The Semantic Grid: A future e-Science infrastructure

e-Science offers a promising vision of how computer and communication technology can support and enhance the scientific process. It does this by enabling scientists to generate, analyse, share and discuss their insights, experiments and results in an effective manner. The underlying computer infrastructure that provides these facilities is commonly referred to as the Grid. At this time, there are a number of grid applications being developed and there is a whole raft of computer technologies that provide fragments of the necessary functionality. However there is currently a major gap between these endeavours and the vision of e-Science in which there is a high degree of easy-to-use and seamless automation and in which there are flexible collaborations and computations on a global scale. To bridge this practice–aspiration divide, this paper presents a research agenda whose aim is to move from the current state of the art in e-Science infrastructure, to the future infrastructure that is needed to support the full richness of the e-Science vision. Here the future e-Science research infrastructure is termed the Semantic Grid (Semantic Grid to Grid is meant to connote a similar relationship to the one that exists between the Semantic Web and the Web). In particular, we present a conceptual architecture for the Semantic Grid. This architecture adopts a service-oriented perspective in which distinct stakeholders in the scientific process, represented as software agents, provide services to one another, under various service level agreements, in various forms of marketplace. We then focus predominantly on the issues concerned with the way that knowledge is acquired and used in such environments since we believe this is the key differentiator between current grid endeavours and those envisioned for the Semantic Grid

Digital Healthcare Projects Policy Action Plan

Whilst the policies of the centre are designed to support a focused effort researching the field of information and communication technologies (ICTs), including increasingly pervasive communication networks, it is recognised that increasing processing power and the ability to transfer more information faster through both wired and wireless systems means that the developments will also include increased ability to search, filter and share both data and information. Our approach is to find new ways in which technologies can be used to meet the challenges facing health and healthcare in the next 10–15 years. ICTs can both enable and drive change in health and healthcare, and this raises social issues as well as technical ones. Particularly important is that ICTs may drive healthcare towards treating patients nearer (or in) their homes, putting greater emphasis upon bringing the patient more actively into the processes supporting their own healthcare contributing to the transition from the traditional ‘paternalistic’ model to one of negotiation and wider information sharing. . These technologies will generate vast amounts of health-related data. These data are made available to appropriate groups in a timely fashion. It must be processed to yield useful information. This raises questions about how any information generated is used. How is the data analysed? Who owns patient data? Most importantly, who should have access to patient data? The PSC policy documents aim to be both specific yet offer general advice. The intention is to provide cohesive guidance for projects and collective research effort yet provide specific direction to individuals that focus upon their needs. The field cross sections healthcare, pervasive systems and ECS groups. For this reason computer scientists offer to support this process through the provision of tools to steer users through establishing the most appropriate contacts and technology bases inside the pervasive systems centre so as to help find the ‘right’ technology partner and assist in building comprehensive records for collaborative efforts

Semantic annotation in ubiquitous healthcare skills-based learning environments

This paper describes initial work on developing a semantic annotation system for the augmentation of skills-based learning for Healthcare. Scenario driven skills-based learning takes place in an augmented hospital ward simulation involving a patient simulator known as SimMan. The semantic annotation software enables real-time annotations of these simulations for debriefing of the students, student self study and better analysis of the learning approaches of mentors. A description of the developed system is provided with initial findings and future directions for the work.<br/

Artificial intelligence in cyber physical systems

This article conducts a literature review of current and future challenges in the use of artifcial intelligence (AI) in cyber physical systems. The literature review is focused on identifying a conceptual framework for increasing resilience with AI through automation supporting both, a technical and human level. The methodology applied resembled a literature review and taxonomic analysis of complex internet of things (IoT) interconnected and coupled cyber physical systems. There is an increased attention on propositions on models, infrastructures and frameworks of IoT in both academic and technical papers. These reports and publications frequently represent a juxtaposition of other related systems and technologies (e.g. Industrial Internet of Things, Cyber Physical Systems, Industry 4.0 etc.). We review academic and industry papers published between 2010 and 2020. The results determine a new hierarchical cascading conceptual framework for analysing the evolution of AI decision-making in cyber physical systems. We argue that such evolution is inevitable and autonomous because of the increased integration of connected devices (IoT) in cyber physical systems. To support this argument, taxonomic methodology is adapted and applied for transparency and justifcations of concepts selection decisions through building summary maps that are applied for designing the hierarchical cascading conceptual framework

