Records |
Author |
Melanie Eckle; João Porto de Albuquerque; Benjamin Herfort; Alexander Zipf; Richard Leiner; Rüdiger Wolff; Clemens Jacobs |
Title |
Leveraging OpenStreetMap to Support Flood Risk Management in Municipalities: A Prototype Decision Support System |
Type |
Conference Article |
Year |
2016 |
Publication |
ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2016 |
Volume |
|
Issue |
|
Pages |
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Keywords |
Decision Support Systems; OpenStreetMap; Volunteered Geographic Information; Critical Infrastructure |
Abstract |
Floods are considered the most common and devastating type of disasters world-wide. Therefore, flood management is a crucial task for municipalities- a task that requires dependable information to evaluate risks and to react accordingly in a disaster scenario. Acquiring and maintaining this information using official data however is not always feasible, especially for smaller municipalities. This issue could be approached by integrating the collaborative maps of OpenStreetMap (OSM). The OSM data is openly accessible, adaptable and continuously updated. Nonetheless, to make use of this data for effective decision support, the OSM data must be first adapted to the needs of decision makers. In the pursuit of this goal, this paper presents the OpenFloodRiskMap (OFRM)- a prototype for a OSM based spatial decision-support system. OFRM builds an intuitive and practical interface upon existing OSM data and services to enable decision makers to utilize the open data for emergency planning and response. |
Address |
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Corporate Author |
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Thesis |
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Publisher |
Federal University of Rio de Janeiro |
Place of Publication |
Rio de Janeiro, Brasil |
Editor |
A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3396 |
ISBN |
978-84-608-7984-17 |
Medium |
|
Track |
Intelligent Decision Support in the Networked Society |
Expedition |
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Conference |
13th International Conference on Information Systems for Crisis Response and Management |
Notes |
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Approved |
no |
Call Number |
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Serial |
1335 |
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Author |
Benjamin Herfort; João Porto De Albuquerque; Svend-Jonas Schelhorn; Alexander Zipf |
Title |
Does the spatiotemporal distribution of tweets match the spatiotemporal distribution of flood phenomena? A study about the River Elbe Flood in June 2013 |
Type |
Conference Article |
Year |
2014 |
Publication |
ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2014 |
Volume |
|
Issue |
|
Pages |
747-751 |
Keywords |
Catchments; Data mining; Information systems; Social networking (online); Spatial distribution; Water levels; Crisis management; Digital elevation model; Geographical features; Situational awareness; Social media; Social media platforms; Spatiotemporal distributions; Twitter; Floods |
Abstract |
In this paper we present a new approach to enhance information extraction from social media that relies upon the geographical relations between twitter data and flood phenomena. We use specific geographical features like hydrological data and digital elevation models to analyze the spatiotemporal distribution of georeferenced twitter messages. This approach is applied to examine the River Elbe Flood in Germany in June 2013. Although recent research has shown that social media platforms like Twitter can be complementary information sources for achieving situation awareness, previous work is mostly concentrated on the classification and analysis of tweets without resorting to existing data related to the disaster, e.g. catchment borders or sensor data about river levels. Our results show that our approach based on geographical relations can help to manage the high volume and velocity of social media messages and thus can be valuable for both crisis response and preventive flood monitoring. |
Address |
GIScience Department, Heidelberg University, Germany; Dept. of Computer Systems/ICMC, University of Sao Paulo, Brazil |
Corporate Author |
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Thesis |
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Publisher |
The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780692211946 |
Medium |
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Track |
Social Media in Crisis Response and Management |
Expedition |
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Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
Notes |
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Approved |
no |
Call Number |
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Serial |
572 |
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Author |
Svend-Jonas Schelhorn; Benjamin Herfort; Richard Leiner; Alexander Zipf; João Porto De Albuquerque |
Title |
Identifying elements at risk from OpenStreetMap: The case of flooding |
Type |
Conference Article |
Year |
2014 |
Publication |
ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2014 |
Volume |
|
Issue |
|
Pages |
508-512 |
Keywords |
Hazards; Information systems; Risk assessment; Risk management; Elements at risks; OpenStreetMap; Osm; Vgi; Volunteered geographic information; Floods |
Abstract |
