As part of our commitment to building the field of data science for social impact, data.org has launched a $10 million data.org Inclusive Growth and Recovery Challenge.
Any strong and growing economy requires an inclusive and resilient approach to growth to ensure that talent, innovation, and our communities can become stronger in times of stress. By tapping into the expertise of a broad pool of thinkers and doers, we aim to catalyze innovative and scalable solutions to help individuals and communities thrive, all the while building resilience to withstand future challenges.
We recognize that the COVID-19 global pandemic is affecting our society in profound ways and will require new and innovative approaches. Beyond the impacts on public health, the COVID-19 crisis is likely to have severe economic repercussions. Supply chains are being disrupted, businesses are suffering losses, workers are facing unemployment, and too many people lack the savings or credit to weather an economic downturn.
We are seeking inclusive growth proposals from and for anywhere in the world. We are particularly interested in the areas listed below – but welcome other proposals for using data science to advance shared prosperity, and help ensure an inclusive recovery.
- Alzheimer's Disease
- Anesthesiology
- Basic Science
- Biochemistry/Biophysics
- Cancer
- Cardiovascular
- Clinical Science
- Community Health
- COVID-19/SARS-CoV2
- Dermatology
- Diabetes
- Drug Development
- Endocrinology
- Genetics
- GI
- Healthcare Policy
- Hematology
- Hepatology
- HIV
- Immunology
- Medical Education Research
- Medicine
- Microbiology
- Molecular Biology/Cell Biology
- Nephrology
- Neuroscience
- Nursing/PA/Allied Professions
- Obstetrics/Gynecology
- Ophthalmology
- Orthopedic
- Pathology
- Pediatrics
- Pharmacology
- Physiology
- Precision Medicine
- Psychiatry
- Psychology/Behavioral Science
- Pulmonology
- Radiology
- Regeneration
- Surgery
- Translational Science
- Urology
- Faculty
- Institutional
- Junior Faculty
- MD Students
- New Investigator
- PhD Students
- Postdoc/Residents/Fellows
- Under 40 years old
- Under 50 years old
- Under 60 years old
- Underrepresented Groups
- Women