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We have developed and implemented the Relational Grid Monitoring Architecture (R-GMA) as part of the DataGrid project, to provide a flexible information and monitoring service for use by other middleware components and applications. R-GMA presents users with a virtual database and mediates queries posed at this database: users pose queries against a global(More)
The availability of streaming data sources is progressively increasing thanks to the development of ubiquitous data capturing technologies such as sensor networks. The heterogeneity of these sources introduces the requirement of providing data access in a unified and coherent manner, whilst allowing the user to express their needs at an ontological level.(More)
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that(More)
Computational Grids are distributed systems that provide access to computational resources in a transparent fashion. Collecting and providing information about the status of the Grid itself is called Grid monitoring. We describe R-GMA (Relational Grid Monitoring Architecture) as a solution to the Grid monitoring problem. It uses a local as view approach to(More)
BACKGROUND Provenance is a critical ingredient for establishing trust of published scientific content. This is true whether we are considering a data set, a computational workflow, a peer-reviewed publication or a simple scientific claim with supportive evidence. Existing vocabularies such as Dublin Core Terms (DC Terms) and the W3C Provenance Ontology(More)
A wireless sensor network (WSN) can be construed as an intelligent, large-scale device for observing and measuring properties of the physical world. In recent years, the database research community has championed the view that if we construe a WSN as a database (i.e., if a significant aspect of its intelligent behavior is that it can execute(More)
Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g. flood emergency response. However, in order to interpret the readings from the sensors, the data needs to be put in context through correlation with other sensor(More)
The discovery of new medicines requires pharmacologists to interact with a number of information sources ranging from tabular data to scientific papers, and other specialized formats. In this application report, we describe a linked data platform for integrating multiple pharmacology datasets that form the basis for several drug discovery applications. The(More)
Grids are distributed systems that provide access to computational resources in a transparent fashion. Providing information about the status of the Grid itself is called Grid monitoring. As an approach to this problem, we present the Relational Grid Monitoring Architecture (R-GMA), which tackles Grid monitoring as an information integration problem. A(More)
Data integration is a key challenge faced in pharmacology where there are numerous heterogenous databases spanning multiple domains (e.g. chemistry and biology). To address this challenge, the Open PHACTS consortium has developed the Open PHACTS Discovery Platform that leverages Linked Data to provide integrated access to pharmacology databases. Between its(More)