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Wednesday, September 26 • 4:20pm - 4:40pm
Experiences in Optimizing Geospatial Data Processing for Isotopic Landscape Modeling

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Over the past decade, stable isotopic landscape modeling has become a promising approach to answering a wide array of questions in multiple disciplines. However, its application has been hindered by the difficulty for individual researchers to collect, compile, and integrate environmental and isotopic data over large spatial and temporal scales and to develop and interpret geostatistical models. To help address these challenges, we developed a science gateway called IsoMAP (http://isomap.org/) which provides an online workspace for spatial analysis, modeling and prediction of stable isotope ratio variation in the natural environment. One of the main challenges in developing the IsoMAP gateway is to efficiently integrate a variety of large scale heterogeneous environmental and isotopic datasets into the isoscapes modeling workflow to ensure real-time query response at the front end as well as timely data update at the back end. In this paper, we will describe how the geospatial data processing workflow was implemented in the initial version of gateway and how it is being optimized by leveraging the built-in geospatial data processing capabilities and the materialized view object of the PostGIS database. Our preliminary evaluation shows that the data update process is significantly improved with greater reliability. The system downtime is reduced from several days to a few hours for each update. Our experience and lessons learned will be applicable to the development of other geospatial data workflows, a common task in the cyberinfrastructure of many science disciplines.

Presenters and Authors
LZ

Lan Zhao

Research Scientist, Purdue University


Wednesday September 26, 2018 4:20pm - 4:40pm CDT
Lil Tex Auditorium, Commons Conference Center 10100 Burnet Road, Bldg 137, Austin, TX 78758

Attendees (4)