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Paper No. 216-1
Presentation Time: 1:30 PM
A VISION FOR MOBILE GEOSCIENCE IN OUTREACH, RESEARCH, AND CITIZEN SCIENCE, USING FLYOVER COUNTRY (Invited Presentation)
The NSF-funded Flyover Country mobile app for geoscience (FC) is evolving in several directions: as an outreach instrument, a research tool, and a hook for citizen science. Each facet offers opportunities for implementation of novel approaches in exposure and visualization of the fruits of many decades of geoscientific study, as well as for engagement of the app’s user community. FC for outreach and informal education enlists the wonder of the landscape as viewed from an airplane, car window, or hiking vista to inspire and immediately satisfy curiosity about the natural world. FC for research will offer the field scientist a wealth of analytical data (geochemistry, chronology, floral and faunal assemblages, etc.) in geospatial context, visualization of complex datasets, and collaboration recommendations using ORCIDs. FC for citizen science will reward data submitters by visualizing their data in near real time on a map alongside “professionally collected” geoscience data, and will motivate members of the public (including K-12 and undergraduate students) to collect data using NASA/NSF GLOBE protocols by issuing a “mission” or “call to action” when their proposed FC ground travel path crosses an area with poor spatial coverage for a given parameter. The rapid deployment of APIs, the growing interconnectivity and transparency of well-curated databases or domain repositories, and the active community collaboration fostered largely by the NSF EarthCube and Geoinformatics initiatives, make these activities feasible. The next step in increasing accessibility and understanding of the geosciences may be translation of the vast amount of extant high-quality place-based geoscience writing (e.g., field trip guides): not just semiautomated translation into multiple languages, but also semiautomated text leveling for readers of nonexpert background. Both types of translation could use ontologies and natural language processing to handle jargon.