Should Data Frameworks be Inherently Multiscalar? A Use Case of the Living Atlas of the World

Abstract:

In addition to an individual research project, many researchers are involved in at least one major partnership, perhaps one ocean observatory, or one collaborative. The accompanying data framework may be focused on a subdiscipline of oceanography (i.e., marine geology and geophysics, physical oceanography, marine ecology, etc.) or particular study region. The data framework obviously exists to support research, but also collaboration in data collection, spatial analysis, visualization, and communication of the science to multiple audience. These interactions likely take place at multiple scales: the scale of the individual researcher, of small workgroups within a lab, or of inter-organizational collaboration. There are also frameworks that cut horizontally across discipline and region, connecting to broader national or global initiatives such as NSF EarthCube, other NSF-funded Research Coordination Networks, GEOSS, or ODIP. The Living Atlas of the World is presented as a use case of a data framework seeking to cut effectively across multiple spatial and temporal scales. The Living Atlas was first created in 2014 to make authoritative geographic information accessible via hosted cloud services so that users could more quickly address scientific and societal problems and decisions at spatial scales ranging from a small study area the entire globe, while using a range of interactive map functions to tell engaging narratives along the way (aka “story maps”). What began as a way to build trusted, authoritative, and freely available *basemaps* from data contributed online by the GIS community, has grown to a larger program extending far beyond basemap layers to satellite imagery, bathymetry, water column layers, and hydrology, as well elevation, human population, and 3D web scenes. The Living Atlas is continually under construction with new efforts that now extend beyond just the reading and serving of dataset, to the provisioning of spatial analysis on these *data services* in the cloud, as well as the crosswalking and sharing of workflows and use cases, additional apps for mobile, web, and desktop, community-building events where people gather face-to-face, and close interlinkages to other platforms such as ODIP and NSF EarthCube.