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I’m a Solver: Bogdan and Stephanie Yamkovenko

Bogdan and Stephanie Yamkovenko won The Economist-Nielsen Data Visualization Challenge, which asked the World to review Nielsen consumer data, generate insightful conclusions with broad implications, and present a compelling visual presentation of the most interesting ideas from the data. Over 4,000 Solvers from 101 countries signed up to participate in the Challenge. To view the Yamkovenko’s winning submission, a video of them presenting it at The Economist World in 2013 Festival, and profiles of all the Challenge finalists, please click here.

We saw an advertisement in The Economist for the Data Visualization Challenge sponsored by Nielsen and The Economist. The focus of the Challenge was to analyze a data set provided by Nielsen and to tell a story using data visualization. I am a journalist and have also done graphic design in the past, so I knew I could handle the visual story telling. Bogdan is a researcher and assistant professor with an affinity for statistics, which means that he could easily handle the data analysis.

Bogdan and I have been married for six years and had never previously collaborated professionally on a project. This Data Visualization Challenge was a great opportunity for us to combine our skills and, ultimately, be competitive.

We began our work on the Challenge with a brainstorm about the Nielsen global dataset, which consisted of the Nielsen Global Consumer Confidence Index and other data about consumer spending and purchasing habits. We decided to supplement the dataset with other widely available economic indicators (such as unemployment rates). We noticed that countries that had high confidence in their economies were not necessarily the best performing economies.

When working on my master’s degree in journalism, I developed an appreciation for my profession’s role as the “fourth estate.” As we looked at the confidence index, we noticed that countries such as Saudi Arabia and Egypt had high confidence, but their economies weren’t doing that great. We wondered whether democracy was playing a role in the citizens’ confidence. We decided to include the Reporters Without Borders Press Freedom Index in our analysis, and found that countries with the highest confidence also had the most restricted press. This finding gave us a compelling story to tell and gave the original Nielsen dataset more context and depth. Read more

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Happy New Year!

Dear Seekers & Solvers –

As we enter 2013, we would like to thank you – our Seekers and Solvers alike – for your continued support of InnoCentive. We achieved great things with your help, and anticipate growing momentum this year. But, before looking forward to 2013, let’s take a few moments to consider the past year and recap our journey together.

This year has been exciting and groundbreaking in many ways: Our global Solver network grew to over 275,000 creative and diverse minds, we crossed the 1,500 threshold in external Challenges posted to our network, and we exceeded $13 million in total awards paid out to our Solvers. Additionally, our Seekers – and their Challenges – grew more diverse in 2012 due to the increased use of Challenges in industries such as aerospace, financial services, healthcare, and the public sector. Further, the adoption of “Big Data” Prodigy Challenges among our Seekers (e.g., Cleveland Clinic and Prize4Life) saw explosive growth. All of these trends mean exciting new opportunities for Seekers and Solvers alike in 2013!

Our mission has always been to help address and resolve problems that matter, so we have been fortunate to have worked with incredible organizations that ask the world to address global concerns and make extraordinary things happen. We – the collective “we” which includes Seekers, Solvers, and InnoCentive – helped Prize4Life to better predict the progression of disease in ALS patients. We announced the conclusion of the “Global Giveback Challenge Series,” a collaboration between InnoCentive, GlobalGiving, and the Rockefeller Foundation to find solutions to dire water-related problems in developing countries. And we helped BeyondPolio find novel ideas for reducing the cost of using inactivated poliovirus vaccine (IPV) to help in the final stages of the global polio eradication effort. There are many more examples, but suffice to say, we still firmly believe in changing the world, one Challenge at a time.

As many of you know, we kicked the year off with our acquisition of OmniCompete, a firm based in London that specializes in Grand Challenges and is best known for its long-running Global Security Challenge. This acquisition also enabled us to expand our presence in the United Kingdom and Europe. Prior to this acquisition, in December 2011, we announced a strategic alliance with Booz Allen Hamilton to bring to market integrated, full-service open innovation and Challenge offerings to both commercial enterprises and public sector agencies. Read more

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I’m a Solver: Torsten Hothorn

Dr. Torsten Hothorn has been on quite a run lately working on Prodigy “Big Data” Challenges. Recently, he won the $30,000 Cleveland Clinic Challenge, Build an Efficient Pipeline to Find the Most Powerful Predictors, and he earned a $10,000 award for his second place finish in The DREAM-Phil Bowen ALS Prediction Prize4Life Challenge. (We recently profiled Lilly Fang, a member of one of the two first place winning teams for the Prize4Life Challenge, and also posted a Seeker Spotlight featuring Prize4Life’s Neta Zach which dives into the background of the Challenge and final results). We’re happy to have Dr. Hothorn here to discuss his experience with these important Challenges.

