Big Data and Analytics for Emergency Management and Public Safety workshop
http://researcher.watson.ibm.com/researcher/view_group.php?id=7160
Hosted by: 2016 IEEE International Conference on Big Data (IEEE Big Data 2016)
http://cci.drexel.edu/bigdata/bigdata2016/
December 5-‐8, 2016, Washington DC, USA Natural disasters, such as wildfires, floods, storms, 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 years1. 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?
1 http://www.worldbank.org/en/topic/disasterriskmanagement/overview
Workshop on Big Data and Analytics for Emergency Management and Public Safety
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Research topics:
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 submissions on related topics are welcome.
o Real time analytics for heterogeneous spatiotemporal big data streams o Unsupervised machine learning for big data o Scalable predictive analytics workflows for big data o Extracting and visualising critical insights from big data o 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. Three members of the Program Committee will review submitted contributions.
Important dates: o Oct 10, 2016: Due date for full workshop papers submission o Nov 1, 2016: Notification of paper acceptance to authors o Nov 15, 2016: Camera-‐ready of accepted papers o Dec 5-‐8, 2016: All workshops (the exact date of this workshop will be
announced on the website)
Submissions: 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. Formatting Instructions DOC: ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.doc PDF: ftp://pubftp.computer.org/press/outgoing/proceedings/instruct8.5x11x2.pdf LaTex: ftp://pubftp.computer.org/Press/Outgoing/proceedings/IEEE_CS_Latex8.5x11x2.zip 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 link Submission link is available on the workshop’s website.
Journal Special Issues: Based on the topic relevance, selected papers will be published in a Special Issue of the International Journal of Risk and Contingency Management, and one Special Issue of the International Journal of Data Warehousing and Mining, in 2017. More information will be provided shortly on the workshop’s website.
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Program Co-‐Chairs:
o Dr Laura Irina Rusu, IBM Research Australia o Gandhi Sivakumar, Watson CoC, Master Inventor, IBM Australia
Program Committee Members:
o Prof Wenny Rahayu, Head of School Engineering and Mathematical Sciences, La Trobe University, Melbourne, Australia
o Prof Matt Duckham, Deputy Head (Geospatial Sciences), RMIT University, Melbourne, Australia
o Dr Michael Rumsewicz, Research Manager, Bushfire and Natural Hazards CRC, Australia
o Dr Anna Phan, IBM Research, Melbourne, Australia o Dr Melanie Roberts, IBM Research, Melbourne, Australia o Dr Mahsa Salehi, IBM Research, Melbourne, Australia o Dr Peter Zhong, Resilient Information Systems for Emergency Response,
Australia o Dr Ziyuan Wang, IBM Research, Melbourne, Australia o Dr Kenneth David Strang, State University of New York, USA
