Advanced Science/Event-based Data Service Framework at GES DISC
Friday, 19 December 2014
The NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) has provided numerous Earth science data, information, and services to various research communities and general publics for decades. To maintain an overall fine service including improving serving our users with advanced data services has been our primary goal. We are developing an advanced science/event-based data service framework. The framework aims to effectively provide users with a sophisticatedly integrated data package via user-friendly discovering and selecting a system-preset science/event topic (e.g., hurricane, volcano, etc.) from an in-developing knowledge database of the framework. A data recipe page related to the Hurricane topic has been developed to demo the concept. More showcases of various subjects such as Volcano, Dust Storm, and Forest Fire are also under development. This framework is in developing on top of existing data services at GES DISC, such as Mirador (data search engine), Giovanni (visualization), OPeNDAP, and data recipes. It also involves other data tools, such as Panoply, GrADS, IDL, etc. The Hurricane Sandy (Oct 22-31 2012) event is used here for a sample description. As Hurricane Sandy being selected as a user case, a table containing nine system-preset data variables (i.e., precipitation, winds, sea surface temperature, sea level pressure, air temperature, relative humidity, aerosols, soil moisture and surface runoff, and trace gases) linked to the respective data products with fine temporal and spatial resolutions from various in-house sources is provided. The “bundled” variable data can thus be readily downloaded through Mirador. The in-house Giovanni is accessible for users to acquire quick views of Level 3 (gridded) variables. For Level 2 (swath) or the Giovanni-unavailable Level 3 data, the system provides a link to data recipes that give a how-to guide to read and visualize the data using offline tools, such as Panoply, GrADS, or IDL.