New seismological data mining methods are enabling discoveries and cross-disciplinary research across Earth system science. Research is challenged by the relatively short time period of observation for which digital records are readily available. Historical data recorded on paper and other physical media when suitably converted into machine readable formats, extends the time period of Earth observation and research back many decades. For legacy seismic data to be made available to support Earth system science, compelling challenges must be addressed in handling, preserving, and creating and maintaining archives of digital renderings of this "dark" data. 

This workshop seeks to bring together stakeholders across organizations and scientific domains to discuss the science drivers and challenges facing community use of legacy seismic data. We actively encourage participation among users and maintainers of these data collections as well as experts in their usage and potential applications. We welcome contributions as they pertain to NSF 10 Big Ideas including climate change research, machine learning, and big data analytics. This workshop will clearly identify the scientific importance of securing these data as well as provide a clear statement and prioritization of community needs and interests.

CONFIRMED SPEAKERS

Ana Aguiar, LLNL
Tim Ahern, IRIS emeritus
Andrew Bartlett, Retriever Technology
Daniel Burk, Michigan State U.
Josep Batlo, ICGC
James Dewey, USGS
Diane Doser, UT El Paso
Rebecca Koskela, DataONE
Alberto Michelini, INGV
Gabriele Morra, UL Lafyette
Meredith Nettles, Lamont-Doherty Earth Observatory
Emile Okal, Northwestern University
Paul Richards, Lamont-Doherty Earth Observatory
Kaiwen Wang, Stanford Univeristy
Brian Young, Sandia National Laboratory