risk for certain types of hazards caused a 22% reduction in the number of times the department had to send a crew for emergency cleanups.

So not only did NYC Parks’ program have a positive impact, now they were armed with a tangible result to provide justification for past and future investments in their data infrastructure and data collection efforts.

m6d is a company that is fueled by data. I spend every day pumping this fuel through our system and I forget that it is kind of a luxury to be able to do so. But there are countless non-profit organizations that simply don’t have the resources that come standard here. Thanks to a facilitator like DataKind, the gap between the two can now be bridged. Although corporations often donate money for good causes, it’s often more rewarding to be able to donate human resources to an organization that can truly benefit from it.

I analyze data all day, every day. But this project was special. It reminded me how important it is to stop and smell the roses. After all, NYC Parks practically demands it.

by Brian Dalessandro

Data nerds and data-curious socialites rejoice! DataKind NYC is opening its doors every other Thursday night to invite the data community to come hang out, work on projects, socialize, and otherwise talk about data for the greater good. Our NexLeaf DataCorps team meets from 7-9 so you can come chat with them about their work keeping vaccines and medical transplants safe around the world or come talk to anyone from the DataKind team. Heck, just come have a beer!

If you’re curious about what we do or just want to know learn more about data and its use for the greater good, come by:

DataKind (in the Blue Ridge Foundation)
150 Court St. 2nd Floor
Brooklyn, NY 11205

Google Map

We hold office hours from 5-9PM on Thursdays every other Thursday. Upcoming office hour days are:

• May 2nd, 2013
• May 16th, 2013
• May 30th, 2013
• June 13th, 2013
• June 27th, 2013

You can always write us at contact@datakind.org with questions or check this blog for any changes to dates or other upcoming excitement. Hope to see you all Thursday!

We are thrilled to announce that today, during Big Data Week, we are excitedly launching our first official chapter, DataKind UK!

We were so inspired and amazed by all of you who wrote to us from around the globe wanting to use data in the service of humanity that we knew we had to find a way to empower more people far and wide.   DataKind UK is our answer to your calls and our next big step in enabling a truly global data-driven sector.  DataKind UK will be spearheading our operations overseas, connecting data scientists with mission-driven organizations to tackle the world’s biggest problems with data, driving the conversation around the responsible use of data, and acting as a thought leader in data policy and data culture.  Headed up by a simply unbeatable set of Directors - Duncan Ross (Teradata), Fran Bennett (Mastodon C), Stewart Townsend (Big Data Week), and Kaitlin Thaney (Digital Science, Strata London) – DataKind UK is poised to transform the third sector in the UK and we can’t wait to do great things together.

// Why the UK?

// How do you guys work together?

// When will DataKind be in my city?

We hope you’ll join us in celebrating this wonderful event by heading over to DataKind UK to learn more or by following their efforts on Twitter at @DataKindUK.  Or heck, if you’re not in the UK, just hack on some data in our honor.  Either way, we welcome our DataKind family across the pond and hope you’ll join us there!

“Me with two screens.  Don’t mess” – Max Richman

We’re continuing our Data Heroes series this month with someone who exemplifies the idea of using data for the greater good.  Max Richman started out in mapping for international development, where he provided geospatial services to the Office of Foreign Disaster Assistance, worked with USAID to transform their program, finance, and project into cartographic visualizations, and helped UNICEF prepare over 200 indicators for educational assessment that he then went on to analyze for them.  You’d think that would be enough to fill multiple day jobs, but Max has still found the time to come bring his data science skills (which he humbly rebuffs, calling himself “an international development kid who taught himself some stats”) to DataKind in no small ways.  We met Max at our first DC DataDive, where he worked with the DC Action for Children team and utlimately went on to finish a six-month project with them building an interactive visualization of child wellbeing.  Almost a year later, Max returned to the frontlines as one of our Data Ambassadors at our recent World Bank DataDive, tirelessly working for months before the event to understand the World Bank’s needs around Poverty and Anti-corruption through leading a team of 15 to build scrapers of food prices across the world.  Max is one of the most enthusiastic, sharp, and down-to-earth dudes we’ve ever met, and we’re glad to have you guys meet him too.

Name:

Max Richman

@richmanmax

What’s your day job?

