Reference Data Layers for Earth and Environmental Science: History, Frameworks, Science Needs, Approaches, and New Technologies

Abstract:

Global Mapping Project, Web-enabled Landsat Data (WELD), International Satellite Land Surface Climatology Project (ISLSCP), hydrology, solid earth dynamics, sedimentary geology, climate modeling, integrated assessments and so on all have needs for or have worked to develop consistently integrated data layers for Earth and environmental science. This paper will present an overview of an abstract notion of data layers of this types, what we are referring to as reference data layers for Earth and environmental science, highlight some historical examples, and delve into new approaches. The concept of reference data layers in this context combines data availability, cyberinfrastructure and data science, as well as domain science drivers. We argue that current advances in cyberinfrastructure such as iPython notebooks and integrated science processing environments such as iPlant’s Discovery Environment coupled with vast arrays of new data sources warrant another look at the how to create, maintain, and provide reference data layers. The goal is to provide a context for understanding science needs for reference data layers to conduct their research. In addition, to the topics described above this presentation will also outline some of the challenges to and present some ideas for new approaches to addressing these needs. Promoting the idea of reference data layers is relevant to a number of existing related activities such as EarthCube, RDA, ESIP, the nascent NSF Regional Big Data Innovation Hubs and others.