Event-Driven Technology to Generate Relevant Collections of Near-Realtime Data
Abstract
Getting the right data when it is needed continues to be a challenge for researchers and decision makers. Event-Driven Data Delivery (ED3), funded by the NASA Applied Science program, is a technology that allows researchers and decision makers to pre-plan what data, information and processes they need to have collected or executed in response to future events. The Information Technology and Systems Center at the University of Alabama in Huntsville (UAH) has developed the ED3 framework in collaboration with atmospheric scientists at UAH, scientists at the Geological Survey of Alabama, and other federal, state and local stakeholders to meet the data preparedness needs for research, decisions and situational awareness. The ED3 framework supports an API that supports the addition of loosely-coupled, distributed event handlers and data processes. This approach allows the easy addition of new events and data processes so the system can scale to support virtually any type of event or data process. Using ED3's underlying services, applications have been developed that monitor for alerts of registered event types and automatically triggers subscriptions that match new events, providing users with a living "album" of results that can continued to be curated as more information for an event becomes available. This capability can allow users to improve capacity for the collection, creation and use of data and real-time processes (data access, model execution, product generation, sensor tasking, social media filtering, etc), in response to disaster (and other) events by preparing in advance for data and information needs for future events. This presentation will provide an update on the ED3 developments and deployments, and further explain the applicability for utilizing near-realtime data in hazards research, response and situational awareness.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFMIN31C0095G
- Keywords:
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- 3360 Remote sensing;
- ATMOSPHERIC PROCESSES;
- 4337 Remote sensing and disasters;
- NATURAL HAZARDS;
- 4262 Ocean observing systems;
- OCEANOGRAPHY: GENERAL;
- 7924 Forecasting;
- SPACE WEATHER