Research Analyst at InterMedia and freelance international development researcher and technologist.

Tell us about your work with DataKind.

Where to start….  With a confession: When I first heard about the DC datadive in early 2012, I was skeptical.  I’d participated in a few hackathons, even “social action” focused ones and the end results were always nice but rarely impactful.  Flash-forward one year.  Working with fellow DataKind volunteers (shout-out to the whole Team Awesome!), we built a map prototype that weekend and then over the coming months iteratively developed a fully-fledged interactive childhood well-being indicator platform for (the wonderful and amazing!) DC Action for Children.  The project was formally launched in October with DC mayor Vincent Gray in attendance.

I was also extremely honored to represent DataKind during a simulation of the Digital Humanitarian Network at the 2012 International Crisis Mappers Conference, blending my volunteer work with my professional expertise.

What inspires you to use your data skills for good in your spare time?

Suppose I’m one of those crazies trying to both acquire and apply data skills for “good” full time.  Although certainly not as well developed data-wise as the commercial and media sectors, social sector data work is quickly picking-up steam.

Among others, two main inspirations:

1) Altruism: I try to give back after growing-up comfortably in a world that affords such comforts to very few.

2) Self-interest: I love meeting and learning from amazing people.

What is one of the most surprising things you’ve learned or seen in working with data?

How mapping, research, and data are really all about the process.  You definitely want solid visuals, insights, and outputs, but the real value is unlocked as you gain a greater understanding of the domain in which you are applying your skills and your partners/clients/audience see new value in data.

What’s the most interesting or visually striking data project you’ve seen recently?

The Census Dotmap app is pretty nifty – http://bmander.com/dotmap/index.html

rMarkdown and rPubs seem like great new ways to disseminate research and findings using R.

Love what Kiva does with their micro-lending platform and API – http://build.kiva.org/

I’m a huge fan of what Data Community DC is building.  Lots of great meet-ups and events all around the district – http://datacommunitydc.org/blog/

What does someone getting started with data science need to learn?

My message to those who want do data work:

1) Chat with someone about how to get started.

2) Learn how you learn so you can best self-teach.

3) Do it for work or as a hobby.

4) With repetition one gets better at estimating how long tasks take, and

5) Then pad that time to further unpack concepts and streamline what you are doing.

For instance, I started with major commercial software like Excel (data processing), ArcGIS (mapping) and Stata/SPSS (statistics).  As time permitted, I experimented with more code-based as well as free and open-source ways of accomplishing these tasks, using Python, QGIS, and R.  I still have tons to learn, but I find this stack fits a lot of needs.

What blogs do you read?

More aggregators than specific blogs.  I serendipitously sip from the river of tweets by the data, design, and international development geeks I follow.   Hacker News from time to time.  I also just started reading US-edition Google News in Spanish to brush-up on my vocab.

What is your favorite vacation destination?

Grew up in Los Angeles and grad school in London, so those are two of my favorites.  Unawatuna beach in Sri Lanka isn’t bad either.

The 2013 Civic Data Challenge launches today at the Data Visualization Summit in San Francisco. The Challenge invites participants to turn raw data about civic health into useful applications and visualizations that have direct impact on public decision-making.

Expanded version of last year’s challenge

Last year, the National Conference on Citizenship (NCoC) and Knight Foundation launched the first-ever national Civic Data Challenge. Winning teams spanned the country and included undergraduate students and nonprofit leaders, financial analysts and graphic designers, developers and coders. They brought new eyes, new minds, and new skill sets to the field of civic health to help make this trove of community insight more valuable and accessible to decision makers and the public. For a great recap of last year’s Challenge, read Fast Company’s Visualizing Civic Data to Make the Case for Civic Health.

This year, NCoC and Knight Foundation are teaming up again to launch an expanded version of the Challenge. Exciting additions to this year’s Challenge include:

• Three Challenge phases–ideation, creation, and implementation– to help teams come together to build entries that are responsive to community needs.
• Grand prizes to teams that create exceptionally useful products AND work with community partners to successfully implement those tools.
• The opportunity for participants to improve entries along the way with the support of a team of expert advisors.
  

