STRABOSPOT DATABASE AND APPLICATIONS: COMMUNITY-DRIVEN AND VALUE-ADDED

The StraboSpot database and applications enable the collection, storage, and sharing of geologic data necessary to address data-driven Earth Science research questions. The StraboSpot Data System allows scientists to collect data in the field and in the lab, maintaining spatial relations and geologic context across scales. We have used a community driven approach in the development of StraboSpot, learning from the disciplinary groups their needs, workflows, and vision. Community engagement throughout the development process is critical to future community buy-in and adoption of the database.

Initial development of the StraboSpot database took place during a series of community workshops of about 10 to 40 participants. During these workshops, we developed metadata standards and shared vocabulary and worked to understand preferred workflows. Based on these workshops, we determined that it is necessary to provide one database for different data types and geologic disciplines, enabling interdisciplinary searching, and allowing users to combine different data types. To remove obstacles to data upload, we worked with community members to replicate natural workflows, and to provide added value through new tools.

This community engagement led to one database with three applications to upload data: Strabo2 for field data; StraboMicro for laboratory derived data, including microstructural (thin section) scale images and associated data (e.g., compositions, orientations); and StraboExperimental, for data derived from rock deformation experiments. Critically, samples are linked in the backend, providing ties between geologic field context and field samples, experimentally deformed samples, and the derived microstructural (thin section) data and images.

In response to community feedback, we are currently developing Group Workflows to enable collaborative work in the field and in the laboratory, while maintaining provenance and versioning. In addition, we are developing a Quality Assurance/Quality Control (QA/QC) system to add trust to observational data. StraboSpot conforms to FAIR (Findable-Accessible-Interoperable-Reusable) standards. A QAQC system can provide a transparent and objective infrastructure to assist scientists’ ability to share data, by facilitating the evaluation of that data, thus building trust in community shared data.