Outcomes from the Innovations in Open Science (IOS) Planning Workshop: Community Expectations for a Geoscience Data Commons

Data intensive research, including data analytics, machine learning, and data assimilation continues to drive innovation and discovery across the geosciences. Geoscience datasets maintained in domain repositories, such as climate model projections, historical reanalysis products and observing facility produced datasets provide rich resources to support these initiatives. Presently, these datasets are primarily maintained in disconnected, domain-focused data systems designed to support the legacy “download, clean and analyze model” that requires data to be downloaded to a local system and reorganized before any analysis can happen. This is a time consuming process with bandwidth and storage requirements that may be prohibitive, particularly for less resourced institutions. Additionally, datasets maintained through these domain-focused repositories may be provided with unique naming standards, metadata, data structures, and formats that are likely to create barriers to access for those outside of a domain, including those investigating interdisciplinary research ideas and attempting to generalize computational workflows. This combination of the download, clean, and analysis model and the use of non-standard formats combine to create a barrier to exploiting the full research potential of geoscience data assets.

This presentation will highlight the outcomes of a two day workshop that brought together more than 70 diverse individuals from multiple stakeholder groups to identify and outline requirements for a geoscience research data commons environment. The overall goal of the workshop was to ask participants to develop recommendations to satisfy community needs for geoscience research data commons from a broad range of perspectives. Additionally, we wanted to build a welcoming and inclusive community through the workshop that will provide the foundation for continued collaborative activities that result from the workshop. Workshop participants participated in plenary sessions and breakout discussions that focused on developing requirements to modernize community-accessible data science infrastructure, to better connect our geoscience datasets with geoscience-focused analytics environments, and to support researcher needs in meeting data sharing expectations in alignment with the FAIR (https://doi.org/10.1038/sdata.2016.18) and CARE (https://doi.org/10.5334/dsj-2020-043) principles.