<html><body><div style="color:#000; background-color:#fff; font-family:times new roman, new york, times, serif;font-size:12pt"><div><div><div>*Apologies for multiple postings*<br></div><div><br></div><div>Call for Papers</div><div><span class="Apple-style-span">**Social Media and Linked Data for Emergency Response (SMILE) Workshop co-located</span> with ESWC 2013</div><div>**26-30 May, Montpellier, France**</div><div><span class="Apple-style-span" style="color: rgb(73, 73, 73); font-family: Verdana, sans-serif; font-size: 12px; line-height: 18px; "><h4 style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px; padding-top: 0px; padding-right: 0px; padding-bottom: 0px; padding-left: 0px; font-weight: normal; font-family: Helvetica, Arial, sans-serif; font-size: 16px; "><br></h4></span></div><div>SMILE 2013 http://oak.dcs.shef.ac.uk/?q=smile</div><div><br></div><div>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.</div><div><br></div><div>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.</div><div><br></div><div>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 information.</div><div><br></div><div>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. </div><div><br></div><div style="color: rgb(0, 0, 0); font-size: 16px; font-family: 'times new roman', 'new york', times, serif; background-color: transparent; font-style: normal; ">SMILE aims to bring together expertise from three research
areas:</div><div><br></div><div>-Semantic Web and Linked Data;</div><div>-Social Sciences;</div><div>-Emergency Response and Crisis Management;</div><div><br></div><div><br></div><div>Important dates:</div><div><br></div><div>*Submission deadline: March 4, 2013*</div><div>Acceptance notification: April 1, 2013</div><div>Camera-ready deadline: April 15, 2013</div><div><br></div><div>Submissions:</div><div><br></div><div>Full research papers, up to 12 pages</div><div>Short papers and position papers, up to 6 pages</div><div>Posters and Demonstrations, 4 pages with the description of the application and a link to a live online demo (for demonstrations).</div><div><br></div><div>Paper submissions will have to be formatted in the style of Springer Publications format for Lecture Notes in Computer Science (LNCS). Submissions will be made using EasyChair Conference Systems, and the proceedings of the papers will be provided by
CEUR-WS.</div><div><br></div><div>Organising Committee</div><div><br></div><div>Dr. Vitaveska Lanfranchi, University of Sheffield, UK</div><div>Suvodeep Mazumdar, University of Sheffield, UK</div><div>Dr. Eva Blomqvist, Linköping University, Sweden</div><div>Dr. Christopher Brewster, Aston University, UK</div><div><br></div><div>More Information:</div><div><br></div><div>SMILE 2013 http://oak.dcs.shef.ac.uk/?q=smile</div></div></div></div></body></html>