I am a Professor of Biostatistics in the Department of Statistics at the University of Munich, Germany, and I’m interested in both methodological developments and applications of statistical models in medicine and biology. Research and teaching in Biostatistics ideally brings together practical problems and statistical theory. While I mainly teach students of statistics, I enjoy working with scientists from fields as diverse as oncology, ecology, and forestry. Because a statistical model is only useful when it actually can be applied to gain insights into aspects of data that otherwise would remain hidden, I spend a lot of time developing and implementing new statistical models. Some open source software packages to which I contributed are distributed via CRAN, the R package repository.

Developing statistical software always means pushing forward existing functionality. One of the best and most effective ways to find out where improvements are needed most is to work on the solution of practical problems, apply the software, and look at the results. While I’m not short of collaborators with interesting problems, I decided to give one of the Cleveland Clinic Challenges hosted by InnoCentive a shot when I first learned about InnoCentive in the Fall of 2011. In 2004 and 2006, I authored two scholarly papers about nonparametric survival models that also work in the presence of numerous potentially predictive variables. The Cleveland Clinic Challenge, “Build an Efficient Pipeline to Find the Most Powerful Predictors,” was an exact match for the models that I developed and described in these two papers. Luckily, I had already invested a fair amount of time into a software implementation, using the R add-on package “party,” and thus the solution was (almost) at my fingertips.

I must admit that “The DREAM-Phil Bowen ALS Prediction Prize4Life Challenge” was a little more challenging than I first thought. With the patient data coming from different clinical trials, it took a while to compile the data into a format suitable for statistical analysis. The relatively complex longitudinal structure of the data, the expected weak association between predictor variables and ALS disease progression, and the large amount of missing values in some of the potentially interesting predictor variables suggested that a nonparametric regression approach (e.g., random forests), might be a good candidate for a potential solution. However, the Challenge data gave me a hard time predicting ALS disease progression with good accuracy. Eventually, I went back and started from scratch. First, I slightly reformulated the Challenge objective by using an alternative statistical measure for describing the disease progression of a patient. In a second step, I collected as much information as I could about the disease progression in the first three months in which a patient was under observation. I observed that using these variables as predictors of the new ALS disease progression measure lead to better performing models.

Besides my interest in applying software that I developed and the thrill of competing with people from all over the world in this prediction Challenge – the InnoCentive leaderboard is really something one can get addicted to – I look forward to using the PRO-ACT database (a subset of which the Prize4Life Challenge was based on) in the classroom. Next spring, I’ll teach longitudinal data analysis and I intend to let my students work with the ALS patient data. That way, my students will be constantly reminded what the models and formulae presented on the blackboard are actually good for and what scientific obligation to society actually means to a statistician.

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Seeker Spotlight: Prize4Life

In July 2012, we launched a computational Challenge, The DREAM-Phil Bowen ALS Prediction Prize4Life Challenge, with Prize4Life to better predict the progression of disease in ALS patients. Earlier this month, Prize4Life announced the winners. The judging panel received an overwhelming response, with 1,073 Solvers having signed up, and submissions coming from around the world. Given the quality of the submissions, the judging panel doubled the original prize purse to $50,000. We’re very pleased to have Dr. Neta Zach, Scientific Director for Prize4Life, join us to discuss this Challenge. (Ed Note: Dr. Zach’s colleague, Dr. Melanie Leitner, was interviewed in July at the launch of the Challenge).

Hello Dr. Zach –  Could you take us back to the beginning and help us to understand what motivated you to run this Challenge, and in particular, why you opted for a computational “Big Data” Challenge?

Prize4Life’s mission is to accelerate the development of treatments and a cure for ALS. We have embraced the prize-for-breakthrough model in part because we are interested in attracting new and innovative ideas to ALS research. One area that we identified with great potential is quantitative analysis of ALS data. To that end, we developed the PRO-ACT (Pooled Resource Open-Access ALS Clinical Trials) database in collaboration with the Northeast ALS Consortium (NEALS) and the Neurological Clinical Research Institute at MGH, with funding from the ALS Therapy Alliance. PRO-ACT, which will be launched in early December, contains information from over 8,500 patients from past clinical trials, ten times more than had been previously available.

