Domino Data Lab Opens Platform for Data Scientists Advancing COVID-19 Research

SAN FRANCISCO, Calif., April 8, 2020 — Domino Data Lab, provider of an open data science platform for large enterprises, announced that it is extending complimentary access to its Domino data science platform to organizations that are advancing the collective understanding of the COVID-19 virus, its spread, and approaches to lessening its destructive effects across the population.

Researchers can access the project on Domino that is pre-populated with several datasets including the Center for Disease Control and Prevention Fluview, and the Johns Hopkins University 2019 Novel Coronavirus data repository. Those interested in participating can view and sign up for access to the COVID-19 infectious disease data project, and request expanded use of Domino for COVID-19 research in the blue dialogue box once they are registered.

The company has the benefit of working alongside data science teams at many of the top health and life science companies, and top universities globally that are at the forefront of battling COVID-19. Leading health and life sciences organizations with more than 1,500 data scientists active on Domino today are researching COVID-19 treatments, while finance, insurance, automotive, technology, and retail clients conduct a host of other virus analyses with implications across industries.

Domino’s data science platform offers data scientists the capacity to build, test and adapt their models in an open platform with the flexibility to use their preferred tools from open source technologies including R and Python, and established providers including SAS and Matlab on the first Kubernetes-native data science workbench. Together, data scientists remotely develop, test and deploy models in collaboration with colleagues worldwide—all with full reproducibility of experiments. IT teams are relieved because the unified platform allows them to support and provision environments as needed in a single pane of glass while using the most efficient compute in the cloud or on premise.

Reinsurance provider SCOR dedicated a task force to the analysis of the COVID-19 outbreak crisis. The team is composed of experts from their Knowledge Community including doctors, epidemiologists, actuaries and data scientists. Based on the data repository made available by John Hopkins University, they built and released a public web app in Domino to help visualize COVID-19 trends in a practical display of the essential information. Initially set up to build biometric risk models, the multi-expertise task force realized that sharing the data could help better inform the public.

“We have a responsibility to inform the public about the ongoing threat,” said Bruno Latourrette, SCOR Chief Knowledge Officer. They share a clear visual analysis of the pandemic that helps keep the public informed with daily updates of intuitive, interactive charts. People can see how many new cases have occurred by region, daily deaths, and recoveries, as well as the trajectory over time. The hope being to encourage more people to adapt their daily routines.

“Data is being generated and updated in almost real-time. Speed is critical in modeling and learning from these updates,” said Josh Poduska, Chief Data Scientist at Domino Data Lab. “It’s not so much a matter of not having enough data, but of not being able to digest all of the data points simultaneously gathered across the world into self-learning models, to build a better collective understanding of the disease by sharing those data models and learnings.”

By using machine learning to crunch through data and learnings from past diseases, medical data scientists are able to discover and match patterns with those other diseases to predict the most likely molecules or other therapies to successfully treat Coronavirus. They simulate tests to narrow the field of actual tests required in the lab which saves tremendous effort and time. Sifting through recorded text records becomes much faster and more efficient using data science. Instead of manually poring through stacks of academic research papers, NLP analysis helps uncover potential correlations and insights that can be used to help analyze COVID-19.