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Big EMPS 2016 : Workshop on Big Data and Analytics for Emergency Management and Public Safety

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Link: http://researcher.watson.ibm.com/researcher/view_group.php?id=7160
 
When Dec 5, 2016 - Dec 8, 2016
Where Washington DC
Submission Deadline Oct 10, 2016
Notification Due Nov 1, 2016
Final Version Due Nov 15, 2016
Categories    big data   analytics   machine learning   GIS
 

Call For Papers

Big Data and Analytics for Emergency Management and Public Safety workshop
hosted at IEEE Big Data 2016
http://researcher.watson.ibm.com/researcher/view_group.php?id=7160

Overview:
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Natural disasters, such as wildfire, flood, storm, heat waves, earthquakes, landslides and many others have occurred in ever-increasing numbers in recent years.
Moreover, the World Bank estimates that economic developments, population growth and rapid urbanisation will drive an increase in disaster losses over coming years.

Traditionally, public discourse on emergency management and response has considered such natural disasters as the primary focus, but recent years have shown that fast spreading human diseases (e.g. Ebola), pests or animal diseases (e.g. Hendra virus), telecommunication systems failures, and acts of violence and terrorism have far reaching consequences requiring a similar framework of emergency response. As with natural disasters, such health, infrastructure and security incidents can critically impact communities and jeopardise public safety.

With a current focus on moving from reacting to these events as they happen towards preventing and minimising them, big data and analytics play a critical role in societal ability to plan, prepare and recover from emergency events.

This workshop will be the first at IEEE Big Data conference to address a number of acute questions in Emergency Management and Public Safety, which are of interest and applicable to a worldwide audience, for example:
* How can we make use of massive amounts of data (weather, demographics, urbanism, climate, natural resources etc.) to predict the risk and the possible impact of disasters?
* How can we make use of big open data to better predict disease outbreaks and their impact on communities (health), governments (spending) and economies (losses)?
* What can we learn by analysing big data contributing to past emergency events, to learn and use that knowledge intelligently to build up community resilience to such events?

Research topics:
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Note: the topics proposed below have a focus on big data for emergency management and public safety, for example weather, social networks data, climate, diseases, demographics, however the list is not exhaustive and papers on other related topics are welcome.

- Real time analytics for heterogeneous spatiotemporal big data streams
- Unsupervised machine learning for big data
- Scalable predictive analytics workflows for big data
- Extracting and visualising critical insights from big data
- Uncertainty propagation in connected big data models

Contributions are invited from prospective authors with interests in the indicated session topics and related areas of application. All contributions should be high quality, original and not published elsewhere or submitted for publication during the review period.
Submitted contributions will be reviewed by three members of the PC.

Important dates:
~~~~~~~~~~~~~~~~
Oct 10, 2016: Due date for full workshop papers submission
Nov 1, 2016: Notification of paper acceptance to authors
Nov 15, 2016: Camera-ready of accepted papers
Dec 5-8, 2016: Workshops

Submissions:
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All papers accepted for workshop will be included in the Workshop Proceedings published by the IEEE Computer Society Press, therefore papers should be formatted to 10 pages IEEE Computer Society Proceedings Manuscript Formatting Guidelines.
Although we accept submissions in the form of PDF, PS, and DOC/RTF files, you are strongly encouraged to generate a PDF version for your paper submission if your paper was prepared in Word.

Submission guidelines and link is available on the workshop’s website.

NEW: Journal special issue:
~~~~~~~~~~~~~~~~~~~~~~~~~~
Selected papers will be published in a Special Issue of the International Journal of Data Warehousing and Mining (IJDWM) in 2017. More information will be provided shortly on the workshop’s website.


Organisers:
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Program Co-Chairs:
Dr Laura Irina Rusu, IBM Research Australia
Gandhi Sivakumar, Watson CoC, Master Inventor, IBM Australia

Program Committee Members:
Prof Wenny Rahayu, Head of School Engineering and Mathematical Sciences, La Trobe University, Melbourne, Australia
Prof Matt Duckham, Deputy Head (Geospatial Sciences), RMIT University, Melbourne, Australia
Dr Michael Rumsewicz, Research Manager, Bushfire and Natural Hazards CRC, Australia
Dr Anna Phan, IBM Research, Melbourne, Australia
Dr Melanie Roberts, IBM Research, Melbourne, Australia
Dr Mahsa Salehi, IBM Research, Melbourne, Australia
Dr Peter Zhong, Resilient Information Systems for Emergency Response, Australia
Dr Ziyuan Wang, IBM Research, Melbourne, Australia

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