The DREAM-Phil Bowen ALS Prediction Prize4Life Challenge (a.k.a. ALS Prediction Prize) was a way to utilize, for the first time, the new and promising PRO-ACT database. Specifically, we wanted to use it in order to confront a basic puzzling question in ALS: most patients are like Lou Gehrig, with a rapidly progressing disease course. Some patients, however, turn out to be more like Stephen Hawking, where the disease progression is delayed. What separates the Lou Gehrigs from the Stephen Hawkings?  Understanding the variability of the disease can mean a lot for ALS patients going through diagnosis and can lead to a substantial reduction in the cost of clinical trials for ALS treatments. The unique approach of providing ALS “Big Data” to a global community of researchers speeds up the process while driving down the costs of discovery, which is good news for both the scientific and patient communities we serve.

Having run a couple of high-profile Challenges now, was there anything that particularly surprised you during the course of this Challenge?

We were happily surprised by the level of engagement this prize received. We had over a 1,000 registered Solvers. You can see the engagement in the quality of the winning solutions, but beyond that, the fact that so many Solvers – from 64 countries no less – were actively engaged on the forum and through emails, with over 300 forum messages and 1,500 emails, speaks to the success of this Challenge! Indeed, this engagement bore fruit – even the solutions that didn’t win were so valuable that we encouraged several of the Solvers to submit for publication in scientific journals to share their algorithms with the ALS community at large. This was our first large scale interaction with the quantitative community and we were thrilled by their hard work and devotion to the cause.

I understand that two teams secured first place, each winning $20,000, and a second place winner was awarded $10,000. In fact, the judges decided to double the size of the prize purse based on these submissions. What stood out about these submissions and differentiated them from the others? Read more

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Seeker Spotlight: U.S. EPA & HHS – My Air, My Health Challenge

In June 2012, we launched Phase 1 of the My Air, My Health Challenge seeking to spur the development of personal devices that gather and integrate health and air quality data that is usable and meaningful to long-term health outcomes. Sponsored by the U.S. Environmental Protection Agency (EPA) and U.S. Department of Health and Human Services (HHS) [Office of the National Coordinator for Health Information Technology (ONC) and National Institute of Environmental Health Sciences (NIEHS)], four finalists were announced today to proceed to Phase 2, which entails building and testing a prototype sensor device and offers a $100,000 award to the winner. We recently spoke with Dr. David Balshaw, Program Director for Emerging Technologies at NIEHS, about the Challenge.

Hello Dr. Balshaw. Thank you for joining us today and congratulations on the successful conclusion of Phase 1. Taking us back, what were your original goals for this Challenge and how do you envision that the solutions currently being proposed will address the issue of airborne pollutants and their associated health risks?

In the environmental health research community, we always struggle with our ability to make direct connections between exposure to environmental pollutants and physiological responses at the individual level. While there have been a number of emerging technologies for exposure assessment as well as physiological monitoring, we haven’t seen many efforts to integrate these two capabilities. Combining the analyses of these data streams would improve those linkages. Ultimately, we wanted to see what creative solutions the community could come up with!

Over the last few years, crowdsourcing and prize competitions have become an increasingly popular means for government to innovate and promote strong public-private partnerships. What was your impetus for employing a crowdsourced competition model to achieve your goals for this Challenge?

The Challenge mechanism has really demonstrated an ability to bring innovative ideas into a new field. We thought this problem was an excellent fit because there are so many new technologies out there. Groups didn’t need to put a lot of resources into engineering, and there was a high likelihood of getting a useful device out at the end.

Phase 1 of the My Air, My Health Challenge attracted over 500 Solvers and generated dozens of solution submissions. What are your thoughts on the overall quality of the responses that you received? Read more

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Seeker Spotlight: Popular Science

We recently announced the successful outcome of the Popular Science-InnoCentive Education Challenge. The Challenge, which attracted more than 1,200 Solvers from around the world, asked for lesson plans that could be used at the middle-school level in each of five areas of science that will be vital in the future. Materials couldn’t cost more than $50, and the lesson needed to fit into no more than three, 50-minute classes. We asked Jacob Ward, editor-in-chief of Popular Science, to chat with us about the Challenge and results.

Hello Mr. Ward – thanks for joining us today. Could you tell us about the genesis of this Challenge and what you hoped to accomplish?

For our annual education special — the September issue of Popular Science — we look for ways to inspire a wide range of readers. Our audience runs the age range from 10-year-olds all the way up to retired grandparents. So Popular Science, in collaboration with InnoCentive, wanted to run a Challenge that could conceivably affect all of these people.

