Overview:
How can we trust the integrity of results from research that relies on computations without repeating them? By certifying the successful original execution of a computational workflow that produced findings in situ. With certifications in hand, consumers of research can trust the transparency of results without necessarily repeating computations. The TRACE project is developing techniques and tools for certifying the results of computational research. This includes the creation of technical specifications for describing and certifying research artifacts as well as the development of reusable software tools
Principal Investigators: Bertram Ludäscher, Timothy McPhillips, Kacper Kowalik, Craig Willis
Funding Period: July 2022 – June 2025
Funding Source: NSF (2209628)
Collaborating Partnering Institutions: Cornell University, University of North Carolina at Chapel Hill
Overview:
Whole Tale is an NSF-funded Data Infrastructure Building Block (DIBBS) initiative to build a scalable, open source, web-based, multi-user platform for reproducible research enabling the creation, publication, and execution of tales – executable research objects that capture data, code, and the complete software environment used to produce research findings. A beta version of the system is available at https://dashboard.wholetale.org. The Whole Tale platform has been designed based on community input primarily through working groups and collaborations with researchers.
Principal Investigators: Bertram Ludäscher, Matthew Turk
Funding Period: March 2016 – February 2023
Funding Source: NSF (1541450)
Collaborating Partnering Institutions: University of Chicago, University of Texas at Austin, University of Notre Dame, UC Santa Barbara, University of Southern California, Cornell University, University of North Carolina at Chapel Hill