ROOTED IN SCIENCE. ENHANCED BY PEOPLE.

Real-time scientific data curation

As a response to the COVID-19 infodemic, we’re developing the world’s first real-time systematic review tool by combining cutting edge machine learning and a global collective of dedicated curators.

LEARN MORE
Get involved
+700,000Data sources captured in our rapidly growing data lake
67.000Post-peer reviews completed to date
437Vetted curators registered on the platform

Responding to an infodemic

COVID-19 is the first pandemic in history in which technology and social media are being used on a massive scale to keep people safe, informed, productive and connected. At the same time, the technology we rely on to keep connected and informed is enabling and amplifying an infodemic that continues to undermine the global response and jeopardizes measures to control the pandemic.

Combating misinformation

Misinformation can be harmful to people’s physical and mental health; increase stigmatisation; threaten precious health gains, and lead to poor observance of public health measures.

Without the appropriate trust and correct information, diagnostic tests go unused, immunization campaigns will not meet their targets, and the virus will continue to thrive.

Preventing polarisation

Misinformation is polarizing public debate on topics related to COVID-19. If not addressed, it’s threatening long-term prospects for advancing democracy, human rights and social cohesion.

We’re creating the foundation for dissemination of accurate information, based on science and evidence and preventing the spread, and combating, misinformation.

Improving quality

We’re building the world’s largest and most current COVID-19 evidence sources consisting of 104,000 documents. This data pipeline converges with a novel curation methodology that adopts a “human in the loop” methodology for the characterisation of quality, relevance and key evidence across a range of scientific literature sources.

The human factor

By capturing curators’ critical appraisal methodology through the application of discrete labelling and rating of information, we’ve rapidly developed a foundational data science dataset of over 2529 articles in the realm of pooled COVID-19 information, representing ∼10% of the papers written worldwide on COVID-19 in under two weeks.

This methodology requires volunteers with a background in medicine and reviewing scientific content, to support analysis and assessment of the data that will drive REDASA.

Become a curator

We’re urgently seeking data curators to help in the fight against COVID-19.

You have
  • A background in medicine

  • Experience reviewing scientific content

  • A desire to analyse and assess data

We offer
  • Participation in a game-changing project

  • Listing as collaborators