Visual analytics of flight trajectories for uncovering decision making strategies

In air traffic management and control, movement data describing actual and planned flights are used for planning, monitoring and post-operation analysis purposes with the goal of increased efficient utilization of air space capacities (in terms of delay reduction or flight efficiency), without compromising the safety of passengers and cargo, nor timeliness of flights. From flight data, it is possible to extract valuable information concerning preferences and decision making of airlines (e.g. route choice) and air traffic managers and controllers (e.g. flight rerouting or optimizing flight times), features whose understanding is intended as a key driver for bringing operational performance benefits. In this paper, we propose a suite of visual analytics techniques for supporting assessment of flight data quality and data analysis workflows centred on revealing decision making preferences

The role of the RM-ODP computational viewpoint concepts in the MDA approach

An MDA design approach should be able to accommodate designs at different levels of platform-independence. We have proposed a design approach previously (in [2]), which allows these levels to be identified. An important feature of this approach is the notion of abstract platform. An abstract platform is determined by the platform characteristics that are relevant for applications at a certain level of platform-independence, and must be established by considering various design goals. In this paper, we define a framework that makes it possible to use RM-ODP concepts in our MDA design approach. This framework allows a recursive application of the computational viewpoint at different levels of platform-independence. This is obtained by equating the RM-ODP notion of infrastructure to our notion of abstract platform

Partial differential equations for self-organization in cellular and developmental biology

Understanding the mechanisms governing and regulating the emergence of structure and heterogeneity within cellular systems, such as the developing embryo, represents a multiscale challenge typifying current integrative biology research, namely, explaining the macroscale behaviour of a system from microscale dynamics. This review will focus upon modelling how cell-based dynamics orchestrate the emergence of higher level structure. After surveying representative biological examples and the models used to describe them, we will assess how developments at the scale of molecular biology have impacted on current theoretical frameworks, and the new modelling opportunities that are emerging as a result. We shall restrict our survey of mathematical approaches to partial differential equations and the tools required for their analysis. We will discuss the gap between the modelling abstraction and biological reality, the challenges this presents and highlight some open problems in the field

Can acquisition of expertise be supported by technology?

Professional trainees in the workplace are increasingly required to demonstrate specific standards of competence. Yet, empirical evidence of how professionals acquire competence in practice is lacking. The danger, then, is that efforts to support learning processes may be misguided. We hypothesised that a systemic view of how expertise is acquired would support more timely and appropriate development of technology to support workplace learning. The aims of this study were to provide an empirically based understanding of workplace learning and explore how learning could be facilitated through suitable application of technology. We have used the medical specialist trainee as an exemplar of how professionals acquire expertise within a complex working environment. We describe our methodological approach, based on the amalgam of systems analysis and qualitative research methods. We present the development of a framework for analysis and early findings from qualitative data analysis. Based on our findings so far, we present a tentative schema representing how technology can support learning with suggestions for the types of technology that could be used

Testing in the incremental design and development of complex products

Testing is an important aspect of design and development which consumes significant time and resource in many companies. However, it has received less research attention than many other activities in product development, and especially, very few publications report empirical studies of engineering testing. Such studies are needed to establish the importance of testing and inform the development of pragmatic support methods. This paper combines insights from literature study with findings from three empirical studies of testing. The case studies concern incrementally developed complex products in the automotive domain. A description of testing practice as observed in these studies is provided, confirming that testing activities are used for multiple purposes depending on the context, and are intertwined with design from start to finish of the development process, not done after it as many models depict. Descriptive process models are developed to indicate some of the key insights, and opportunities for further research are suggested

Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

Visualisation techniques, human perception and the built environment

Historically, architecture has a wealth of visualisation techniques that have evolved throughout the period of structural design, with Virtual Reality (VR) being a relatively recent addition to the toolbox. To date the effectiveness of VR has been demonstrated from conceptualisation through to final stages and maintenance, however, its full potential has yet to be realised (Bouchlaghem et al, 2005). According to Dewey (1934), perceptual integration was predicted to be transformational; as the observer would be able to ‘engage’ with the virtual environment. However, environmental representations are predominately focused on the area of vision, regardless of evidence stating that the experience is multi sensory. In addition, there is a marked lack of research exploring the complex interaction of environmental design and the user, such as the role of attention or conceptual interpretation. This paper identifies the potential of VR models to aid communication for the Built Environment with specific reference to human perception issues

Unveiling connectivity patterns of categories in complex systems: an application to human needs in urban places

This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of mathematical sociology on 06/09/2016, available online: http://www.tandfonline.com/doi/full/10.1080/0022250X.2016.1219855We present a methodology based on weighted networks and dependence coefficients aimed at revealing connectivity patterns between categories. As a case study, it is applied to an urban place and at two spatial levels—neighborhood and square—where categories correspond to human needs. Our results show that diverse spatial levels present different and nontrivial patterns of need emergence. A numerical model indicates that these patterns depend on the probability distribution of weights. We suggest that this way of analyzing the connectivity of categories (human needs in our case study) in social and ecological systems can be used to define new strategies to cope with complex processes, such as those related to transition management and governance, urban-making, and integrated planning.Peer ReviewedPostprint (author's final draft

Formalising responsibility modelling for automatic analysis

Modelling the structure of social-technical systems as a basis for informing software system design is a difficult compromise. Formal methods struggle to capture the scale and complexity of the heterogeneous organisations that use technical systems. Conversely, informal approaches lack the rigour needed to inform the software design and construction process or enable automated analysis. We revisit the concept of responsibility modelling, which models social technical systems as a collection of actors who discharge their responsibilities, whilst using and producing resources in the process. Responsibility modelling is formalised as a structured approach for socio-technical system requirements specification and modelling, with well-defined semantics and support for automated structure and validity analysis. The effectiveness of the approach is demonstrated by two case studies of software engineering methodologies