2012-2017 Special Focus on Information Sharing and Dynamic Data Analysis: Overview

If the 20th Century was dominated by rapid advances in technology, most notably the development and growth of computers, then the 21st will be dominated by the huge growth in data. The ability to instrument, monitor and collect data on every action within society provides huge potential to use this information to improve life: designing better systems (e.g. in healthcare), better managing interactions between large complex systems (e.g. in urban planning and traffic management), identifying subtle problems and bad outcomes (e.g. in homeland security), and more.

Yet while there have been great strides made in building and designing systems which have strong control over their data sources (think of large web-based applications, such as search engines and social networks), systems which need to span multiple, noisy data sources have shown less progress. Consider traffic management in a modern city: there are many complex inputs (historical travel patterns, current and predicted weather activity, maintenance, accident reports, and current observed traffic density). Various controls are possible (adjusting traffic signal timings, blocking or opening lanes, reversible flows etc.), but it remains a hard problem to ensure smooth flow of traffic at peak times. A key stumbling block is provided by the difficulties inherent in bringing together multiple diverse sources of information and using these to correctly draw conclusions and make decisions. Similar examples can be seen in other application areas: identifying disease spread from signals as broad as pharmacy purchases and web search trends; finding potential terrorist plots from a mixture of open and classified sources.

The goal of the Special Focus on Information Sharing and Dynamic Data Analysis is to address the technical problems at the heart of these data challenges. No simple solution or single algorithm can revolutionize this area. Instead, there needs to be protracted effort to understand, model and make progress on these fundamental issues. However, there many embedded technical problems that need to be solved: this is a matter of science, as well as engineering. Our approach is to highlight the key technical problems that need to be solved in this area. This cannot be done in clinical isolation, but requires the participation of practitioners and data users, in addition to scientists and academics. The special focus aims to provide venues for these interactions to occur, and to stimulate further progress via meetings, reports, and identification of open problems. The focus will take place over four years, allowing time for some topics to be visited multiple times as advances are made.

Cross-cutting themes throughout the Special Focus will be:

Opportunities to Participate:

Up. Index of Special Focus on Information Sharing and Dynamic Data Analysis:
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Document last modified on September 9, 2017.