Visualizing practical knowledge: The Haughton-Mars Project

To improve how we envision knowledge, we must improve our ability to see knowledge in everyday life. That is, visualization is concerned not only with displaying facts and theories, but also with finding ways to express and relate tacit understanding. Such knowledge, although often referred to as "common," is not necessarily shared and may be distributed socially in choreographies for working together—in the manner that a chef and a maitre d’hôtel, who obviously possess very different skills, coordinate their work. Furthermore, non-verbal concepts cannot in principle be inventoried. Reifying practical knowledge is not a process of converting the implicit into the explicit, but pointing to what we know, showing its manifestations in our everyday life. To this end, I illustrate the study and reification of practical knowledge by examining the activities of a scientific expedition in the Canadian Arctic—a group of scientists preparing for a mission to Mar

INTEGRATED DESIGN OF ALTERNATIVE ENERGY OPTIONS - A MULTICRITERIA APPROACH

Energy planning has come a long way during the 20th century from an intuitive approach to a full-scale discipline, incorporating technological and economic dimensions. The latter include both the micro- and the macro- level, whereas the technological framework covers energy, technology, thermodynamics and thermo-economic approaches. It is only during the last two decades that the environmental aspects of energy conversion has started to assume the gravity that it should have been assigned perhaps from the start, with the deterioration of the environment, e.g. acid rain, urban pollution, global warming, etc. and the depletion of resources becoming issues of outmost importance. The emergence of the renewable energy technologies as a reliable substitute of conventional fossil fuels gave promises that were only partially fulfilled as they never assumed the role that society had entrusted on them in the beginning. The alternative energy options, both on the technological and the resource level, revealed the complex nature of energy planning, where energy production and conversion should be addressed in tandem with energy demand and consumption and the particular preferences of the individuals. In both cases the spatial elements should be carefully analyzed and taken into consideration. Today’s energy planning asks for a complex approach which must includes the technological, economic, environmental and social design, accounting for the multitude of facets that interweave in the analysis and successful implementation of energy policies and projects. The aforementioned four dimensions must in turn be decomposed in a number of attributes in order for a quantitative and qualitative estimation to be realized. For the identification of an appropriate solution, a multi-criteria analysis seems to be the logical framework since it allows for a multitude of elements to be incorporated, and at the same time it can include a variety of stakeholders, with conflicting perhaps interests. In this paper we present the new approach for energy planning with the technological, economic, environmental and social design dimensions integrated in a new platform together with the necessary decomposition analysis. The whole new framework is presented via theoretical and practical examples and will hopefully pave the way towards a new under transition, energy future.

Human-machine networks: Towards a typology and profiling framework

© Springer International Publishing Switzerland 2016. In this paper we outline an initial typology and framework for the purpose of profiling human-machine networks, that is, collective structures where humans and machines interact to produce synergistic effects. Profiling a humanmachine network along the dimensions of the typology is intended to facilitate access to relevant design knowledge and experience. In this way the profiling of an envisioned or existing human-machine network will both facilitate relevant design discussions and, more importantly, serve to identify the network type. We present experiences and results from two case trials: a crisis management system and a peerto- peer reselling network. Based on the lessons learnt from the case trials we suggest potential benefits and challenges, and point out needed future work

Realising Synergy in Business Analytics Enabled Systems

The synergy of IT resources with other organisational resources is important in achieving operational and strategic benefits. The synergistic interaction between IT resources and other organisational resources leads to the emergence of new IT-enabled organisational resources, which are capable of generating significant organisational value. The aim of this paper is to understand how this synergy is realised between IT resources and other organisational resources. Based on a synthesis of relevant literature, we propose six enablers and mechanisms which lead to synergy. To assess the face validity of these enablers and mechanisms, we conducted ten one-hour interviews with Business Analytics (BA) experts. The results assisted us in refining and contextualising the enablers and mechanisms for BA systems and led to a clear and comprehensive definition of synergy. The paper concludes with suggestions for empirical research to further refine our definition of synergy

