Site-based data curation based on hot spring geobiology

Abstract

Site-Based Data Curation (SBDC) is an approach to managing research data that prioritizes sharing and reuse of data collected at scientifically significant sites. The SBDC framework is based on geobiology research at natural hot spring sites in Yellowstone National Park as an exemplar case of high value field data in contemporary, cross-disciplinary earth systems science. Through stakeholder analysis and investigation of data artifacts, we determined that meaningful and valid reuse of digital hot spring data requires systematic documentation of sampling processes and particular contextual information about the site of data collection. We propose a Minimum Information Framework for recording the necessary metadata on sampling locations, with anchor measurements and description of the hot spring vent distinct from the outflow system, and multi-scale field photography to capture vital information about hot spring structures. The SBDC framework can serve as a global model for the collection and description of hot spring systems field data that can be readily adapted for application to the curation of data from other kinds scientifically significant sites.

Documenting provenance in noncomputational workflows: Research process models based on geobiology fieldwork in Yellowstone National Park

“…The students reported finding this prospective discussion of data collection methods and best practices helpful in their work, and many were successful at producing robust metadata in their field books that would be key for curating and sharing their data. The spreadsheet template, as well as an excerpt of one student's completed template are available in our Supplemental Materials (https://doi.org/10.6084/m9.figshare.5450809); this work is also discussed further by Palmer et al ().…”

“…To that end, we developed a method of Research Process Modeling. This approach draws on systems analysis and information modeling approaches, and is informed by both our prior work on this project (Palmer et al, ), and prior work on computational process curation (Goble et al, ) and workflow‐centric research objects (for example, Bechhofer et al, ; Belhajjame et al, ). The simple inventory described above became one of four components required to document the artifacts, processes, and relationships involved in the collection of physical samples and observational data.…”

“…Additionally, the inventory identifies the Minimum Information Framework (MIF) superclass and the Formats for each data artifact. The “MIF superclasses” are drawn from our prior work developing a high‐level information model for geobiology field data (Palmer et al, ). Classifying data artifacts according to MIF classes is helpful in supporting reuse of data for new purposes, and may aid access and retrieval functions as data collections are brought together in repositories over time.…”

“…Through the SBDC project, we sought to support the aggregation and integration of geobiology data within and across scientifically significant sites. In collaboration with geobiologists and National Park Service (NPS) personnel, we developed a Minimum Information Framework of key information classes that ought to be prioritized for collection and curation (Palmer et al, ). We additionally used the approaches described herein to identify optimal points of curatorial intervention in the research workflow; these are points at which data should be optimally documented and managed, thereby making field‐based processes retraceable, and the data collected reliably interpretable and reusable.…”

Physiology, Metabolism, and Fossilization of Hot-Spring Filamentous Microbial Mats

“…Detailed description of all protocols and techniques used for field collection, biomolecule extractions, and meta-omic analyses are presented in the Supplementary Information and briefly summarized here. Detailed descriptions of the experimental design and metadata curation strategies adopted for all aspects of the field and laboratory analyses in the present study are presented in the works of Palmer et al (2017) and Thomer et al (2018).…”