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

Co-presence Communities: Using pervasive computing to support weak social networks

Although the strongest social relationships feature most prominently in our lives, we also maintain a multitude of much weaker connections: the distant colleagues that we share a coffee with in the afternoon; the waitress at a our regular sandwich bar; or the ‘familiar stranger’ we meet each morning on the way to work. These are all examples of weak relationships which have a strong spatial-temporal component but with few support systems available. This paper explores the idea of ‘Co-presence Communities’ - a probabilistic definition of groups that are regularly collocated together - and how they might be used to support weak social networks. An algorithm is presented for mining the Copresence Community definitions from data collected by Bluetooth-enabled mobile phones. Finally, an example application is introduced which utilises these communities for disseminating information

REST and Linked Data: a match made for domain driven development?

At a first glance there might appear to be an obvious alignment and overlap between the approaches prescribed by REST and Linked Data. On more detailed inspection divergences in scope and applicability present themselves, and for some aspects, incompatibility. In this paper we investigate these similarities and differences and suggest the coupling is worthy of a third look: in combination as a flexible environment in which the developer can focus on domain driven applications

Specification of high-level application programming interfaces (SemSorGrid4Env)

This document defines an Application Tier for the SemsorGrid4Env project. Within the Application Tier we distinguish between Web Applications - which provide a User Interface atop a more traditional Service Oriented Architecture - and Mashups which are driven by a REST API and a Resource Oriented Architecture. A pragmatic boundary is set to enable initial development of Web Applications and Mashups; as the project progresses an evaluation and comparison of the two paradigms may lead to a reassessment of where each can be applied within the project, with the experience gained providing a basis for general guidelines and best practice. Both Web Applications and Mashups are designed and delivered through an iterative user-centric process; requirements generated by the project case studies are a key element of this approach

Exploiting Synergy Between Ontologies and Recommender Systems

Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations. Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

Relaciones entre la vegetación y su espectro polínico en Cataluña

Con el fin de obtener elementos de comparación entre e l paisaje l ocal y regional y su espectro polinice, se presentan l os t"esul tados de análisis polínicos de 29 muestras de superficie recol ectadas en diversas localidades de Cataluña, a la vez que se aportan datos acerca de la representación polínica de l as especies más significativas .On purpose te obtain patterns of compar ison between l ocal and regional landscape and his palynological diagram, i t has be en gi v en the palynol ogical diagram resul ts of 29 superficial collected sampl es in several local ities of Cataluña, at the same time , it has been given some informat i on about palynological representation of the most significa ti ve s pecie

Exploiting synergy between ontologies and recommender systems

Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations.Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured

Programming patterns and development guidelines for Semantic Sensor Grids (SemSorGrid4Env)

The web of Linked Data holds great potential for the creation of semantic applications that can combine self-describing structured data from many sources including sensor networks. Such applications build upon the success of an earlier generation of 'rapidly developed' applications that utilised RESTful APIs. This deliverable details experience, best practice, and design patterns for developing high-level web-based APIs in support of semantic web applications and mashups for sensor grids. Its main contributions are a proposal for combining Linked Data with RESTful application development summarised through a set of design principles; and the application of these design principles to Semantic Sensor Grids through the development of a High-Level API for Observations. These are supported by implementations of the High-Level API for Observations in software, and example semantic mashups that utilise the API