ALBERT

Description: Geobiology explores how Earth's system has changed over the course of geologic history and how living organisms on this planet are impacted by or are indeed causing these changes. For decades, geologists, paleontologists, and geochemists have generated data to investigate these topics. Foundational efforts in sedimentary geochemistry utilized spreadsheets for data storage and analysis, suitable for several thousand samples, but not practical or scalable for larger, more complex datasets. As results have accumulated, researchers have increasingly gravitated toward larger compilations and statistical tools. New data frameworks have become necessary to handle larger sample sets and encourage more sophisticated or even standardized statistical analyses. In this paper, we describe the Sedimentary Geochemistry and Paleoenvironments Project (SGP; Figure 1), which is an open, community-oriented, database-driven research consortium. The goals of SGP are to (1) create a relational database tailored to the needs of the deep-time (millions to billions of years) sedimentary geochemical research community, including assembling and curating published and associated unpublished data; (2) create a website where data can be retrieved in a flexible way; and (3) build a collaborative consortium where researchers are incentivized to contribute data by giving them priority access and the opportunity to work on exciting questions in group papers. Finally, and more idealistically, the goal was to establish a culture of modern data management and data analysis in sedimentary geochemistry. Relative to many other fields, the main emphasis in our field has been on instrument measurement of sedimentary geochemical data rather than data analysis (compared with fields like ecology, for instance, where the post-experiment ANOVA (analysis of variance) is customary). Thus, the longer-term goal was to build a collaborative environment where geobiologists and geologists can work and learn together to assess changes in geochemical signatures through Earth history. With respect to the data product, SGP is focused on assembling a well-vetted and comprehensive dataset that is tractable to multivariate statistical analyses accounting for multiple geological and methodological biases. Phase 1 of the project, which focused on the Neoproterozoic and Paleozoic, has been completed. Future phases will capture a broader range of geologic time, data types, and geography. The database contains tens of thousands of unpublished data points provided by consortium members, as well as detailed metadata that go beyond what is contained in papers. In many cases, these represent measurements that are tangential to a given published study but still of high utility to database studies; these allow the community to address questions that would be impossible to answer solely with the published data. For instance, in order to use a proxy such as Mo/TOC (total organic carbon) ratios in mudrocks deposited under a euxinic water column, the full suite of trace metal, iron speciation, and total organic carbon data is needed. Likewise, geospatial information is required to account for sampling biases, and many statistical learning approaches cannot accept, or have difficulty with, incomplete geological predictor variables. Ultimately, it is this complete data matrix that will allow for SGP’s most insightful analyses.