Submit an idea now

The Civic Data Challenge is asking community leaders, government officials, developers, coders and all interested citizens to get involved. The first step is to submit an idea through the Challenge website, from April 11 – May 19. This ideation phase is an opportunity to creative a collective brainstorm about what tools (apps, websites, videos, and infographics) could be built using civic data. These ideas will inform the parameters of the Challenge and teams will begin building entries to respond May 24 – July 28.  Join us at www.CivicDataChallenge.org.

The Civic Data Challenge is supported by our launch partners at Innovation Enterprise who are organizing the Data Visualization Summit. DVSF is the world’s largest executive led data visualization summit and will be attended by Fortune 500 executives. The challenge is also supported by promotional partners at CEOs for Cities, DataKind, Data Visualization Summit and sponsors at Iron.io.

QCRI Hiring Data Scientists, Software Engineers & Interns for Humanitarian and Development Projects

Mia Newman, Humanity United

The tech field is growing rapidly around the world, and new gadgets, new apps, and innovative uses of old technologies are invented every day. But these advances in technology are not evenly spread. Some communities still live in infrastructure-starved regions of the world, while others live under governments hostile to their free speech. Elsewhere, human rights activists simply may not be aware of how best to leverage the emerging tools around them.

These difficulties become even more pressing in the context of some of the worst violations of human security and dignity around the world. For this reason, USAID and Humanity United have come together seeking to answer a core question: Can we channel the many innovations in technology around us toward helping to prevent mass atrocities? Part of President Obama’s comprehensive strategy to respond to mass atrocities and genocide, the Tech Challenge for Atrocity Prevention is a prize-based challenge to encourage technologists, developers and others to engage and collaborate with the human rights space on five key problems.

The first stage of the competition opened in the fall of 2012, and the final round of the competition launched last week. This round of the Tech Challenge will offer prizes for excellent proposals submitted to three distinct challenges:

1. The Model Challenge: how can we better model and forecast sub-national violence? (TopCoder)
2. The Communicate Challenge: what technological innovations could facilitate better (and more secure) communication with and among conflict-affected communities? (Innocentive)
3. The Alert Challenge: how can we better gather and verify information from hard-to-access areas? (OpenIDEO)

The Model Challenge, run through the TopCoder platform, is especially relevant to readers of DataKind. How can we apply data-driven analysis to the fog of war? What tools can we offer policymakers and activists to help predict which community is vulnerable to attack during a wider conflict? What unlikely places might data already exist that might help forecast this violence?

The Model Challenge builds on a series of stages. In the first stage, participants competed
to find applicable, public datasets that compile potential predictors of atrocities at a sub-
national level. Currently, core teams are competing to develop potential frameworks for
predictive modeling using the best datasets collected from participants and experts in the
first stage. Finally, we’ll use the winning challenge statement from stage two as the basis
for the final Atrocity Prevention Marathon Challenge, in which participants will compete
to construct the best, workable algorithm to predict community-level violence against
civilians.

DataKind readers will be ideal participants in The Tech Challenge, and we strongly
encourage you to apply. You are engaged, collaborative, data-oriented, and as interested as
we are in constructively challenging our conception of what technology and data can offer
to communities in the developing world. We look forward to hearing from you!

DataKind is nothing without a team of awesomely smart, creative, and talented data wizards constantly tackling big thorny data problems.  You can imagine our excitement, then, when Peter Darche, a graduate student at NYU’s Interactive Telecommunications Program, asked if there were any opportunities to intern with us.  Peter had been a rockstar student of Jake’s at ITP who was committed to using data for social change, so it took about 30 seconds to answer “yes” and invite him onto the team as our spring intern.  Pete’s a brilliant addition to the DataKind family and he’s working on a really great project related to corporate influence on politics that you can read about below.  We thought it would be better for you all to hear about Peter in his own words though so, without further ado, welcome Peter Darche!

Yesterday, Jake asked us to write up a quick statement introducing ourselves to the DataKind community.  “I know it will be awkward,” he said, “writing in the third person, but… that’d be great.”  Well, we do find it awkward, Jake.  Regardless, we’re DataKinders now, so awkwardness must be pushed through.  Excelsior!