"Going back to our roots": second generation biocomputing

Researchers in the field of biocomputing have, for many years, successfully "harvested and exploited" the natural world for inspiration in developing systems that are robust, adaptable and capable of generating novel and even "creative" solutions to human-defined problems. However, in this position paper we argue that the time has now come for a reassessment of how we exploit biology to generate new computational systems. Previous solutions (the "first generation" of biocomputing techniques), whilst reasonably effective, are crude analogues of actual biological systems. We believe that a new, inherently inter-disciplinary approach is needed for the development of the emerging "second generation" of bio-inspired methods. This new modus operandi will require much closer interaction between the engineering and life sciences communities, as well as a bidirectional flow of concepts, applications and expertise. We support our argument by examining, in this new light, three existing areas of biocomputing (genetic programming, artificial immune systems and evolvable hardware), as well as an emerging area (natural genetic engineering) which may provide useful pointers as to the way forward.Comment: Submitted to the International Journal of Unconventional Computin

The deferred model of reality for designing and evaluating organisational learning processes: A critical ethnographic case study of Komfo Anokye teaching hospital, Ghana

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The study proposed an evidence-based framework for designing and evaluating organisational learning and knowledge management processes to support continuously improving intentions of organisations such as hospitals. It demarcates the extant approaches to organisational learning including supporting technology into ‘rationalist’ and ‘emergent’ schools which utilise the dichotomy between the traditional healthcare managers’ roles and clinicians’ roles, and maintains that they are exclusively inadequate to accomplish transformative growth intentions, such as continuously improving patient care. The possibility of balancing the two schools for effective organisational learning design is not straightforward, and fails; because the balanced-view school is theoretically orientated and lack practical design to resolve power tensions entrenched in organisational structures. Prior attempts to address the organisational learning and knowledge management design and evaluation problematics in actuality have situated in the interpretivist traditions, only focusing on explanations of meanings. Critically, this is uncritical of power relations and orthodox practices. The theory of deferred action is applied in the context of critical research methods and methodology to expose the motivations behind the established organisational learning and knowledge management practices of Komfo Anokye Teaching Hospital (KATH) which assumed rationality design conceptions. Ethnographic data was obtained and interpreted with combined critical hermeneutics and narrative analyses to question the extent of healthcare learning and knowledge management systems failures and unveil the unheard voices as force for change. The study makes many contributions to knowledge but the key ones are: (i) Practically, the participants accepted the study as a catalyst for (re)-designing healthcare learning and knowledge management systems to typify the acceptance of the theory of deferred action in practice; (ii) theoretically, the cohered emergent transformation (CET) model was developed from the theory of deferred action and validated with empirical data to explain how to plan strategically to achieve transformative growth objectives; and (iii) methodologically, the sense-making of the ethnographic data was explored with the combined critical hermeneutics and critical narrative analyses, the data interpretation lens from the critical theory and qualitative pluralism positions, to elucidate how the unheard emergent voices could bring change to the existing KATH learning and knowledge management processes for improved patient care

Investigating biocomplexity through the agent-based paradigm.

Capturing the dynamism that pervades biological systems requires a computational approach that can accommodate both the continuous features of the system environment as well as the flexible and heterogeneous nature of component interactions. This presents a serious challenge for the more traditional mathematical approaches that assume component homogeneity to relate system observables using mathematical equations. While the homogeneity condition does not lead to loss of accuracy while simulating various continua, it fails to offer detailed solutions when applied to systems with dynamically interacting heterogeneous components. As the functionality and architecture of most biological systems is a product of multi-faceted individual interactions at the sub-system level, continuum models rarely offer much beyond qualitative similarity. Agent-based modelling is a class of algorithmic computational approaches that rely on interactions between Turing-complete finite-state machines--or agents--to simulate, from the bottom-up, macroscopic properties of a system. In recognizing the heterogeneity condition, they offer suitable ontologies to the system components being modelled, thereby succeeding where their continuum counterparts tend to struggle. Furthermore, being inherently hierarchical, they are quite amenable to coupling with other computational paradigms. The integration of any agent-based framework with continuum models is arguably the most elegant and precise way of representing biological systems. Although in its nascence, agent-based modelling has been utilized to model biological complexity across a broad range of biological scales (from cells to societies). In this article, we explore the reasons that make agent-based modelling the most precise approach to model biological systems that tend to be non-linear and complex