SFI Applied Complexity Postdoctoral Fellow Sam Zhang joins the inaugural class of U.S. Research Software Sustainability Institute (URSSI) Early-Career Research Fellows. The fellowship supports “research projects focused on improving current disciplinary or domain practices in developing science software,” especially explorations of “emerging best practices (or problems) in sustaining” that software.
Zhang is a software engineer turned computational social scientist who studies the scientific enterprise as a complex system. At SFI, he is expanding his research program to include more work on society as a whole, including topics such as global human rights, and developing more applied solutions to the problems in the systems that he studies.
In his own previous work building data analyses, Zhang saw how interactions between social processes and coding practices drive researchers to release software that’s hard to reuse.
“Typically, scientists look toward software engineering as a model for how to write ‘good code.’ But developing an app is very different from creating a reproducible data-analysis pipeline,” says Zhang. “With this fellowship, I want to help make a more effective software-development model accessible to an academic audience.”
As a URSSI fellow, Zhang plans to develop a software package allowing scientists to develop easy-to-replicate code using an approach pioneered by the Human Rights Data Analysis Group, called principled data processing. This powerful set of guidelines, developed so that governmental truth commissions can reproduce their data analyses over decades, lines up well with the needs of academic data scientists.