Vote by Jan. 6 for Most Promising Health Data Platform for Open Science Prize | Healthcare Informatics Magazine | Health IT | Information Technology Skip to content Skip to navigation

Vote by Jan. 6 for Most Promising Health Data Platform for Open Science Prize

January 3, 2017
by David Raths
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Prize supports development of services, tools or platforms that enable open health content sharing to spark innovation
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Jan. 6 is the deadline for the public to vote for the most promising candidates for the Open Science Prize, which will be awarded to one of six international  teams that has developed the most promising prototype to unleash the power of open content and data to advance biomedical research and its application for health benefit.

The prize contest is a partnership between the Wellcome Trust, the U.S. National Institutes of Health and the Howard Hughes Medical Institute. It  provides funding to encourage and support the prototyping and development of services, tools or platforms that enable open content — including publications, datasets, codes and other research outputs — to be discovered, accessed and re-used in ways that will advance discovery and spark innovation. All teams applying for the prize had to include at least one member based in the US, and at least one member based in another country.

For Phase I of the Open Science Prize, six teams each received prizes of $80,000 to develop their prototypes. The Phase II prizewinner, to be announced in March, will receive the prize of $230,000. The public is being asked to vote on which projects should be shortlisted for the prize.

When you vote, you will be asked to select your top three prototypes in order, and you are only able to vote once. The three teams receiving the greatest number of public votes will be shortlisted and the final decision made by the expert advisors and partners. Voting closes at 11:59pm PST on Jan. 6.  

Here are brief descriptions of the prototypes:

Fruit Fly Brain Observatory

Mental and neurological disorders pose major medical and socioeconomic challenges for society. Understanding human brain function and disease is arguably the biggest challenge in neuroscience. To help address this challenge, smaller but sufficiently complex brains can be used. This application will store and process connected data related to the neural circuits of the fruit fly brain. Using computational disease models, researchers can make targeted modifications that are difficult to perform in vivo with current genetic techniques. These capabilities will significantly accelerate the development of powerful new ways to predict the effects of pharmaceuticals upon neural circuit functions.

Open Neuroimaging Laboratory

There is a massive volume of brain imaging data available on the internet, capturing different types of information such as brain anatomy, connectivity and function. This data represents an incredible effort of funding, data collection, processing, and the goodwill of thousands of participants. The development of a web-based application called BrainBox will enable distributed collaboration around annotation, discovery and analysis of publicly available brain imaging data, generating insight on critical societal challenges such as mental disorders but also on the structure of our cognition.


MyGene2: Accelerating Gene Discovery with Radically Open Data Sharing


Approximately 350 million people worldwide and over 30 million Americans have a rare disease. Most rare diseases are Mendelian conditions, which means that mutation(s) in a single gene can cause disease. Over 7,000 Mendelian conditions have been described to date, but the causal gene is known for only half. Consequently, close to 70 percent of families who undergo clinical testing lack a diagnosis. MyGene2 is a website that makes it easy and free for families with Mendelian conditions to share health and genetic information with other families, clinicians and researchers worldwide in order to make a match.

OpenAQ: A Global Community Building the First Open, Real-Time Air Quality Data Hub for the World

Poor air quality is responsible for one out of eight deaths across the world. Accessible and timely air quality data is critical to advancing the scientific fight against air pollution and is essential for health research. OpenAQ aims to provide more timely information on poor air quality by combining the world’s publicly available, official real-time data onto one open-source and open data platform.

Real-Time Evolutionary Tracking for Pathogen Surveillance and Epidemiological Investigation

 The goal of this project is to promote open sharing of viral genomic data and harness this data to make epidemiologically actionable inferences. The team will develop an integrated framework for real-time molecular epidemiology and evolutionary analysis of emerging epidemics, such as Ebola virus, MERS-CoV and Zika virus. The project will use an online visualization platform where the outputs of statistical analyses can be used by public health officials for epidemiological insights within days of samples being taken from patients.


OpenTrialsFDA aims to increase access, discoverability and opportunities for re-use of a large volume of high quality information in the publically available Federal U.S. Food and Drug Administration drug approval packages. These review packages often contain information on clinical trials that have never been published in academic journals. However, despite their high value these FDA documents are notoriously difficult to access, aggregate, and search. As a consequence, they are rarely used by clinicians and researchers. The project will allow third party platforms to access, search, and present the information, thus maximizing discoverability and impact.

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