ACMD Seminar: The Future of Science Is Modular

Joel Chan
Associate Professor, University of Maryland

Tuesday, Oct. 20, 2026, 3:00-4:00 PM ET (1:00-2:00 PM MT)
In person at Gaithersburg Bldg. 101 LR D with VTC to Boulder 1-4020

Add this talk to your calendar: https://inet.nist.gov/calendar/ics/2336461

Abstract: Suppose we set out to design the record of science from first principles. We could start from what science needs its record to do (remember what we found, let others check and build on it, credit the people who did the work) and from the tools available in 2026 (the internet, immersive technologies, agentic workflows, and more), with none of the history of journals and papers. What would we build? Would it look like what we have today? I argue that we would build something modular: a record of questions, claims, evidence, and studies as composable, citable objects rather than narrative documents. Drawing on several years of research through design and field deployments in working research labs, I show what it could be (and in some cases, actually is) like to live in such a record today. A modular record remembers dead ends and unpublished results: in one cell biology lab, members routinely find and build on results that others recorded years earlier. A modular record can be perceived as well as read: in SenseEER, a prototype immersive sensemaking environment, statements become composable entity–relation objects, and hypotheses with weak evidential support visibly destabilize until researchers add evidence. A modular record also gives computational agents structure to work within: for example, tracing a model's parameters back to the primary measurements behind them, while scientists review what the agents propose. I close by inviting discussion of where a modular record might, or might not, fit the workflows of computational and measurement science, and what is needed to bridge the gap between our present information-overload reality and a modular future of science for all.

Bio: Joel Chan is an Associate Professor in the University of Maryland’s College of Information (INFO) and Director of the Human-Computer Interaction Lab (HCIL). His research and teaching work to enable a future where informed innovation is accessible to everyone, with a focus on human-centered design of novel information systems, such as search engines and knowledge management systems, in the domains of scientific discovery and design. His research has received funding from the National Science Foundation, the Office of Naval Research, the Institute for Museum and Library Sciences, Adobe Research, Google, Protocol Labs, the Chan-Zuckerg Initiative, Navigation Fund, and the Sloan Foundation, and received Best Paper awards and nominations from the ASME Conference for Design Theory and Methodology, the Journal of Design Studies, the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), and the ACM Conference on Creativity and Cognition (C&C). Previously, he was a Postdoctoral Research Fellow and Project Scientist in the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University, and received his PhD in Cognitive Psychology at the University of Pittsburgh.

Host: Simon Su

Note: This talk will be recorded to provide access to NIST staff and associates who could not be present to the time of the seminar. The recording will be made available in the Math channel on NISTube, which is accessible only on the NIST internal network. This recording could be released to the public through a Freedom of Information Act (FOIA) request. Do not discuss or visually present any sensitive (CUI/PII/BII) material. Ensure that no inappropriate material or any minors are contained within the background of any recording. (To facilitate this, we request that cameras of attendees are muted except when asking questions.)

Note: Visitors from outside NIST must contact Meliza Lane at least 24 hours in advance.