The Challenge asked Solvers to submit lessons plan in five distinct areas – Bomimetics, fuel cells, polymers, climate change, and “big data.” What led you to choose these specific areas?

In the end, we wanted to come up with lesson plans for the future of science, out beyond what people are teaching today. We consulted with educators, futurists, and other experts to settle on five areas of growing interest, and that we knew had the potential to really revolutionize their respective fields. Biologically-inspired (biomimetic) design is a growing trend at the moment, fuel cells could truly overturn the power mechanisms we rely on today, and everyone’s talking about “big data” — we figured that if we could engage kids today in these areas, we’d be helping to pave the way to some truly revolutionary work when those kids enter the workforce in a couple of decades.

You posted the winning solutions (i.e., lesson plans) on PopSci.com, along with details about the second and third place entrants. What drove you to open the solutions to the public and what’s the response been like?

With a Challenge like this, it was incredibly difficult to choose a winning entry for each category, because we received so many inspiring and revolutionary ideas. So we figured that even though not everyone could win, we wanted as many lesson plans as possible to get public visibility. There were so many useful lesson plans submitted, and teachers need new lesson plans so badly, why not put them all out there?

Of the dozens of InnoCentive Challenges that have been posted to the PopSci Innovation Pavilion, we’ve seen PopSci provide significant lift – both in terms of number of Solvers and their submissions. To what do you attribute your readers embracing open innovation Challenges and becoming successful Solvers? Read more

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Seeker Spotlight: Sandler-Kenner Foundation for Pancreatic Cancer

We recently completed an Ideation Challenge for the Sandler-Kenner Foundation for Pancreatic Cancer which looked for new tools and approaches for earlier diagnosis of this deadly disease. We spoke with Dr. Gregory Echt, Chairman of the Foundation, about his experience with the Challenge process and the results. 

Hello Dr. Echt. As we understand it, this was your first experience with Challenge Driven Innovation. How did it go?

We felt the InnoCentive Challenge went very smoothly. We appreciated the help and support of your staff in guiding us through the process, as well as helping us to understand how to most effectively formulate our Challenge and to review submissions. 

Was there anything that particularly surprised you during the Challenge?

We were pleased with the number of replies and equally impressed with the overall quality of the responses. They were thoughtful and demonstrated novel and critical thinking skills, often utilizing research approaches from other areas of science. The reach of the Challenge was astounding — we had interest from over 500 Solvers in 57 countries. Over 60 submissions came from 17 countries, which confirmed to us that early detection of pancreatic cancer is a pressing worldwide problem. 

You ended up making four awards totaling $12,500.  Tell us about some of the solutions you received and their possible impact.

I want to reiterate that I was very pleased with the quality of all of the submissions. In general, we found the winning solutions remained focused on our goal, which is to develop highly sensitive detection tools that can be easily implemented by medical professionals and eventually cost effective enough to become part of a routine medical practice. The winning team from New Delhi applied their expertise and knowledge gained through studies on the development of a non-invasive early diagnostic method for tuberculosis. The three recognition awards had varied backgrounds. One is a senior lecturer in molecular microbiology, and another has an M.D.-Ph.D. in biophysics with an interest in the nano-technological side of bioresearch.  The third recognition awardee proposed the use of a 3D non-invasive high resolution ultrasound. Interestingly enough, this awardee was motivated by a family member who had recently been diagnosed with pancreatic cancer.

I believe that you have been in touch with the winning Solvers. Can you tell us more about those conversations and your plans for the winning solutions?

We have been in touch with all of the Solvers. They have all expressed their appreciation for the recognition of their work. One of the awardees indicated that his research team would use this award to fund a pilot study. We have also put the winning Solvers in touch with each other, encouraging them to learn from each other and to continue the discussion on early detection. We plan to follow these researchers in order to encourage the development of their ideas.

Our Solvers always welcome feedback.  Is there any advice you would offer after reviewing so many submissions? Read more

Anjai Lal

The Economist’s Entrepreneurship Challenge Winners

Anjai Lal and Sahsa Vyash are the the winners of the third Economist-InnoCentive Challenge, The Economist-InnoCentive Entrepreneurship Challenge. They presented their winning plan at The Economist’s Ideas Economy: Innovation Event on March 23-24 in Berkeley, CA. This blog post is by Anjai.

