CIC-DM 2016 International Workshop on Collaborative Internet Computing for Disaster Management

Call For Papers

The ability to collect, analyze, and integrate data from large number of diverse data sources has offered unprecedented opportunities to study human behaviors and their relationship to various types of systems and services. Mobile phone data and the content generated by hundreds of millions of users on social media such as Twitter, or Facebook, present continuous data streams of human social activities, and offer a unique chance to understand the structure and dynamics of social and information behavior in various situations. The goal of this workshop is to bring together researchers and practitioners working in the related areas of big data, internet computing and crisis information management to meet the growing challenges in efficient disaster management. We aim to foster a productive collaboration between computer/information scientists, public policy and urban planners, government officials, and other interested participants to discuss issues and challenges related to disaster management. This includes theoretical, methodological, ethical, and political questions in regard to the study of large-scale emergency related data and intelligent systems. A particular objective of the CIC-DM'16 is to bridge the gap between the methods of scalable data management, data mining, and the smart applications to improve emergency responses. We aim to provide a platform for the exchange of ideas, identification of important and challenging problems, and discovery of possible synergies. Our hope is that this workshop will spur vigorous discussions and encourage collaboration between the various disciplines resulting in joint projects and grant submissions.

Topics of interest

Data analytics
Data management
Human/social computing
Emergent research issues

• Extracting emergency events from big data
• Measurement of relevance and user activities through emergency information retrieval in social streams
• Identifying misinformation during emergencies and crisis events
• Evaluation framework for the emergency mining algorithms
• Scalable or real-time architecture for large-scale emergency information processing, mining and visualization
• Emergency social and information structure pattern discovery and predictive modeling
• Social network analysis and spatiotemporal analysis for crisis management
• Collective sense-making in crisis events
• Scalable collaborative graph data processing and streaming data processing for rare events
• Human computer interfaces for emergency data mining and crowdsourcing
• Visual analytics for crisis informatics
• Large-scale collective intelligence for emergency data integration and data fusion; fusion of social communication features, metadata, user generated content, and social context within the emergency situations
• Large-scale process monitoring for handling high data rates during emergencies
• Security and privacy management for emergency information processing
• Collaborative Big Data storage and management in the cloud for emergency management
• Collaborative Big Data reliability assessment for crisis informatics
• Challenges for collaboration in Big Data emergency management and data utilization
• New technologies (e.g., mobile applications) for mining and deploying emergency information
• Probabilistic computing in disasters
• Reinforcement learning for autonomous systems
• Any-time algorithms for large-scale in-situ reinforcement learning
• Deep learning for complex and fast evolving decision scenarios
• Resilient machine learning for planning & coordination in hostile environments

IMPORTANT DATES

Paper submission: August 29, 2016

                       

Notification of acceptance: September 16, 2016

           

Final manuscripts due: October 20, 2016