Finalized:
Wednesday, December 4, 2013Author(s):
Hsu, L., B. McElroy, R. L. Martin, and W. KimAssociated Group(s):
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Laboratory experiments in geomorphology and sedimentology provide compelling visualizations and insight into processes that shape the landscape and generate stratigraphy. Taking water and sediment as the basic ingredients, experiments produce physical analogues to mountain, valley, river, delta, and submarine environments, offering rich information on the linkages between modern processes and the sedimentary record of Earth history (Paola et al., 2009). However, contemporary experiments produce large volumes of dark data in ad hoc formats (i.e., data that are not in digital format or not accessible from the internet). These data are therefore impractical to other Earth scientists who could reuse them and accelerate the pace of discovery. Because cross-disciplinary communication and collaboration are becoming critical for providing rich new research opportunities (e.g.Montanez and Issacson, 2013), we must find a community-scale solution for improving data preservation and re-use.
We describe a new effort to determine and address needs and promote consensus responses of scientists and educators in the Sedimentary Experiment community. The initiative will coordinate community discussion and activity to help facilitate best practices in experimental methods and in the storage, archiving, and dissemination of experimental data. This will result in a more informed, capable, and efficient scientific enterprise. This article summarizes the motivation, current activities, implications, and avenues for broad participation of the group that is spearheading this effort, the Sediment Experimentalists Network (SEN).
Suggested Citation:
Hsu, Lesli & McElroy, Brandon & Martin, Raleigh & Kim, Wonsuck. (2013). Building a Sediment Experimentalist Network (SEN): sharing best practices for experimental methods and data management. The Sedimentary Record. 11. 9-12. 10.2110/sedred.2013.4.9.
This material is based upon work supported by the National Science Foundation under Grant No. 1324760. Opinions, findings, conclusions or recommendations expressed are those of the authors and do not reflect the views of the NSF.