Anjai Lal

I am currently a second year MBA student at the Yale School of Management. I graduated from Indian Institute of Technology in 2006 with a major in Electrical Engineering. Thereafter, I worked with British Telecom as a consultant where I was primarily involved in strategy and planning. At BT, I held a cross functional profile that spanned around Crisis Management, Strategy, Technology, Finance and Project and Vendor Management. I am passionate about the telecom/technology sector and am extremely interested in the emerging markets. I will graduate from Yale School of Management in May, 2011.

At Yale, my interests lie in Strategy, Finance and Technology. I spent the last summer with Zephyr Management, a Private Equity fund in NYC. I also interned with IBM in Business Performance Services. I head the South Asian Business Forum at the School of Management and am also a member of the organizing team of Asia Tomorrow- Yale’s premier student run conference. Read more

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Solution Revealed: Economist Ideas Economy Cyberschool Challenge Winner – Andrew Deonarine

Earlier this month, The Economist announced a winner in the 21st Century Cyber Schools Challenge.  There were many strong submissions, and the team decided that the two runners up also deserved recognition for their outstanding solutions.  We will be posting solution summaries from the Challenge winner, Andrew Deonarine, as well as the two runners up in this Challenge, Tristram Hewitt and Daniel Rasmus.  Congratulations Andrew, Tristram and Daniel.

Below is a summary of the winning solution from Andrew Deonarine.  To see a larger version of the image, right click and select “view image”

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In locations such as South Asia and sub-Saharan Africa, children, teens, and adults do not have access to education. Many are illiterate, and cannot make use of books and other learning material. While some technologies, such as inexpensive laptops and tablets have been proposed to address the educational needs of this population, the devices are too expensive, require some degree of literacy, and are difficult to implement in resource poor areas. However, cellular phones have significant penetration in the world’s poorest countries, since they provide a means to make a living. In essence, they comprise a global, untapped computer network.

In this solution, I have presented a cellular phone based technology called EduCell that develops and distributes educational material using a method called PhoneCasting. PhoneCasting allows someone to write their own educational program using their phone and distribute it to other devices. EduCell consists of a piece of software that that runs small multi-lingual “scripts”, easily developed by local teachers in developing countries. Scripts are then assembled with multimedia to create interactive modules that teach reading, writing, arithmetic, etc. Modules can then distributed (PhoneCasted) to millions of other phones via an Internet server, or pre-loaded, at no cost. The benefits of the PhoneCasting technology are significant: a software programmer or knowledge of English is not required to produce content, which democratizes software development. This would, for the first time, make basic literacy and educational material accessible to hundreds of millions of cellular phone users, and their children, around the world.

Dr. Andrew Deonarine

Solution Revealed: Economist Ideas Economy Cyberschool Challenge Runner Up #1, Tristram Hewitt

Earlier this month, The Economist announced a winner in the 21st Century Cyber Schools Challenge.  There were many strong submissions, and the team decided that the two runners up also deserved recognition for their outstanding solutions.  We will be posting solution summaries from the Challenge winner, Andrew Deonarine, as well as the two runners up in this Challenge, Tristram Hewitt and Daniel Rasmus.  Congratulations Andrew, Tristram and Daniel.

Below is Tristram’s summary of his solution:

Imagine a school house in a Nicaraguan village. One hundred students, each with nothing but a laptop, independently engage in their lessons. A precocious twelve year-old collaborates with an Ecuadorian peer on a biology project about rural water contamination over the cyber school learning platform. To her right, an eleven year-old, who tended the family’s coffee plot for the past year, plays a computer game to practice basic addition.

In this cyber school, semi-automated teaching systems power an individualized education. Students learn basic concepts, broken into independent lesson modules, through a mix of multi-media programming, games, interactive assignments, and live teacher contact. Structured peer interactions build creative and critical thinking skills. The teacher’s primary task, then, is not to “stand and deliver” but to facilitate student movement through pre-designed lessons. On the ground level, social workers supervise the school house; encouraging students, engaging parents, and creating the socio-emotional foundation required for academic success.

Grade levels do not exist. Rather, students advance through a course sequence outlined in the primary and secondary school curricula, each of which has a distinct purpose. While primary school teaches the minimum skills and knowledge required for participation in economic and civic life, secondary school prepares students for a vocation or university.

Combined, these elements form a scalable school model. Automated teaching technologies keep costs low by enabling high student-to-teacher ratios. Centrally managed courses improve quality. Local support systems ensure widespread access. Children in the developing world enjoy a newfound opportunity to realize their potential.