Please use this link to comment.This contribution was submitted to the National Science Foundation as part of the NSF CI 2030 planning activity through an NSF Request for Information. Consideration of this contribution in NSF's planning process and any NSF-provided public accessibility of this document does not constitute approval of the content by NSF or the US Government. The opinions and views expressed herein are those of the author(s) and do not necessarily reflect those of the NSF or the US Government. The content of this submission is protected by the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.AuthorsWilliams, John W. University of Wisconsin-Madison; Paleoecology, paleoclimatology, biogeography, paleoecoinformaticsGoring, Simon University of Wisconsin-Madison; Paleoecology, geoinformatics, ecologyEmile-Geay, Julien University of Southern California; Paleoclimatology, geoinformatics, data analysisFils, Douglas Consortium for Ocean Leadership; Data ManagementGrimm, Eric University of Minnesota; Paleoecology, informaticsLehnert, Kerstin Columbia University; Geoinformatics, geochemistry, petrologyMcKay, Nicholas Northern Arizona University; Paleoclimatology, geoinformatics, data analysisMyrbo, Amy University of Minnesota; Limnogeology, diversity, geoinformaticsNoren, Anders University of Minnesota; Sedimentology, geoinformaticsPark Boush, Lisa University of Connecticut; Paleobiology, limnogeology, climate change, science communicationPeters, Shanan University of Wisconsin-Madison; Paleobiology, cyberinfrastructure, stratigraphySinger, Brad University of Wisconsin-Madison; GeochronologyUhen, Mark D. George Mason University; Paleontology, paleobiologyAuthorship for this article follows the pattern: Author 1, author 2, and is alphabetical thereafter.
Paleoclimatology is a highly collaborative scientific endeavor, increasingly reliant on online databases for data sharing. Yet, there is currently no universal way to describe, store and share paleoclimate data: in other words, no standard. Data standards are often regarded by scientists as mere technicalities, though they underlie much scientific and technological innovation, as well as facilitating collaborations between research groups. In this article, we propose a preliminary data standard for paleoclimate data, general enough to accommodate all the proxy and measurement types encountered in a large international collaboration (PAGES2K). We also introduce a vehicle for such structured data (Linked Paleo Data, or LiPD), leveraging recent advances in knowledge representations (Linked Open Data). The LiPD framework enables quick querying and extraction, and we expect that it will facilitate the writing of open-source, community codes to access, analyze, model and visualize paleoclimate observations. We welcome community feedback on this standard, and encourage paleoclimatologists to experiment with the format for their own purposes.