Announcing Ki data challenges for Brazil and India citizens
Create your own team to work with provided data on solutions to healthy birth, growth, and development and make a difference in your community
For the first time, the Grand Challenges team is partnering with Ki to run a data-driven challenge, and Ki data will be provided for call participants. Through this call, experts in research and data science can work together to identify innovative approaches to answering urgent questions about issues ranging from pre-term birth to stunting and wasting to cognitive impairment. Our goal is to speed up the cycle of innovation so that we can help more children lead healthy and productive lives, faster. We have opportunities for investigators in Brazil now, and we’ll be announcing additional opportunities for investigators worldwide in the coming months.
Ki is teaming up with Grand Challenges Explorations
Ki is an initiative funded by the Gates Foundation to promote data-driven problem-solving. Over the last three years, members of the Ki team have been aggregating data about birth, growth, and development into a large knowledge base and developing processes and tools to analyze and learn from it. Thanks to the generosity of data contributors around the world, we now have an unprecedented collection of data to work with.
Grand Challenges is a global family of initiatives that aims to get the world’s most creative minds to work on high-risk, high-reward innovations to improve people’s lives.
Grand Challenges Explorations (GCE), one of the Grand Challenges initiatives, gives $100,000, 18-month grants based on a simple two-page proposal so that innovators have the resources they need to see where very early-stage ideas may lead. GCE issues several calls for proposals every year.
In 2018, Ki is collaborating with GCE to issue calls for proposals for data-driven solutions to healthy birth, growth & development problems.
Developing and validating approaches to foster maternal and child health is challenging due to the complex interaction of biological, environmental, and social factors. Furthermore, policy recommendations for such approaches frequently lack sufficient supporting scientific evidence, while clinical trials are expensive, time-consuming, and increasingly difficult to implement.
Data-Driven Approaches to Improve Maternal and Child Health in Brazil