PNNL scientists explore a new model for research and data sharing.
Scientists conducted an “open experiment” in which every aspect of a laboratory experiment was documented online and in real time. This model pushed the researchers to write higher-quality analysis code, shortened the time required to do so, enabled them to quickly identify problems, and resulted in a stronger publication.
Researchers in every field of science are being pushed—by funders, journals, governments, and their peers—to increase the transparency and reproducibility of their work. A key part of this effort is a move toward open data as a way to fight post-publication data loss, improve data and code quality, enable powerful meta- and cross-disciplinary analyses, and increase public trust in, and the efficiency of, publicly funded research. The approach used in this study is a way to help researchers achieve these goals and may serve as a model for others.
In early 2015, Department of Energy scientists at Pacific Northwest National Laboratory planned a laboratory incubation experiment to characterize the chemical and biological properties of sub-Arctic, active-layer soils subjected to changes in temperature and moisture. This experiment required (1) a multidisciplinary team that was not located in one time zone; (2) integration of various data; (3) rapid performance of quality control and diagnostics, so that if instrument problems arose the team would lose only the minimum amount of time and data; and (4) tight integration of data, statistical analyses, and manuscript results. The team designed a data processing and analytical system written in an open-source and widely used language for statistical computing and graphics, and placed it in a publicly available “repository” that stored all code and data, making them available in real time. Using an automated analytical pipeline in an open repository provided significant advantages for the project, but the costs of such an approach and investments required should also be considered.
Contacts (BER PM)
Daniel Stover and Jared DeForest
Daniel.Stover@science.doe.gov, 301-903-0289; and Jared.DeForest@science.doe.gov, 301-903-1678
Pacific Northwest National Laboratory
This research was supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science program.
Bond-Lamberty, B., P. Smith, and V. Bailey. 2016. “Running an Open Experiment: Transparency and Reproducibility in Soil and Ecosystem Science," Environmental Research Letters 11(8), 084004. DOI: 10.1088/1748-9326/11/8/084004. (Reference link)
SC-23.1 Climate and Environmental Sciences Division, BER
BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER
May 10, 2019
Quantifying Decision Uncertainty in Water Management via a Coupled Agent-Based Model
Considering risk perception can improve the representation of human decision-making processes in age [more...]
May 09, 2019
Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Scenarios
Study provides country-specific urban area growth models and the first dataset on country-level urba [more...]
May 05, 2019
Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning
A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in bu [more...]
May 03, 2019
Calibration and Uncertainty Analysis of Demeter for Better Downscaling of Global Land Use and Land Cover Projections
Researchers improved the Demeter model’s performance by calibrating key parameters and establi [more...]
Apr 22, 2019
Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles
Representation of warm temperature events varies considerably among global climate models, which has [more...]
List all highlights (possible long download time)