Upload, Configure, Analyze, and Share Geospatial Data in 3 Minutes
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Abstract
Geospatial data is growing rapidly in volumes thanks to the advancement of large observatories, sensor networks, GPS technologies, and personal devices. Such data is crucial in research and education across many disciplines, making great impacts on our daily life. However, it is not an easy task for researchers and end users to explore, analyze, and share geospatial data. Our past experience involved months of development to create a web application by a computer science graduate student to share a climate dataset online via a map interface.
The NSF funded GABBS project (mygeohub/groups/gabbs) is developing building blocks to help non-experts to easily develop tools to meet their geospatial data needs. As part of the GABBS project, we created the GeoBuilder tool using the HUBzero platform and GABBS geospatial building blocks. GeoBuilder guides users in a step-by-step wizard-style interface to load geospatially referenced csv files, configure a data viewer on a map, and explore the data by plotting them dynamically. It also allows a data provider to save a GeoBuilder-generated viewer of his dataset and share with collaborators or the public. In this talk we will describe the design and implementation of the Geobuilder tool and demo how it can be used to share geospatial data with a map interface and plotting functions in less than 3 minutes with no programming required.
Bio
Lan Zhao
Lan Zhao is a research scientist in Rosen Center for Advanced Computing (RCAC) at Purdue University. She has been working on the design and development of data driven cyberinfrastructure systems for multiple cross-disciplinary projects, including GEOSHARE (Geospatial Open Source Hosting of Agriculture, Resource and Environmental Data), WaterHUB, U2U (Useful to Usable), GABBS (Geospatial Modeling and Data Analysis Building Blocks in HUBzero), XSEDE CESM modeling gateway, DRINET (Drought Research Initiative Network), and IsoMAP (Isoscapes Modeling, Analysis and Prediction). Her interests include infrastructure for scientific data storage, retrieval, provenance, and processing, integration and sharing of heterogeneous data sets and models, and composition of data-driven scientific workflows.
Sponsored by
HUBzero Foundation
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