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CFP SMILE 2013 : Social Media and Linked Data for Emergency Response Workshop

From: Eva Blomqvist <evabl444@gmail.com>
Date: Thu, 07 Feb 2013 15:16:42 +0100
Message-ID: <5113B74A.7030504@gmail.com>
To: public-lod@w3.org
* Social Media and Linked Data for Emergency Response Workshop *

Workshop website:

Co-located with the 10th Extended Semantic Web Conference - May 26-30, 
2013 at Montpellier, France

Submission Deadline: March 4, 2013
Acceptance Notification: April 1, 2013
Camera-Ready: April 15, 2013

Emergencies require significant effort in order for emergency workers 
and the general public to respond effectively. Emergency Responders must 
rapidly gather information, determine where to deploy resources and make 
prioritization decisions regarding how best to deal with the emergency. 
Good situation awareness is therefore paramount to ensure a timely and 
effective response. Thus, for an incident to be dealt with effectively, 
citizens and responders must be able to share reliable information and 
help build an understanding of the current local and global situation 
and how this may evolve over time. Information available on Social Media 
is increasingly becoming a fundamental source for Situation Awareness. 
During a crisis, citizens share their own experiences, feelings and 
often, critical local knowledge. Integrating this information with 
Linked Open Data, (such as geographic or demographic data) could greatly 
enrich its value to better prevent and respond to disasters and crisis.

These characteristics make the automation of the intelligence gathering 
task hard, especially when considering that (i) documents must be 
processed in (near) real-time and (ii) the relevant information may be 
in the long-tail of the distribution, i.e. mentioned very infrequently. 
Common techniques for extracting information from text have been applied 
to Social Media content with alternate success. For e.g., Named Entity 
Recognition (NER) techniques that extract semantic concepts have been 
shown to perform poorly on short and noisy social media content. While 
annotation services and APIs are a highly stimulating research direction 
for understanding the content and context of social media streams, the 
aggregation and integration of multi-dimensional datasets, from 
different domains and large volumes of data still pose a significant 
technical challenge to development in this area.

Understanding and acting upon large--scale data of different nature, 
provenance and reliability is a significant knowledge management 
challenge. Decision-support and visualization techniques must be 
developed to enable data exploration and discovery for crisis management 
purposes. Social challenges involved in exploiting social media and 
Linked Open Data for crisis situations include: credibility, 
accountability, trustworthiness, privacy, authenticity and provenance of 

SMILE aims to gather innovative approaches for exploitation of social 
media using semantic web technologies and linked data for emergency 
response and crisis management. The workshop would cover advancements in 
the relevant areas. SMILE aims to bring together expertise from three 
research areas:

- Semantic Web and Linked Data;
- Social Sciences;
- Emergency Response and Crisis Management;

The following topics are of special interest to SMILE:

- Semantic Annotation, for understanding the content and context of 
social media streams
- Integration of Social Media with Linked Data
- Interactive Interfaces and visual analytics methodologies for managing 
multiple large-scale, dynamic, evolving datasets.
- Stream reasoning and event detection
- Social Data Mining
- Collaborative tools and services for Citizens, Organisations, Communities
- Privacy, ethics, trustworthiness and legal issues in the Social 
Semantic Web
- Use case analysis, with specific interest for use cases that involve 
the application of Social Media and Linked Data methodologies in 
real-life scenarios

Applied in the context of:

- Crisis and Disaster Management
- Emergency Response
- Security and Citizen journalism

Full research papers, up to 12 pages
Short papers and position papers, up to 6 pages
Posters and Demonstrations, 4 pages with the description of the 
application and a link to a live online demo (for demonstrations).

More details at http://oak.dcs.shef.ac.uk/?q=smile

- Dr. Vitaveska Lanfranchi, University of Sheffield, UK
- Suvodeep Mazumdar, University of Sheffield, UK
- Dr. Eva Blomqvist, Linköping University, Sweden
- Dr. Christopher Brewster, Aston University, UK

PROGRAMME COMMITTEE (To be completed...)

Neil Ireson, University of Sheffield, United Kingdom
Dr. Sam Chapman, K-Now, United Kingdom
Amparo Elizabeth Cano Basave, KMI, United Kingdom
Dr. Rodrigo Carvalho, K-Now, United Kingdom
Andrea Varga, University of Sheffield, United Kingdom
Dr. Irina Temnikova, University of Wolverhampton, United Kingdom

More details at http://oak.dcs.shef.ac.uk/?q=smile
Received on Thursday, 7 February 2013 18:18:46 UTC

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