Authors: Lan Zhao, Carol Song

An interdisciplinary team of researchers is building the DRINET hub to support regional scale drought information dissemination and synthesis, and sharing of datasets, models and tools in an NSF-funded data interoperability project. The DRINET project engages diverse stakeholders, from hydrologists, agriculture experts, climatologists, to farmers and educators, to collect, publish drought related information and build community acceptance of local and regional data collection/compilation processes and data formats. To-date, many gaps hamper efforts at forecasting droughts and mitigating their impact. This project is fostering increased communication and cross-synthesis of data for diverse applications, and providing a solid basis for study of improved drought risk assessment and trigger indicators. Further, it will serve the purpose of an educational tool, and draw on visualization capabilities to better explain, for example, the role of precipitation and stream flow patterns on droughts.

The DRINET hub is home to researchers, students to publish their own models and tools, datasets, analysis, visualization, training and educational materials for studying droughts. This presentation provides an overview of the datasets, tools and applications that have been built into the DRINET hub to support (1) dynamic data access/analysis using GIS (geographic information system) software; (2) self data publishing and sharing among stakeholders; (3) metadata standardization; (4) tools/applications for drought characterization, prediction and visualization; (5) education and community engagement. Emphasis will be placed on the technologies used to enable quick web application development in the hub environment as well as the integration of GIS and data management capabilities which currently lack native support from the HUBzero software stack. The presenters will also seek developer and end user input on how these components can be improved and shared with the community.

Lan Zhao is a research scientist at Rosen Center for Advanced Computing (RCAC) in Purdue University. 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 using service-oriented technologies.

Researchers should cite this work as follows:

• Lan Zhao; Carol Song (2011), "DRINET Hub for Drought Information Synthesis, Modeling and Applications," https://help.hubzero.org/resources/433.

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