The identification of elements at risk is an essential part in hazard risk assessment. Especially for recurring natural hazards like floods, an updated database with information about elements exposed to such hazards is fundamental to support crisis preparedness and response activities. However, acquiring and maintaining an up-to-date database with elements at risk requires both detailed local and hazard-specific knowledge, being often a challenge for local communities and risk management bodies. We present a new approach for leveraging Volunteered Geographic Information to identify elements at risk from the free and open-source mapping project OpenStreetMap. We present initial results from a case study in the city of Cologne, Germany, to validate our approach in the case of flood-hazard. Our results show that the identification of elements at flood risk from OpenStreetMap is a suitable and cost-effective alternative for supporting local governments and communities in risk assessment and emergency planning. |
Address |
GIScience Department, Heidelberg University, Germany; Leiner and Wolff GmbH, Germany; Dept. of Computer Systems, Univ. of Sao Paulo, Brazil |
Corporate Author |
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Thesis |
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Publisher |
The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780692211946 |
Medium |
|
Track |
Planning, Foresight and Risk Analysis |
Expedition |
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Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
Notes |
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Approved |
no |
Call Number |
|
Serial |
920 |
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Author |
Benjamin Herfort; Melanie Eckle; João Porto de Albuquerque; Alexander Zipf |
Title |
Towards assessing the quality of volunteered geographic information from OpenStreetMap for identifying critical infrastructures |
Type |
Conference Article |
Year |
2015 |
Publication |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2015 |
Volume |
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Issue |
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Pages |
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Keywords |
Critical Infrastructure; Disaster Management; Emergency planning; OpenStreetMap; Volunteered Geographic |
Abstract |
Identifying the assets of a community that are part of its Critical Infrastructure (CI) is a crucial task in emergency planning. However, this task can prove very challenging due to the costs involved in defining the methodology and gathering the necessary data. Volunteered Geographic Information from collaborative maps such as OpenStreetMap (OSM) may be able to make a contribution in this context, since it contains valuable local knowledge. However, research is still due to assess the quality of OSM for the particular purpose of identifying critical assets. To fill this gap, this paper proposes a catalogue of critical asset types, based on the analysis of different reference frameworks. We thus analyze how good the emergent OSM data model is for representing these asset types, by verifying whether they can be mapped to tags used by the OSM community. Results show that critical asset types of all selected sectors and branches are well represented in OSM. |
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Corporate Author |
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Thesis |
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Publisher |
University of Agder (UiA) |
Place of Publication |
Kristiansand, Norway |
Editor |
L. Palen; M. Buscher; T. Comes; A. Hughes |
Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9788271177881 |
Medium |
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Track |
Planning, Foresight and Risk Analysis |
Expedition |
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Conference |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
Notes |
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Approved |
yes |
Call Number |
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Serial |
1313 |
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Author |
Johannes Anhorn; Benjamin Herfort; João Porto de Albuquerque |
Title |
Crowdsourced Validation and Updating of Dynamic Features in OpenStreetMap – An analysis of Shelter Mapping after the 2015 Nepal Earthquake |
Type |
Conference Article |
Year |
2016 |
Publication |
ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2016 |
Volume |
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Issue |
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Pages |
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Keywords |
OpenStreetMap; Validation; Disaster Shelter; Nepal Earthquake; Crowdsourcing |
Abstract |
The paper presents results from a validation process of OpenStreetMap (OSM) rapid mapping activities using crowdsourcing technology in the aftermath of the Gorkha earthquake 2015 in Nepal. We present a framework and tool to iteratively validate and update OSM objects. Two main objectives are addressed: first, analyzing the accuracy of the volunteered geographic information (VGI) generated by the OSM community; second, investigating the spatio-temporal dynamics of spontaneous shelter camps in Kathmandu. Results from three independent validation iterations show that only 10 % of the OSM objects are false positives (no shelter camps). Unexpectedly, previous mapping experience only had a minor influence on mapping accuracy. The results further show that it is critical to monitor the temporal dynamics. Out of 4,893 identified shelter camps, 54% were already empty/closed six days after the first mapping. So far, updating geographical features during humanitarian crisis is not properly addressed by the existing crowdsourcing approaches. |
