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Introduction to our research
Shelterland is contributing and benefitting from a number of international R&D projects that focus on enhancing and improving end-user education through virtual experience. What are the key elements that improve the training session and how can this be improved before, during and after a specific training exercise. We are researching topics such as:
Training and Training Systems for Crisis Managers
The challenge of educating crisis personnel is to move from a strategy based on the delivery of training in procedure and process, towards one based on training to diagnose, plan and act in unexpected and difficult situations.
Software Engineering
A key technical aspect for our projects is the controlled exchange of partially sensitive information between components in a complex and heterogeneous distributed system with multiple stakeholders.
Decision Support and Knowledge Management in Crisis Management
A typical set of emergency plans at a major European airport or traffic hub for fire and natural catastrophes may span a number of main documents, cover hundreds of pages, provide information and coordinating instructions for several hundred items, and include 38 maps relating to numerous locations. Searching such huge documents for associated pieces of information to correlate coordinating procedures between different organizations and information needs is extremely effortful and time-consuming, especially in a crisis.
Natural User Interfaces for Crisis Management Training
In work environments such as crisis and emergency management, systems must avoid the use of intrusive technologies in ways that reduce the opportunities for interaction and sharing among co-workers. We research the development of a natural Human-Machine Interface (HMI) that can be deployed in the trainee emergency manager's simulated work environment. The technology replicates the real operational environment by being non-intrusive and causing minimal disruption to work activities.
Dynamic Data Visualization
We advance state-of-the-art dynamic data visualization by developing technology and techniques to deliver interactive and dynamic interaction with multi-formatted, multi-source datasets that enable better sense-making by the detection of the expected and the discovery of the unexpected, in order to discover what we do not know but need to know about a problem space, with data in different modalities.
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