Manas Sharma portfolio
Organisation size: Big
Manas Sharma stands out for pushing the boundaries of data visualization and for the level of maturity shown in his work as an early career journalist. The judges were impressed by a portfolio that could only be possible through mastering all aspects of a project from data collection and reporting to analysis and visualization. Readers are rewarded with digestible visual stories on a range of complex topics. Manas is a promising journalist to watch and follow.
The Reuters Graphics team are continuously thinking of ways to push the boundaries of reporting and gathering information. Manas Sharma has been instrumental in our progress in 2020, producing a number of striking examples which have pushed the boundaries of data journalism and visual storytelling. From building a COVID-19 epidemiological model from scratch to calculating the damage to the habitats of 1,400 animal species by the Australian bushfires.
This portfolio showcases some his best work, both from a data journalism perspective, such as his research and data scraping of all coronavirus research papers to deliver the “Speed Science” project, and also his innovative front end web development and production, like his presentation on the scale of Australia’s bushfires, that offered readers a navigable and digestible experience breaking his complex data work into understandable insights for the reader.
Manas, 24, is based in Singapore, working with the graphics team in Asia but collaborating on global stories and data projects.
Description of portfolio:
Stopping the spread
Building a herd immunity model
Research – key covid data points/parameters and the mathematics of model building
Analysis – batch running thousands of simulations through the model to reveal key findings
Production – front-end web development, allowing the simulations to run in the browser and be placed in the story. An additional, reactive interactive model was added at the bottom of the page for readers to input their own values.
Reuters built an epidemic model to simulate how the coronavirus can spread within a population. We ran the model thousands of times to compare when “herd immunity” would kick in for various reproductive numbers and under a range of scenarios. The model enabled us to show readers what level of immunity would likely be required in order to stop the spread.
Anatomy of Singapore’s outbreak
Scraping data – from daily press releases
Handling data – cleaning, formatting, merging
Analysis – to see how clusters were forming and how to visualise
Production – Coding animations in WebGL
Manas transformed printed Covid-19 case data into a slick animation of Singapore’s explosive worker dormitory clusters. The piece documents and explains how and where clusters formed. He used WebGL to enable the reader’s computer and browser to seamlessly render more than 30,000 nodes.
Assessing Australia’s “ecological disaster”
All data research work – Find, collect, clean, format data
Analysis – Used QGIS and Node.js to batch process fire hotspot data, overlay on each habitat, find the intersecting area, and ultimately calculate how much habitat was burned for every individual species.
Production – Finalised data set EXCLUSIVE to Reuters, which could be used by others on the team for the visualisations on the page.
As environmental agencies and other news organisations estimated the environmental damage from fires, a Reuters data analysis of more than 1,400 species revealed the true extent of destruction. We processed massive amounts of satellite-derived fire data and habitat information. By calculating the intersection of those datasets we were able to reveal the animals hardest hit by bushfires.
Sizing up Australia’s bushfires
Building the interactive graphic and web page and wiring in the data
An innovative explanation of the unprecedented scale of fires burning in Australia. We built a ticker linked to the scroll of the page which counts area as you progress, overlaying small countries and cities to show true scale. This very effective and innovative format has since been replicated in other online fire visualisations.
Speed science: The risks of swiftly spreading coronavirus research
Data – collecting and scraping all scientific papers related to the new coronavirus
Analysis – running language analysis to find all papers of interest, authors, locations
Exporting graphics – that could be used in the presentation
Web page build
A Reuters analysis found that at least 153 studies – including epidemiological papers, genetic analyses and clinical reports – examining every aspect of the newly discovered (at the time) COVID-19 – have been posted or published since the start of the outbreak. These involved 675 researchers from around the globe. This was a huge increase compared to MERS and SARS research.
While speedy scientific analysis is highly useful if it’s good, flawed or misleading science can sow panic and may make a disease epidemic worse by prompting false policy moves or encouraging risky behaviour.
One scientific post suggests links between the new coronavirus and HIV, a second says it may have passed to people via snakes, while a third claims it is a pathogen from outer space.