COVID-19 Roundup: Risk, Reopening, Recognition & More
As the COVID-19 pandemic sweeps the globe, big data and AI have emerged as crucial tools for everything from diagnosis and epidemiology to therapeutic and vaccine development. Here, we collect the latest news in how big data is fighting back against COVID-19.
Data intelligence firm Collibra has collaborated with visualization firm Tableau to compile a COVID-19 data catalog combining open datasets, business domain glossaries, and other reference data and integrate it with Tableau’s COVID-19 Data Hub. According to Collibra’s chief customer officer, the goal is to help decision-makers understand “what data is available and how it can be used, and to access relevant data and reports more quickly.” To read more, click here.
The ambient seismic noise produced by human beings walking, driving, and taking public transit has been drastically reduced by the pandemic. Researchers around the world collaborated to analyze data from hundreds of seismic sensors, including 65 citizen-owned and -operated “Raspberry Shake” seismographs, to examine how seismic noise levels had changed, finding a 50% worldwide decrease. To read more, click here.
Tata Consultancy Services (TCS) has announced a new suite of AI-powered software to help businesses reopen amid the pandemic. The suite, called Intelligence Urban Exchange (IUX) for Workplace Resilience, can help perform complex, data-oriented tasks like monitoring infection risk levels using contact tracing and video data, or predicting impacts to revenue and supply chains. To read more, click here.
The National Institutes of Health (NIH) has awarded a grant to researchers at Rensselaer Polytechnic Institute to develop AI tools for the identification of high-risk COVID-19 patients. “My group has been focusing on using artificial intelligence and deep learning to analyze medical imaging data with an emphasis on translating the technology from benchside to bedside,” said Pingkun Yan, assistant professor of biomedical engineering at Rensselaer.
Face masks have become widely prevalent during the pandemic – but they’re causing problems for some sectors. Facial recognition algorithms, in particular, are having trouble identifying faces under masks. According to a study from the National Institute of Standards and Technology, even the best facial recognition algorithms are failing to correctly identify masked faces between 20% and 50% of the time. To read more, click here.
A new tool created by researchers at the University of Texas at Austin and Northwestern University aims to help policymakers decide what data to track when setting standards for social distancing policy measures. The model generates a series of “trigger points” that, if crossed, alert policymakers that social distancing measures need to be strengthened to prevent crowding in hospitals. To read more, click here.
Cloud data platform provider Snowflake has announced a partnership with the state of California to deliver public access to COVID-19 data through the Snowflake Data Marketplace, effective immediately. California is also using Snowflake’s cloud data platform internally to store and analyze a variety of datasets, including COVID-19 case numbers, suspected case numbers, hospitalizations, available hospital resources and more. To read more, click here.
Do you know about big data applications for COVID-19 that should be featured on this list? If so, send us an email at [email protected]. We look forward to hearing from you.