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Crisis response situations require collaboration across many different organizations with different backgrounds, training, procedures and objectives. The response to the Indian Ocean Tsunami in 2004 and the Hurricane Katrina relief efforts in 2005 emphasized the importance of effective communication and collaboration. Compounding the challenges associated with collaboration during crisis situations is the distributed nature of the supporting organizations and the lack of a designated leader recognized across military, government and non-government organizations. The US Army Research Laboratory is working with the University of Edinburgh, the University of Virginia, Perigean Technologies and Carnegie Mellon University in the creation of an openly accessible “Virtual Collaborative Environment” (VCE) to support the “Whole of Society Crisis Response” (WoSCR) community of interest and crisis action planning activities. The VCE consist of a collaborative portal containing a suite of Web 2.0 social networking and group tools including data visualization facilities, a 3D virtual collaboration space and a collaboration protocol. All tools were selected to support the key functions identified in a cognitive work analysis (CWA) for distributed collaboration and chosen to be open source or as accessible as possible to allow them to be made available to the wide range of organizations that make up the crisis response community.

In this work a machine vision system capable of analysing underwater videos for detecting, tracking and counting fish is presented. The real-time videos, collected near the Ken-Ding sub-tropical coral reef waters are managed by EcoGrid, Taiwan and are barely analysed by marine biologists. The video processing system consists of three subsystems: the video texture analysis, fish detection and tracking modules. Fish detection is based on two algorithms computed independently, whose results are combined in order to obtain a more accurate outcome. The tracking was carried out by the application of the CamShift algorithm that enables the tracking of objects whose numbers may vary over time. Unlike existing fish-counting methods, our approach provides a reliable method in which the fish number is computed in unconstrained environments and under several scenarios (murky water, algae on camera lens, moving plants, low contrast, etc.). The proposed approach was tested with 20 underwater videos, achieving an overall accuracy as high as 85%.

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties. In the last decades, many advances have been made in intelligent planning systems. Significant improvements related to core problems, providing faster search algorithms and shortest plans have been proposed. However, there is a lack in researches allowing a better support for a proper use and interaction with planners, where, for instance, visualization can play an important role. This work proposes a general framework for visualisation of planning information using an approach based on semantic modelling. It intends to enhance the notion of knowledge-based planning applying it to other aspects of planning, such as visualisation. The approach consists in an integrated ontology set and reasoning mechanism for multi-modality visualisation destined to collaborative planning environments. This framework will permit organizing and modelling the domain from the visualisation perspective, and give a tailored support for presentation of information.

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the authorâ s and shouldnâ t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties. Real-time automatic and continuous information gathering through EcoGrid offers an unique and immense opportunity for long term ecological monitoring and planning. However, the vast amount of raw data gathered must be dealt with efficiently and effectively so that they may be timely turned into useable information to assist ecological management. In addition, Ecological data tends to subject to environmental changes and exception-prone so that their qualities vary. Adaptive business process modelling (BPM) techniques provide rich conceptualisation to support workflow systems to perform integrated analytical and documentation tasks flexibly and efficiently. We present one such BPM and show how adaptive workflow systems, like those developed at AIAI, can take advantage of Enterprise Models represented in FBPML to provide effective support to users in real Grid environments.

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties. We describe a collaborative problem solving architecture driven by semantic based workflow orchestration and constraint solving. These technologies are based on shared ontologies that allow two systems of very different natures to communicate, perform specialised tasks and achieve common goals. We give an account of our approach for the workflow assisted collaboration with a specialised knowledge agent. In this case, a system with constraint solving capabilities. We found that systems built with Semantic Web based technologies are useful for collaboration and are easier to add additional specialised capabilities. However, much care must be exercised before correct semantics may be exchanged and collaborations occur smoothly.

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties. This paper describes our efforts to provide a collaborative problem solving architecture driven by semantic-based workflow orchestration and constraint problem solving. These technologies are based on shared ontologies that allows two systems of very different natures to communicate, perform specialised tasks and achieve common goals. We give an account of our approach for the workflow assisted collaboration with constraint solving capabilities. We found that systems built with semantic (web) based technologies is useful for collaboration and flexible to enhance the system with specialised capabilities. However, much care must be exercised before correct semantics may be exchanged and collaborations occur smoothly.

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties. To achieve more widespread application, Workflow Management Systems (WfMS) need to be developed to operate in dynamic environments where they are expected to ensure that users are supported in performing flexible and creative tasks while maintaining organisational norms [Alonso et al, 1997; Sheth & Kochut, 1997]. In order to cope with these demands, the systems must provide knowledge about the business process itself and the organisational context in that these processes operate [Jarvis et al, 1999]. It, however, is not an easy task to provide the appropriate and sufficient knowledge at the right level of abstraction that supports a workflow system at all stages of operation in a dynamic environment and for different types of users. At the same time, Enterprise Modelling (EM) methods are well recognised for their value in describing complex domains in an organised but usually informal structure. In particular, business process modelling techniques provide rich conceptualisations that tend to describe the type of information required by the adaptive workflow systems. However, because of their lack of formal structure the use of Enterprise Models that have been developed is limited [Junginger, 2000][Chen-Burger, 2001a]. We propose the use of a formal language within a three-layered framework. This language helps to turn the information contained in an informal Enterprise Model into the kind of formal model required by an adaptive Workflow System. In its current state of development, FBPML (Fundamental Business Process Modelling Language) covers business processes, organisational structure, agents and their capabilities as well as execution logic that gives direct instructions to a workflow engine. We assist modelling efforts of Enterprise Modellers by giving them a visual modelling language, underpinned by a formal representation, that is expressive and easy to use and that lets them specify the information required by a workflow engine. In this paper, we present our formal enterprise modelling language, FBPML. We show how adaptive workflow systems, like those developed at AIAI (e.g. the Task Based Process Manager [Stader et al, 2000], AKT Workflow [Chen-Burger, 2002a] and I-X system [Tate, 2002]), can take advantage of Enterprise Models represented in FBPML to provide effective support to users in real business environments.

In this chapter, we describe our project dissemination efforts via a programmable, configurable, 3D Virtual World environment in Second Life and OpenSimulator.