A workflow for reproducing mean benthic gas fluxes

Abstract

Long-term data sets provide unique opportunities to examine temporal variability of key ecosystem processes. The need for such data sets is becoming increasingly important as we try to quantify the impact of human activities across various scales and in some cases, as we try to determine the success of management interventions. Unfortunately, long-term benthic flux data sets for coastal ecosystems are rare and curating them is a challenge. If we wish to make our data available to others now and into the future, however, then we need to provide mechanisms that allow others to understand our methods, access the data, reproduce the results, and see updates as they become available. Here we use techniques, learned through the EarthCube Ontosoft Geoscience Paper of the Future project, to develop best practices to allow us to share a long-term data set of directly measured net sediment N 2 fluxes and sediment oxygen demand at two sites in Narragansett Bay, Rhode Island (USA). This technical report describes the process we used, the challenges we faced, and the steps we will take in the future to ensure transparency and reproducibility. By developing these data and software sharing tools we hope to help disseminate well-curated data with provenance as well as products from these data, so that the community can better assess how this temperate estuary has changed over time. We also hope to provide a data sharing model for others to follow so that long-term estuarine data are more easily shared and not lost over time.

An introduction to the special issue on Geoscience Papers of the Future

“…The technical report of Fulweiler et al . [] offers a reproducible computational description of how they prepare data about nitrogen and oxygen fluxes from a bay in the Northeastern U.S., so that their research methods on benthic processes can be applied elsewhere. Other disciplines that also challenge the existing technologies and best practices for reproducibility, open science, and digital scholarship, are equally suited for a GPF.…”

“…Each of the aforementioned studies follows the GPF guidelines and discusses the benefits and challenges associated with the publication of a GPF. All papers consistently emphasize the added burden associated with openly sharing data, software, and methods [ David et al ., ; Essawy et al ., ; Fulweiler et al ., ; Pope , ; Yu et al ., ]. Documenting and sharing data is a particular challenge when files are large and diverse [ Essawy et al ., ] and/or unearthed from old studies [ Fulweiler et al ., ; Pope , ].…”

“…All papers consistently emphasize the added burden associated with openly sharing data, software, and methods [ David et al ., ; Essawy et al ., ; Fulweiler et al ., ; Pope , ; Yu et al ., ]. Documenting and sharing data is a particular challenge when files are large and diverse [ Essawy et al ., ] and/or unearthed from old studies [ Fulweiler et al ., ; Pope , ]. Challenges associated with documenting and sharing software and methods are especially acute for data‐intensive analyses [ Essawy et al ., ], further stressed when performed a posteriori of paper publication [ Pope , ], and sometimes rise from the self‐perceived inferiority of geoscientists' computer skills [ David et al ., ].…”

“…[2016] present a reproducible data-intensive impact study of drought on two U.S. States that is run remotely on a server and that uses a workflow framework that automatically records data products and tracks provenance. Fulweiler et al, 2016;Pope, 2016;Yu et al, 2016]. Documenting and sharing data is a particular challenge when files are large and diverse [Essawy et al, 2016] and/or unearthed from old studies [Fulweiler et al, 2016;Pope, 2016].…”

“…Yet all papers unanimously highlight the benefits of transparency for reproducibility. The open availability of digital products and the automation of the methods enable the verification and/or update of researchers' own results [David et al, 2016;Fulweiler et al, 2016] and also allow for reproducibility by others during peer review or for research purposes [David et al, 2016;Yu et al, 2016]. Additionally, open data sharing motivates detailed data curation and guarantees safer data storage [David et al, 2016;Fulweiler et al, 2016;Yu et al, 2016].…”