How to fulfill open science expectations for simulation based research?

There is strong agreement across the sciences that replicable workflows are needed for computational modeling. Open and replicable workflows not only strengthen public confidence in the sciences, but also result in more efficient community science. However, the massive size and complexity of geoscience simulation outputs, as well as the large cost to produce and preserve these outputs, present problems related to data storage, preservation, duplication, and replication. The simulation workflows themselves present additional challenges related to usability, understandability, documentation, and citation. These challenges make it difficult for researchers to meet the bewildering variety of data management requirements and recommendations across research funders and scientific journals. This presentation will introduce initial outcomes from the EarthCube Research Coordination Network project titled What About Model Data? - Best Practices for Preservation and Replicability (https://modeldatarcn.github.io/), which is working to develop tools to assist researchers in determining what components of geoscience modeling research should be preserved and shared to meet evolving community open science expectations. Preliminary findings suggest that all code, initialization data, and configuration components of simulation workflows should be preserved and shared, and a determination can be made on what simulation outputs need to be preserved and shared by evaluating expected simulation experiment characteristics. Additionally, sufficient support for software and data curation need to be provided so researchers arent spending time allocated for research on these activities, and evaluation criteria for career advancement need to be updated to reward researchers for following open science practices.