| |
Abstracts for Semantic Grid Workshop at GGF9 |
Carole Goble, University of Manchester, UK
myGrid is an e-Science pilot research project developing open source high-level middleware to support personalised in silico experiments in biology. In silico experiments use databases and computational analysis rather than laboratory investigations to test hypothesis. Registries provide information about available data and computational services, while remote legacy bioinformatics applications are wrapped using a consistent distributed analysis framework Soaplab. As in conventional science, experimental method is as important as final results. myGrid formalises these methods as workflow or query specifications and provides service based middleware components to enact them. e-Science for the individual often has a narrow focus where generic solutions provide little benefit. Therefore personalisation forms a key theme in myGrid service design. Information repositories, service registries and change notification systems are all being developed to provide personalised views of resources based on an individual's standpoint. To enable such personalisation, middleware components make extensive use of metadata to gain an insight into the subject of each resource. The project is pioneering the use of semantic web technology, to manage metadata annotation, ontologies and semantic discovery. The overall aim is to supply this collection of services as a toolkit with which end applications can be built. To demonstrate this concept the project is building its own end application (the myGrid workbench).
Jim Blythe, Ewa Deelman and Yolanda Gil, USC Information Sciences Institute
Grid computing provides key infrastructure for distributed problem solving in dynamic virtual organizations. It has been adopted by many scientific projects, and industrial interest is rising rapidly. However, grids are still the domain of a few highly trained programmers with expertise in networking, high-performance computing, and operating systems. We have been working in capturing knowledge and heuristics about how to select application components and computing resources, and using that knowledge to generate automatically executable job workflows for a grid. Our system is implemented and integrated with a grid environment where it has generated dozens of workflows with hundreds of jobs in real time. In order to be applicable to a wide range of existing and new grid applications, the planner needs to be able to work with varying levels of semantic information for processes and the information they consume and create. We discuss our experiences dealing with different levels of data and describe a planning-based system that can provide different levels of support based in the information available.
Simon Cox, School of Engineering Sciences, University of Southampton, UK
Semantic Web technologies are evolving the Grid towards the Semantic Grid to yield an intelligent grid which allows seamless process automation, easy knowledge reuse and collaboration within a community of practice. We discuss our endeavours in this direction in the context of Grid enabled optimisation and design search in engineering ("Geodise" project) . In our work we have developed a semantics-based Grid-enabled computing architecture for Geodise. The architecture incorporates a service-oriented distributed knowledge management framework for providing various semantic and knowledge support. It uses ontologies as the conceptual backbone for information-level and knowledge-level computation. We also describe ontological engineering work and a service-oriented approach to ontology deployment. We present several application examples that show the benefit of semantic support in Geodise.
Mario Cannataro, University "Magna Græcia" of Catanzaro, Italy
Main issues to be faced by next-generation Grids are the management and exploitation of the overwhelming amount of data produced by applications but also by Grid operation, and the intelligent use of Grid resources and services. To achieve this very ambitious goals, next-generation Grids should include knowledge discovery and knowledge management functionalities, for both applications and system management. The way how data and information available at different levels of Grid can be effectively acquired, represented, exchanged, integrated, and converted into useful knowledge is an emerging research field known as `Grid Intelligence'. Ontologies and metadata are the basic elements through which such Grid Intelligence can be deployed. Moreover Grids should offer semantic modeling of user's tasks/needs, available services, and data sources to support high level services and dynamic services finding and composition. This document describes some of these emerging services and a first implementation in the KNOWLEDGE GRID, an environment for the design and execution of geographically distributed high-performance knowledge discovery applications.
Luc Moreau, Simon Miles, Juri Papay, Keith Decker, Terry Payne, University of Southampton, UK
Service discovery in large scale, open distributed systems is difficult because of the need to filter out services suitable to the task at hand from a potentially huge pool of possibilities. Semantic descriptions have been advocated as the key to expressive service discovery, but the most commonly used service descriptions and registry protocols do not support such descriptions in a general manner. In this paper, we present an approach and implementation for service registration and discovery that uses an RDF triple store to express semantic service descriptions and other task/user-specific metadata, using a mechanism for attaching structured and unstructured metadata. The result is an extremely flexible service registry that can be the basis of a sophisticated semantically-enhanced service discovery engine, an essential component of a Semantic Grid.
John Brooke, University of Manchester, UK
There is, as yet, no common standard for describing Grid resources. Different Grid middleware systems have had to create ad hoc methods of resource description and it is not yet known how well these can interoperate. We describe work in the Grid Interoperability Project (GRIP) that investigates the possibility of matching the resource descriptions provided by the GLUE schema and implemented in MDS-2 with the resource descriptions provided by the Abstract Job Object framework utilised by UNICORE and stored in the UNICORE Incarnation Database. From this analysis we propose methods of working towards a uniform framework for resource description across different Grid middleware systems.
Mike Surridge, IT Innovation, UK
The vision of the Grid for Industrial Applications (GRIA) project is to make the Grid usable for business and industry: it enables Grid service providers and consumers to come together within a commercial business environment. This brings a strong requirement for a secure and interoperable Grid system which is open at the standards level, makes use of third-party components and can be used by other Grids. The intention is that the system should employ flexible negotiation techniques to enable other parties to join with ease. This raises a spectrum of interoperability challenges, some familiar (resource description, workload estimation, quality of service) but others which are evidently beyond current off-the-shelf solutions. These include representing quality of service for collections of related jobs which are embedded in complex business processes, and the need to describe the semantics of multiparty negotiations including hierarchical conversations. In this paper we describe the GRIA vision and approach, and highlight some of the challenges.
David De Roure, School of Electronics and Computer Science, University of Southampton, UK
The grid may be about utility computing but the interface need not stop at the socket on the wall - it has a more pervasive coupling with the physical world. Pervasive Computing benefits Grid users, such as the e-Scientist in the smart chemistry laboratory or participating in future advanced collaborative environments; meanwhile the Grid benefits those wishing to process the higher volume of sensor data captured by pervasive devices, such as in environmental monitoring applications or wearable devices. Both share a service-based approach and we can ask how far a middleware like GT3 can be pushed towards the devices. Semantic Web technologies help with service description, discovery and composition in pervasive computing as they do in grid computing. Profoundly, another aspect of the Semantic Web is often neglected and can be assisted by pervasive devices: the automatic generation of metadata. Coupled with a means of creating and sharing URIs that are described by that metadata, we can benefit from the "network effects" of the Semantic Web, and establish the linking required to realise the vision of 'publication at source' whereby derived data can be traced all the way back to the laboratory bench. This talk will include a review of ongoing work in the Comb-e-Chem and CoAKTinG projects which have adopted this philosophy of annotation at source.