6,555 research outputs found
Towards a service-oriented e-infrastructure for multidisciplinary environmental research
Research e-infrastructures are considered to have generic and thematic parts. The generic part provids high-speed networks, grid (large-scale distributed computing) and database systems (digital repositories and data transfer systems) applicable to all research commnities irrespective of discipline. Thematic parts are specific deployments of e-infrastructures to support diverse virtual research communities. The needs of a virtual community of multidisciplinary envronmental researchers are yet to be investigated. We envisage and argue for an e-infrastructure that will enable environmental researchers to develop environmental models and software entirely out of existing components through loose coupling of diverse digital resources based on the service-oriented achitecture. We discuss four specific aspects for consideration for a future e-infrastructure: 1) provision of digital resources (data, models & tools) as web services, 2) dealing with stateless and non-transactional nature of web services using workflow management systems, 3) enabling web servce discovery, composition and orchestration through semantic registries, and 4) creating synergy with existing grid infrastructures
Extending OWL-S for the Composition of Web Services Generated With a Legacy Application Wrapper
Despite numerous efforts by various developers, web service composition is
still a difficult problem to tackle. Lot of progressive research has been made
on the development of suitable standards. These researches help to alleviate
and overcome some of the web services composition issues. However, the legacy
application wrappers generate nonstandard WSDL which hinder the progress.
Indeed, in addition to their lack of semantics, WSDLs have sometimes different
shapes because they are adapted to circumvent some technical implementation
aspect. In this paper, we propose a method for the semi automatic composition
of web services in the context of the NeuroLOG project. In this project the
reuse of processing tools relies on a legacy application wrapper called jGASW.
The paper describes the extensions to OWL-S in order to introduce and enable
the composition of web services generated using the jGASW wrapper and also to
implement consistency checks regarding these services.Comment: ICIW 2012, The Seventh International Conference on Internet and Web
Applications and Services, Stuttgart : Germany (2012
AI and data-driven infrastructures for workflow automation and integration in advanced research and industrial applications
The use of AI and data-driven technologies and infrastructures for innovation and development of advanced research and
industrial applications requires a strong degree of integration across a broad range of tools, disciplines and competences. In
spite of a huge disruptive potential, the role of AI for research and development in the context of industrial applications is
often hampered by the lack of consolidated and shared practices for transforming domain-specific processes for generating
knowledge into added value. These issues are particularly striking for small-medium enterprises (SMEs), which must adopt
clear and effective policies for implementing successful technology transfer paths for innovation. The activities of the DAIMON
Lab of the CNR-ISMN focus on the design, development, implementation and application of integrated modelling, data-driven
and AI methods and infrastructures for innovation in hi-tech applications. Our approach is based on the development of
horizontal platforms, which can be applied to a broad range of vertical use-cases. Namely, we target the realisation of
high-throughput workflows, related to specific domains and use cases, which are able to collect and process simulations
and/or physical data and information. The implementation of an interoperable integration framework is a prerequisite for
further application of AI tools for predictivity and automation. With a strong focus on the development of key enabling
technologies (KETs), such as advanced materials, the approach pursued is extended to a broad range of application fields and
scenarios of interest in industry, including electronic and ICT, advanced and sustainable manufacturing, energy, mobilit
Flock together with CReATIVE-B: A roadmap of global research data infrastructures supporting biodiversity and ecosystem science
Biodiversity research infrastructures are providing the integrated data sets and support for studying scenarios of biodiversity and ecosystem dynamics. The CReATIVE-B project - Coordination of Research e-Infrastructures Activities Toward an International Virtual Environment for Biodiversity â explored how cooperation and interoperability of large-scale Research Infrastructures across the globe could support the challenges of biodiversity and ecosystem research. A key outcome of the project is that the research infrastructures agreed to continue cooperation after the end of the project to advance scientific progress in understanding and predicting the complexity of natural systems. By working together in implementing the recommendations in this Roadmap, the data and capabilities of the cooperating research infrastructures are better served to address the grand challenges for biodiversity and ecosystem scientists
Dynamic management for business processes modeling & execution in workflows
Contemporary workflow-management systems cannot represent change or evolution
of business processes. When a change is needed due to external reason, an
offline procedure is invoked in order to create a new workflow engine template
for the future instances in the workflow enactment module. The standard
interfaces do not deal with the business process metadata in a way that can
actually change it as a reaction to inbound knowledge. There are many relevant
cases, especially in the virtual enterprise arena, where the business process
is not deterministic and is influenced by external parameters (such as the
selection of virtual partners), so the knowledge of what should be done is
available, however it is external to the system. There is a need to develop a
modeling mechanism that enables to transfer process definitions in an
automatic way, without the need for human interference. One way of confronting
with these issues is the use of a rule-based engine to monitor business
process execution. This engine will contain internal meta-rules that refer to
metadata entities, i.e. rules that describe how to act on other rules
(business process routing) when a change is detected, while executing all
needed consistency checks
Adaptive Process Management in Cyber-Physical Domains
The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the âphysicalâ real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time
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