Address |
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Corporate Author |
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Thesis |
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Publisher |
Federal University of Rio de Janeiro |
Place of Publication |
Rio de Janeiro, Brasil |
Editor |
A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3432 |
ISBN |
978-84-608-7984-53 |
Medium |
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Track |
Geospatial Data and Geographical Information Science |
Expedition |
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Conference |
13th International Conference on Information Systems for Crisis Response and Management |
Notes |
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Approved |
no |
Call Number |
|
Serial |
1372 |
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Author |
Benjamin Herfort; Melanie Eckle; João Porto de Albuquerque |
Title |
Being Specific about Geographic Information Crowdsourcing: A Typology and Analysis of the Missing Maps Project in South Kivu |
Type |
Conference Article |
Year |
2016 |
Publication |
ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2016 |
Volume |
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Issue |
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Pages |
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Keywords |
Crowdsourcing; Classification; Digitization; Conflation; OpenStreetMap |
Abstract |
Recent development in disaster management and humanitarian aid is shaped by the rise of new information sources such as social media or volunteered geographic information. As these show great potential, making sense out of the new geographical datasets is a field of important scientific research. Therefore, this paper attempts to develop a typology of geographical information crowdsourcing. Furthermore, we use this typology to frame existing crowdsourcing projects and to further point out the potential of different kinds of crowdsourcing for disaster management and humanitarian aid. In order to exemplify its practical usage and value, we apply the typology to analyze the crowdsourcing methods utilized by the members of the Missing Maps project developed in South Kivu. |
Address |
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Corporate Author |
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Thesis |
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Publisher |
Federal University of Rio de Janeiro |
Place of Publication |
Rio de Janeiro, Brasil |
Editor |
A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3438 |
ISBN |
978-84-608-7984-59 |
Medium |
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Track |
Geospatial Data and Geographical Information Science |
Expedition |
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Conference |
13th International Conference on Information Systems for Crisis Response and Management |
Notes |
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Approved |
no |
Call Number |
|
Serial |
1378 |
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Author |
Melanie Eckle; Benjamin Herfort; Yingwei Yan; Chiao-Ling Kuo; Alexander Zipf |
Title |
Towards using Volunteered Geographic Information to monitor post-disaster recovery in tourist destinations |
Type |
Conference Article |
Year |
2017 |
Publication |
Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management |
Abbreviated Journal |
Iscram 2017 |
Volume |
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Issue |
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Pages |
1008-1019 |
Keywords |
OpenStreetMap; Flickr; Disaster; Recovery; Tourism |
Abstract |
The aftereffects of disaster events are significant in tourist destinations where they do not only lead to destruction and casualties, but also long-lasting economic harms. The public perception causes tourists to refrain from visiting these areas and recovery of the tourist industry, a major economic sector, to become challenging. To improve this situation, current information about the tourist and infrastructure recovery is crucial for a “rebranding”- information that is however time and cost-intensive in acquisition using traditional information sources. An alternative data source that has shown great potential for information gathering in other disaster management phases, which was less considered for disaster recovery purposes, is Volunteered Geographic Information (VGI). Therefore, this paper introduces a VGI-based methodology to address this task. Initial analyses conducted with Flickr data indicate a potential of VGI for recovery monitoring, whereas the analysis of OpenStreetMap data shows, that this form of VGI requires further quality assurance. |
Address |
GIScience Chair, Heidelberg University, Germany |
Corporate Author |
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Thesis |
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Publisher |
Iscram |
Place of Publication |
Albi, France |
Editor |
Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds |
Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
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Medium |
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Track |
Response and Recovery |
Expedition |
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Conference |
14th International Conference on Information Systems for Crisis Response And Management |
Notes |
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Approved |
no |
Call Number |
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Serial |
2084 |
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