TY  - JOUR
A1  - Wiegmann, Matti
A1  - Kersten, Jens
A1  - Senaratne, Hansi
A1  - Potthast, Martin
A1  - Klan, Friederike
A1  - Stein, Benno
T1  - Opportunities and risks of disaster data from social media: a systematic review of incident information
JF  - Natural Hazards and Earth System Sciences
N2  - Compiling and disseminating information about incidents and disasters are key to disaster management and relief. But due to inherent limitations of the acquisition process, the required information is often incomplete or missing altogether. To fill these gaps, citizen observations spread through social media are widely considered to be a promising source of relevant information, and many studies propose new methods to tap this resource. Yet, the overarching question of whether and under which circumstances social media can supply relevant information (both qualitatively and quantitatively) still remains unanswered. To shed some light on this question, we review 37 disaster and incident databases covering 27 incident types, compile a unified overview of the contained data and their collection processes, and identify the missing or incomplete information. The resulting data collection reveals six major use cases for social media analysis in incident data collection: (1) impact assessment and verification of model predictions, (2) narrative generation, (3) recruiting citizen volunteers, (4) supporting weakly institutionalized areas, (5) narrowing surveillance areas, and (6) reporting triggers for periodical surveillance. Furthermore, we discuss the benefits and shortcomings of using social media data for closing information gaps related to incidents and disasters.
KW  - Katastrophe
KW  - Social Media
KW  - Datenbank
KW  - Information
KW  - Katastrophenmanagement
KW  - Soziale Medien
KW  - Datensammlung
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210804-44634
UR  - https://nhess.copernicus.org/articles/21/1431/2021/nhess-21-1431-2021.html
VL  - 2021
IS  - Volume 21, Issue 5
SP  - 1431
EP  - 1444
PB  - European Geophysical Society
CY  - Katlenburg-Lindau
ER  - 
TY  - JOUR
A1  - Aziz, Zeeshan
A1  - Anumba, Chimay
A1  - Miles, John
T1  - Towards a Semantic Grid Computing Platform for Disaster Management in Built Environment
N2  - Current disaster management procedures rely primarily on heuristics which result in their strategies being very cautious and sub-optimum in terms of saving life, minimising damage and returning the building to its normal function. Also effective disaster management demands decentralized, dynamic, flexible, short term and across domain resource sharing, which is not well supported by existing distributing computing infrastructres. The paper proposes a conceptual framework for emergency management in the built environment, using Semantic Grid as an integrating platform for different technologies. The framework supports a distributed network of specialists in built environment, including structural engineers, building technologists, decision analysts etc. It brings together the necessary technology threads, including the Semantic Web (to provide a framework for shared definitions of terms, resources and relationships), Web Services (to provide dynamic discovery and integration) and Grid Computing (for enhanced computational power, high speed access, collaboration and security control) to support rapid formation of virtual teams for disaster management. The proposed framework also make an extensive use of modelling and simulation (both numerical and using visualisations), data mining (to find resources in legacy data sets) and visualisation. It also include a variety of hardware instruments with access to real time data. Furthermore the whole framework is centred on collaborative working by the virtual team. Although focus of this paper is on disaster management, many aspects of the discussed Grid and Visualisation technologies will be useful for any other forms of collaboration. Conclusions are drawn about the possible future impact on the built environment.
KW  - Mehragentensystem
KW  - Lernendes System
KW  - Katastrophenmanagement
KW  - Software
Y1  - 2004
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20111215-2084
ER  -