Data management, sharing, and reuse in experimental geomorphology: Challenges, strategies, and scientific opportunities

• We review practices of data management throughout the experimental lifecycle.
• Challenges are metadata guidelines, documentation, data storage, and incentives.
• We present resources and strategies for meeting challenges related to data sharing.
• We provide examples of a dataset description template and a workflow document.

The field of experimental geomorphology is in a data-rich era with rapid expansion of high-resolution, digital data sets. Millions of dollars have been invested in building and renovating flume laboratories that run experiments at increasing sophistication, scale, and resolution. However, this overflowing body of laboratory data is not easily analyzed, stored, or accessed. This lack of organization comes at substantial cost to the Earth-surface science community (i.e., geomorphologists, sedimentary geologists, and engineers) through missed opportunities to address scientific challenges. Here, we present an overview of the current state of data management practices and challenges within the context of the experimental lifecycle. Based on this assessment, we identify four areas of greatest need in order to achieve higher rates of data sharing and reuse: metadata guidelines, workflow documentation, data storage, and incentives and training. We suggest specific guidance for addressing these needs and summarize outstanding community debates regarding interoperability and human- versus machine-readability. A proposed metadata list includes basic data set information and disciplinary information for experimental geomorphology, including metadata for evaluating data quality and readiness for reuse. Data publication is presented as a framework for improving data sharing, and we discuss community-specific considerations for review of experimental data sets.