Accelerating COVID-19 modeling research by improving the discovery and new use of data: leveraging community engagement and automation of curation workflows

Project Summary: The Models of Infectious Disease Agent Study (MIDAS) research network has been highly productive, and akey challenge faced by the MIDAS and the general scientific community is how to make its models anddatasets accessible to others so as to amplify and accelerate the research and discovery process. The value ofdata and software as research products has been widely acknowledged, but individual researchers can facepersistent barriers to data sharing, including the prevailing "publish or perish" paradigm as the main driver foracademic tenure and promotion. While new technology can enable data sharing, a social-cultural, human-based approach is essential to improve data access and reuse in a community. We propose to create aMIDAS Coordinating Center (MCC) that is investigator-focused, with the long-term goal of increasingthe use of MIDAS research products for new research and discovery. Our approach will follow FAIR DataPrinciples developed by the NIH Data Commons Consortium to specify requirements for Findable, Accessible,Interoperable, and Reusable research products. We will leverage FAIR-enabling technology developed by theInformatics Services Group (the current MIDAS Information Technology Resource) and add community-basedresearch, outreach, education, and governance. We propose the following specific aims: (1) Facilitatecompliance of MIDAS datasets and software with FAIR Data Principles; (2) Create FAIR 'gold standarddatasets' (GSD) to improve testing of MIDAS models; (3) Create a dynamic infrastructure and support servicesfor data storage and high-performance computing; (4) Coordinate outreach through an annual network meetingand improved electronic communication channels; (5) Educate MIDAS trainees in open science and researchdesign principles; and (6) Create executable workflow representations of MIDAS models to improve modeltesting and reproducibility. The MCC will augment the impact of NIGMS investments in basic scientificresearch by improving the use of MIDAS research products. Other scientists or computer algorithms will beable to discover, access, and integrate MIDAS products and increasingly, machine-driven access to, and useof, datasets and software will accelerate the rate of new discoveries and innovation for control of infectiousdisease threats. The MCC will be led by Dr. Wilbert van Panhuis, MD, PhD, who has worked asepidemiological modeler in the Pitt MIDAS Center of Excellence, and who has collaborated as data scientistwith the ISG. Dr. Van Panhuis has a unique track record of unlocking access to valuable datasets previouslyunavailable to MIDAS and a proven ability to design, and successfully lead, large-scale internationalcollaborations. As PI of the MCC Dr. Van Panhuis will proactively collaborate with MIDAS investigators and theMIDAS Steering Committee. The other MCC team members are also firmly rooted into the MIDAS communityand have complementary expertise in infectious disease and data science.