Improving Discoverability of Geophysical Data using Location Based Services

Friday, 19 December 2014
Daniel Morrison1, Robin J Barnes2, Matthew Potter3, Stuart R Nylund2, Dennis Patrone3, Michele Weiss2, Elsayed R Talaat4, Theodore E Sarris5 and Daniel Smith3, (1)Applied Physics Laboratory Johns Hopkins, Space, Laurel, MD, United States, (2)JHU/APL, Laurel, MD, United States, (3)Applied Physics Laboratory Johns Hopkins, Laurel, MD, United States, (4)NASA Headquarters, Washington, DC, United States, (5)Demokritus University of Thrace, Xanthi, Greece
The great promise of Virtual Observatories is the ability to perform complex search operations across the metadata of a large variety of different data sets. This allows the researcher to isolate and select the relevant measurements for their topic of study.

The Virtual ITM Observatory (VITMO) has many diverse geophysical datasets that cover a large temporal and spatial range that present a unique search problem. VITMO provides many methods by which the user can search for and select data of interest including restricting selections based on geophysical conditions (solar wind speed, Kp, etc) as well as finding those datasets that overlap in time. One of the key challenges in improving discoverability is the ability to identify portions of datasets that overlap in time and in location. The difficulty is that location data is not contained in the metadata for datasets produced by satellites and would be extremely large in volume if it were available, making searching for overlapping data very time consuming.

To solve this problem we have developed a series of light-weight web services that can provide a new data search capability for VITMO and others. The services consist of a database of spacecraft ephemerides and instrument fields of view; an overlap calculator to find times when the fields of view of different instruments intersect; and a magnetic field line tracing service that maps in situ and ground based measurements to the equatorial plane in magnetic coordinates for a number of field models and geophysical conditions.

These services run in real-time when the user queries for data. They will allow the non-specialist user to select data that they were previously unable to locate, opening up analysis opportunities beyond the instrument teams and specialists, making it easier for future students who come into the field.