All science is becoming data science

This is the eleventh in a series of interviews with members of the Machine Commons supplier Collective. Subscribe to the site to be alerted about future posts, or become a partner today!


Steve Purves is the co-founder of Curvenote, a collaborative writing platform for scientists and engineers, based in Alberta. Their mission is to bring the scientific method into the 21st century. In short, they're bringing dynamic processes from the software engineering field - such as collaboration, live links and version control - into a platform that's as easy to use as Google Docs.



Because not all scientists should need the skills of data scientists to work with data.



How have you found business during the pandemic?


“The pandemic, I think, has created a huge case for a change in direction. Back at the start of last year, I was working in a startup for the oil and gas industry."


"That’s an industry I’d previously left and had no intention of going back to, but was lured back by the prospect of being able to apply the new generation of machine learning tools to 3D seismic data."



Classic, lured by the opportunity to apply new tools to interesting data!


“Then, due to the pandemic, the oil industry hit crisis mode. There was a price crash, the pandemic… it just bombed the industry out for a while more severely than the cyclicality the industry sees, and belts were tightened - especially in R&D.”


“The pandemic really gives you a better understanding of how you’re spending your time."

"It puts things in perspective, for us and for a lot of people. I didn’t want to work in the oil industry anymore, except perhaps to help with the clean energy transition.”


“Then I met my co-founder Rowan, and we found that we had this shared mission: to create positive change, to change science - to change how it was done."

"To make it more effective with tools that were built for scientists today and support a modern scientific collaboration process.”



What do you mean, what’s wrong with the current tools available to the scientific community?


“Currently many researchers use a mish-mash of available tech – like Dropbox, Microsoft Word, Google Docs, Latex, git – managing to do all their work with stuff that wasn’t really made for them. As more scientists’ work involves data, this also includes increasingly specialized data analysis tools adding to the complication”


“What we are doing is trying to get a modern collaboration process going.”


“All science is basically turning into data science."

"Perhaps not in the ‘big data’/’machine learning’ sense of the word; not data science as traditional ‘tech’ businesses would see but, increasingly: scientists, engineers, and other technical professionals, must deal with data throughout traditional industries and the sciences. Those professionals are getting into Python, R, Julia and using those to process and analyze their data, to present their work.”


“I think things are getting more challenging, they’re getting even more computational.”




So, business has been interesting then?!


“The tech sector has been booming, especially around collaboration and communication, anything that supports remote working. I’ve been working remotely for over 8 years now but many people have now been pushed into that lifestyle and workstyle. It sort of highlighted the need for better tools for science specifically and in the face of a pandemic the importance of good science that can progress rapidly.”


“So yes, business is good for us!”



“We got accepted into YCombinator back in December 2020 and went through their W21 program. They’ve been really pushing us to look at how to grow the business. Defining future growth and what the business looks like 1, 5, 10 years down the line. That’s given us a real focus for us on our core mission, providing these tools for people working in research, science, and engineering - data scientists and the people they need to collaborate with.”