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

A unified view of data-intensive flows in business intelligence systems : a survey

Data-intensive flows are central processes in today’s business intelligence (BI) systems, deploying different technologies to deliver data, from a multitude of data sources, in user-preferred and analysis-ready formats. To meet complex requirements of next generation BI systems, we often need an effective combination of the traditionally batched extract-transform-load (ETL) processes that populate a data warehouse (DW) from integrated data sources, and more real-time and operational data flows that integrate source data at runtime. Both academia and industry thus must have a clear understanding of the foundations of data-intensive flows and the challenges of moving towards next generation BI environments. In this paper we present a survey of today’s research on data-intensive flows and the related fundamental fields of database theory. The study is based on a proposed set of dimensions describing the important challenges of data-intensive flows in the next generation BI setting. As a result of this survey, we envision an architecture of a system for managing the lifecycle of data-intensive flows. The results further provide a comprehensive understanding of data-intensive flows, recognizing challenges that still are to be addressed, and how the current solutions can be applied for addressing these challenges.Peer ReviewedPostprint (author's final draft

Semantic Support for Computational Land-Use Modelling

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Practitioner requirements for integrated Knowledge-Based Engineering in Product Lifecycle Management.

The effective management of knowledge as capital is considered essential to the success of engineering product/service systems. As Knowledge Management (KM) and Product Lifecycle Management (PLM) practice gain industrial adoption, the question of functional overlaps between both the approaches becomes evident. This article explores the interoperability between PLM and Knowledge-Based Engineering (KBE) as a strategy for engineering KM. The opinion of key KBE/PLM practitioners are systematically captured and analysed. A set of ranked business functionalities to be fulfiled by the KBE/PLM systems integration is elicited. The article provides insights for the researchers and the practitioners playing both the user and development roles on the future needs for knowledge systems based on PLM

Planets: Integrated Services for Digital Preservation

The Planets Project is developing services and technology to address core challenges in digital preservation. This article introduces the motivation for this work, describes the extensible technical architecture and places the Planets approach into the context of the Open Archival Information System (OAIS) Reference Model. It also provides a scenario demonstrating Planets’ usefulness in solving real-life digital preservation problems and an overview of the project’s progress to date