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DI-DAP: An Efficient Disaster Information Delivery and Analysis Platform in Disaster Management

Published: 24 October 2016 Publication History

Abstract

In disaster management, people are interested in the development and the evolution of the disasters. If they intend to track the information of the disaster, they will be overwhelmed by the large number of disaster-related documents, microblogs, and news, etc. To support disaster management and minimize the loss during the disaster, it is necessary to efficiently and effectively collect, deliver, summarize, and analyze the disaster information, letting people in affected area quickly gain an overview of the disaster situation and improve their situational awareness.
To present an integrated solution to address the information explosion problem during the disaster period, we designed and implemented DI-DAP, an efficient and effective disaster information delivery and analysis platform. DI-DAP is an information centric information platform aiming to provide convenient, interactive, and timely disaster information to the users in need. It is composed of three separated but complementary services: Disaster Vertical Search Engine, Disaster Storyline Generation, and Geo-Spatial Data Analysis Portal. These services provide a specific set of functionalities to enable users to consume highly summarized information and allow them to conduct ad-hoc geospatial information retrieval tasks. To support these services, DI-DAP adopts FIU-Miner, a fast, integrated, and user-friendly data analysis platform, which encapsulated all the computation and analysis workflow as well-defined tasks. Moreover, to enable ad-hoc geospatial information retrieval, an advanced query language MapQL is used and the query template engine is integrated.
DI-DAP is designed and implemented as a disaster management tool and is currently been exercised as the disaster information platform by more than 100 companies and institutions in South Florida area.

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  • (2019)Implementation and evaluation of a visualization and analysis system for historical disaster recordsJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-019-01548-zOnline publication date: 19-Oct-2019
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cover image ACM Conferences
CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management
October 2016
2566 pages
ISBN:9781450340731
DOI:10.1145/2983323
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 24 October 2016

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Author Tags

  1. disaster management
  2. sequential query pattern
  3. storyline generation
  4. vertical search engine

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CIKM'16
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CIKM'16: ACM Conference on Information and Knowledge Management
October 24 - 28, 2016
Indiana, Indianapolis, USA

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CIKM '16 Paper Acceptance Rate 160 of 701 submissions, 23%;
Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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View all
  • (2024)An Integrated Framework for Real-Time Disaster Data Acquisition, Processing, and Resource Optimization in Crisis Management Systems2024 4th International Conference on Ubiquitous Computing and Intelligent Information Systems (ICUIS)10.1109/ICUIS64676.2024.10867241(924-931)Online publication date: 12-Dec-2024
  • (2020)Applications of artificial intelligence for disaster managementNatural Hazards10.1007/s11069-020-04124-3103:3(2631-2689)Online publication date: 3-Jul-2020
  • (2019)Implementation and evaluation of a visualization and analysis system for historical disaster recordsJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-019-01548-zOnline publication date: 19-Oct-2019
  • (2017)Data-Driven Techniques in Disaster Information ManagementACM Computing Surveys10.1145/301767850:1(1-45)Online publication date: 10-Mar-2017
  • (2017)ICN Based Disaster Area Network PlatformAdvances in Computer Science and Ubiquitous Computing10.1007/978-981-10-7605-3_207(1301-1306)Online publication date: 20-Dec-2017

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