The elements of a computational infrastructure for social simulation

Applications of simulation modelling in social science domains are varied and increasingly widespread. The effective deployment of simulation models depends on access to diverse datasets, the use of analysis capabilities, the ability to visualize model outcomes and to capture, share and re-use simulations as evidence in research and policy-making. We describe three applications of e-social science that promote social simulation modelling, data management and visualization. An example is outlined in which the three components are brought together in a transport planning context. We discuss opportunities and benefits for the combination of these and other components into an e-infrastructure for social simulation and review recent progress towards the establishment of such an infrastructure

Peering over the shoulders of giants?

‘Open’ is a highly-visible cultural trend of the early twenty-first century. A brief scan of anewspaper or quick Internet search reveals it as a prefix to learning, source, standard, data,knowledge, democracy, access, repository, innovation, government, science and probablymore. The expectations of the broadband generation – young people born around the turn ofthe century – for openness and instant, on‑demand access to information affect research asmuch as any other social activity. As the world’s population of digital residents – those whosee the Web as the place where they express opinions, form relationships, develop an identityand belong to a community – grows, the expectation that the Web will be the place whereinformation is created and communicated will grow alongside them

Super-forecasting the 'technological singularity' risks from artificial intelligence

This article investigates cybersecurity (and risk) in the context of ‘technological singularity’ from artificial intelligence. The investigation constructs multiple risk forecasts that are synthesised in a new framework for counteracting risks from artificial intelligence (AI) itself. In other words, the research in this article is not just concerned with securing a system, but also analysing how the system responds when (internal and external) failure(s) and compromise(s) occur. This is an important methodological principle because not all systems can be secured, and totally securing a system is not feasible. Thus, we need to construct algorithms that will enable systems to continue operating even when parts of the system have been compromised. Furthermore, the article forecasts emerging cyber-risks from the integration of AI in cybersecurity. Based on the forecasts, the article is concentrated on creating synergies between the existing literature, the data sources identified in the survey, and forecasts. The forecasts are used to increase the feasibility of the overall research and enable the development of novel methodologies that uses AI to defend from cyber risks. The methodology is focused on addressing the risk of AI attacks, as well as to forecast the value of AI in defence and in the prevention of AI rogue devices acting independently

The Combechem MQTT LEGO microscope: a grid enabled scientific apparatus demonstrator

Grid computing impacts directly on the experimental scientific laboratory in the areas of monitoring and remote control of experiments, and the storage, processing and dissemination of the resulting data. We highlight some of the issues in extending the use of an MQ Telemetry Transport (MQTT) broker from facilitating the remote monitoring of an experiment and its environment to the remote control of an apparatus. To demonstrate these techniques, an Intel-Play QX3 microscope has been "grid-enabled" using a combination of software to control the microscope imaging, and sample handling hardware built from LEGO Mindstorms. The whole system is controlled remotely by passing messages using an IBM WebSphere Message Broker. <br/

Grid-Enabled Non-Invasive Blood Glucose Measurement

Abstract. Earth and life sciences are at the forefront to successfully include computational simulations and modeling. Medical applications are often mentioned as the killer applications for the Grid. The complex methodology and models of Traditional Chinese Medicine offer different approaches to diagnose and treat a persons health condition than typical Western medicine. A possibility to make this often hidden knowledge ex-plicit and available to a broader audience will result in mutual synergies for Western and Chinese medicine as well as improved patient care. This paper proposes the design and implementation of a method to accurately estimate blood glucose values using a novel non-invasive method based on electro-transformation measures in human body meridians. The frame-work used for this scientific computing collaboration, namely the China-Austria Data Grid (CADGrid) framework, provides an Intelligence Base offering commonly used models and algorithms as Web/Grid-Services. The controlled execution of the Non-Invasive Blood Glucose Measure-ment Service and the management of scientific data that arise from model execution can be seen as the first application on top of the CADGrid