The Models of Infectious Disease Agent Study (MIDAS) research network has been highly productive, and a key challenge faced by the MIDAS and the general scientific community is how to make its models and datasets accessible to others so as to amplify and accelerate the research and discovery process. The value of data and software as research products has been widely acknowledged, but individual researchers can face persistent barriers to data sharing, including the prevailing publish or perish paradigm as the main driver for academic 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 a MIDAS Coordinating Center (MCC) that is investigator-focused, with the long-term goal of increasing the use of MIDAS research products for new research and discovery. Our approach will follow FAIR Data Principles 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 the Informatics Services Group (the current MIDAS Information Technology Resource) and add community-based research, outreach, education, and governance. We propose the following specific aims: (1) Facilitate compliance of MIDAS datasets and software with FAIR Data Principles; (2) Create FAIR "gold standard datasets" (GSD) to improve testing of MIDAS models; (3) Create a dynamic infrastructure and support services for data storage and high-performance computing; (4) Coordinate outreach through an annual network meeting and improved electronic communication channels; (5) Educate MIDAS trainees in open science and research design principles; and (6) Create executable workflow representations of MIDAS models to improve model testing and reproducibility. The MCC will augment the impact of NIGMS investments in basic scientific research by improving the use of MIDAS research products. Other scientists or computer algorithms will be able to discover, access, and integrate MIDAS products and increasingly, machine-driven access to, and use of, datasets and software will accelerate the rate of new discoveries and innovation for control of infectious disease threats. The MCC will be led by Dr. Wilbert van Panhuis, MD, PhD, who has worked as epidemiological modeler in the Pitt MIDAS Center of Excellence, and who has collaborated as data scientist with the ISG. Dr. Van Panhuis has a unique track record of unlocking access to valuable datasets previously unavailable to MIDAS and a proven ability to design, and successfully lead, large-scale international collaborations. As PI of the MCC Dr. Van Panhuis will proactively collaborate with MIDAS investigators and the MIDAS Steering Committee. The other MCC team members are also firmly rooted into the MIDAS community and have complementary expertise in infectious disease and data science.