Social Media and Linked Data for Emergency Response (SMILE)
Co-located with the 10th Extended Semantic Web Conference – May 26-30, 2013 at Montpellier, France
1. Keynote talk accepted by Dr. Tomi Kauppinen
Topic: Linking and Visualizing Social Media Data about Crises
Dr Tomi Kauppinen is a postdoctoral researcher in the Department of Media Technology at the Aalto University School of Science in Finland. During 2010-2012 he was a postdoctoral researcher in Germany in the Semantic Interoperability Lab (MUSIL) at the Institute for Geoinformatics at the University of Muenster in Germany. He holds a PhD (2010) from the Aalto University with a thesis on reasoning about change and time, and interacting with the reasoning results. He co-chaired the First and Second International Workshops on Linked Science 2011 and 2012 at the International Semantic Web Conferences, the track on Interoperability and Semantics of the Geoinformatik 2011 conference, and led the breakout session for Vocabularies for Science at Science Online London 2011 organized by Nature. He was also an organizer of the Workshop on GIScience in the Big Data Age 2012 (GIBDA2012). His research focuses on information usability–especially the visualization, linkage and interaction aspects–to support human-computer interaction. Results are for example novel methods for spatiotemporal and semantic modeling of processes such as changes, and the use of gestural movements to interact with the results. The aim is to facilitate human-computer interaction by providing better information retrieval results, better illustrations and visualizations of complex linkages. This supports using and understanding of large spatiotemporal information. His current projects are opening and linking of scientific and educational data in in the the LinkedScience.org- project and in Linked Open Aalto- project, and sharing of information about changes in ObservedChange.com-project.
2. List of accepted papers released
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 information.
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;
 Wong, W. & Blandford, A. (2004) Describing Situation Awareness at an Emergency Medical Dispatch Centre. In Proc. Human Factors and Ergonomics Society’s 48th Annual Meeting. Santa Monica, CA: HFES. 285-289.
 Endsley, Mica R (1995). “Toward a theory of situation awareness in dynamic systems.” Human Factors: The Journal of the Human Factors and Ergonomics Society 37.1 (1995): 32-64.
 Alan Ritter, Sam Clark, Mausam, and Oren Etzioni. 2011. Named entity recognition in tweets: an experimental study. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP ’11). Association for Computational Linguistics, Stroudsburg, PA, USA, 1524- 1534.
To be announced soon …
Axel Schulz, Petar Ristoski and Heiko Paulheim. I See a Car Crash: Real-time Detection of Small Scale Incidents in Microblogs
Robin Keskisärkkä and Eva Blomqvist. Semantic Complex Event Processing for Social Media Monitoring – A Survey
Seyyed Shah and Christopher Brewster. Sierra: Cooperative Request-Response for Resource Management in Disasters using Semantic Web Principles
Suvodeep Mazumdar, Vitaveska Lanfranchi and Amparo E. Cano. Visualising Topical Sentiment and Influence in Social Media
Topics of Interest
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).
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.
March 4, 2013 March 17, 2013
Acceptance Notification: April 1, 2013
Camera-Ready: April 15, 2013
- 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
- Neil Ireson, University of Sheffield, United Kingdom
- Sam Chapman, K-Now, United Kingdom
- Amparo Elizabeth Cano Basave, KMI, United Kingdom
- Rodrigo Carvalho, K-Now, United Kingdom
- Andrea Varga, University of Sheffield, United Kingdom
- Irina Temnikova, University of Wolverhampton, United Kingdom
- Bart van Leeuwen, Netage, Netherlands
- Mikko Rinne, Aalto University, Finland
- Seyyed Shah, Birmingham University, United Kingdom
- Shuangyan Liu, Aston University, United Kingdom
- Sofie Pilemalm, Linköping University, Sweden