The Semantic Automated Discovery and Integration (SADI) Web service Design-Pattern, API and Reference Implementation

Background. 
The complexity and inter-related nature of biological data poses a difficult challenge for data and tool integration. There has been a proliferation of interoperability standards and projects over the past decade, none of which has been widely adopted by the bioinformatics community. Recent attempts have focused on the use of semantics to assist integration, and Semantic Web technologies are being welcomed by this community.

Description. 
SADI – Semantic Automated Discovery and Integration – is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. Using Semantic Web technologies at every level of the Web services “stack”, SADI services consume and produce instances of OWL Classes following a small number of very straightforward best-practices. In addition, we provide codebases that support these best-practices, and plug-in tools to popular developer and client software that dramatically simplify deployment of services by providers, and the discovery and utilization of those services by their consumers.

Conclusions.
SADI Services are fully compliant with, and utilize only foundational Web standards; are simple to create and maintain for service providers; and can be discovered and utilized in a very intuitive way by biologist end-users. In addition, the SADI design patterns significantly improve the ability of software to automatically discover appropriate services based on user-needs, and automatically chain these into complex analytical workflows. We show that, when resources are exposed through SADI, data compliant with a given ontological model can be automatically gathered, or generated, from these distributed, non-coordinating resources - a behavior we have not observed in any other Semantic system. Finally, we show that, using SADI, data dynamically generated from Web services can be explored in a manner very similar to data housed in static triple-stores, thus facilitating the intersection of Web services and Semantic Web technologies

Towards self-organized service-oriented multi-agent systems

The demand for large-scale systems running in complex and even chaotic environments requires the consideration of new paradigms and technologies that provide flexibility, robustness, agility and responsiveness. Multiagents systems is pointed out as a suitable approach to address this challenge by offering an alternative way to design control systems, based on the decentralization of control functions over distributed autonomous and cooperative entities. However, in spite of their enormous potential, they usually lack some aspects related to interoperability, optimization in decentralized structures and truly self-adaptation. This paper discusses a new perspective to engineer adaptive complex systems considering a 3-layer framework integrating several complementary paradigms and technologies. In a first step, it suggests the integration of multi-agent systems with service-oriented architectures to overcome the limitations of interoperability and smooth migration, followed by the use of technology enablers, such as cloud computing and wireless sensor networks, to provide a ubiquitous and reconfigurable environment. Finally, the resulted service-oriented multi-agent system should be enhanced with biologically inspired techniques, namely self-organization, to reach a truly robust, agile and adaptive system

Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

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Enhancing service-oriented holonic multi-agent systems with self-organization

Multi-agents systems and holonic manufacturing systems are suitable approaches to design a new and alternative class of production control systems, based on the decentralization of control functions over distributed autonomous and cooperative entities. However, in spite of their enormous potential they lack some aspects related to interoperability, migration, optimisation in decentralised structures and truly self-adaptation. This paper discusses the advantages of combining these paradigms with complementary paradigms, such as service-oriented architectures, and enhancing them with biologically inspired algorithms and techniques, such as emergent behaviour and self-organization, to reach a truly robust, agile and adaptive control system. An example of applying a stigmergy-based algorithm to dynamically route pallets in a production system is also provided

Towards engineering ontologies for cognitive profiling of agents on the semantic web

Research shows that most agent-based collaborations suffer from lack of flexibility. This is due to the fact that most agent-based applications assume pre-defined knowledge of agents’ capabilities and/or neglect basic cognitive and interactional requirements in multi-agent collaboration. The highlight of this paper is that it brings cognitive models (inspired from cognitive sciences and HCI) proposing architectural and knowledge-based requirements for agents to structure ontological models for cognitive profiling in order to increase cognitive awareness between themselves, which in turn promotes flexibility, reusability and predictability of agent behavior; thus contributing towards minimizing cognitive overload incurred on humans. The semantic web is used as an action mediating space, where shared knowledge base in the form of ontological models provides affordances for improving cognitive awareness

Learning Networks: a first elaboration

Koper, E.J.R., Sloep, P.B. (2002) Learning Networks connecting people, organizations, autonomous agents and learning resources to establish the emergence of effective lifelong learning. Framework. Heerlen, Nederland: Open Universiteit Nederland, Onderwijstechnologisch expertisecentrum. OTEC2002/46The document contains the initial theoretical framework for learning networks. It has been elaborated in several follow-up publications. It presents an overview of theory, general use-case and graph representation of a learning network

SoS-centric Middleware Services for Interoperability in Smart Cities Systems

Modern cities are supported by many IT systems managed by distinct public and private agents. Such legacy systems are often incompatible since, in general, they use old, dependent and nonstandardised technologies. This results in an environment in which there is no interoperability among smart city systems, preventing richer and more interesting applications to be used by citizens, companies, and city administration. An alternative to solve the lack of interoperability is the adoption of a System-of- Systems (SoS) approach. A SoS is a set of independent and heterogeneous constituent systems that interoperate to accomplish a global mission. The collaboration among such constituent systems enables a SoS to offer new functionalities that cannot be provided by any of these systems working as individual entities. The goal of this paper is to propose SoS-centric middleware services to support the management and execution of SoS in Smart Cities environments in a dynamic, transparent and scalable way. The proposed services, once integrated into a smart city platform, support interoperability among different systems operating in a city. Moreover, this paper also presents a motivational case study to make it clear the issues that must be addressed when multiple independent systems are brought together to provide a new Smart City service or application

Through life capability management: benefits and behaviours

Many commercial and social endeavours require a multitude of socio-technical systems to work together effectively in what has come to be known as systems of systems. The Through Life Capability Management (TLCM) construct, currently being embraced by defence departments across the globe, is one such endeavour. TLCM demands changes in the organisation and culture of the defence supply chain in ways that fly in the face of traditional commercial wisdom. This paper reports on two workshops held with TLCM stakeholders in which they identified, and then prioritised, the benefits that they sought from TLCM. From an agreed set of priority benefits, the groups identified the behaviours needed to realise them; the results point to significant challenges in terms of culture and knowledge management. Ergonomists and systems engineers will need to support development of intervention strategies to effect these required changes