In all seriousness, I am unbelievably excited  about interning at DataKind.  I came to the organization via ITP, an art and technology graduate program at NYU, where I’m currently a student and where I took Jake’s course Data Without Borders.  At ITP I spend most of my time thinking of ways of using self-tracking data to help improve personal social and environmental impact.  Prior to ITP I taught elementary school in the South Bronx and Bed Stuy, and am generally interested in all forms of innovative do-goodery.

During the internship I’ll be working on a project with the Sunlight Foundation examining the influence of money and access on legislative behavior.  The project is being headed up by Data Ambassador Cathy O’Neil, with support from Dr. Lee Drutman of Sunlight.  Our goal is to connect hackers/activists with transparency data from organizations like Sunlight and the Center for Responsive Politics to create a range deliverables, from visualizations to analyses.  Currently, collaborator Shauna Gordon-McKeon and I are working on a creating a timeline for legislative behavior and more projects are in the pipeline!

I’ve already been blown away by the breadth and depth of the DataKind community’s skill-set and experience and am eager contribute to the important work that’s being done.  If you’re interested in the Sunlight project, documentation can be found at sunlightbff.tumblr.com and project-related code can be found at https://github.com/pdarche/sunlight-bff.

In our next installment of our Data Heroes, we’re heading across the pond to talk to Aaron Beck. Aaron is a data analyst at Aimia in London and was one of our rockstar data ambassadors at our DataDive in London. Aaron’s one of those rare people that’s able to jump into an unknown situation and not just adapt to it, but also lead others through it. Thrown in head-first to a problem with Keyfund, Aaron worked tirelessly throughout the weekend with volunteers to visualize deprivation across the UK and help build advanced models for improving Keyfund’s program offerings to high school youths. Yup. Not too shabby for 48 hours work. Without further ado we welcome our latest Data Hero, Aaron Beck!

What’s your day job?

Using data to make people’s lives a little more rewarding (specifically through the Nectar loyalty card scheme).

Tell us about your work with DataKind.

I was the data ambassador for an amazing charity called KeyFund. They help young disadvantaged people build their confidence in 12 key skills by funding their projects.

I worked with a very gifted colleague in Aimia to help prepare KeyFund’s huge database for analysis by all the data scientists during the DataDive.  Over the weekend we were able to quantify the impact of KeyFund for various vulnerable groups on their skills and make recommendations for improving future data collection and the effectiveness of the programme.

What inspires you to use your data skills for good in your spare time?

Mostly the moral compulsion that comes when you understand that with great data skills comes great responsibility. But other than that my top three (in no particular order) are:

1. The people you work with.  Working together with a group of like-minded people to achieve a common goal, in a reasonably tight deadline builds a real esprit de corp and sense of achievement.
2. It’s fun. Most of us enjoy delving into data and finding something no one knew before.
3. Learning opportunities. So many talented people are attracted to DataKind with a diverse range of skills.  It’s almost impossible not to learn something about a statistical technique, computer package, charity, people, working together …

What is one of the most surprising things you’ve learned or seen in working with data?

I love it when data contradicts something you thought you knew.  I think it’s difficult for women (especially my mum) to complain that men are pathetic when they’re sick given sick absence rates for women are higher than for men.  Or for men (mostly British Men) to insist that Muhammed Ali and Angelo Dundee “cheated” Henry Cooper out of victory in a fight in 1963. The belief is that Angelo Dundee cut Ali’s gloves after being knocked down by ‘Enry at the end of the fourth round, giving Ali two minutes recovery time as they were being stitched up.  It’s a strongly and widely believed “fact” – but it just isn’t true.

What’s the most interesting or visually striking data project you’ve seen recently?

I used to work in Defence and I still love the polar area pie chart Florence Nightingale used in the Crimean War (http://en.wikipedia.org/wiki/Pie_chart).  Developments made in mapping and multi-dimension \ dynamic diagrams like Google motion charts are ace – but Florence’s work demonstrates you don’t always need cutting edge software to develop visually striking information.

What does someone getting started with data science need to learn?

I guess the tools of trade. The fun comes from manipulating data and bending it to your will and lots of the software you need to that is now free.  Some maths and statistics would be nice – but not essential I don’t think.

What did you eat for breakfast?

Lots of coffee and a croissant.