426 research outputs found
A Semantically Enabled Service Architecture for Mashups over Streaming and Stored Data
No full textSensing 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 readings, sensor data histories, and stored data, as well as juxtaposing with maps and forecast models. In this paper we use a flood emergency response planning application to identify requirements for a semantic sensor web. We propose a generic service architecture to satisfy the requirements that uses semantic annotations to support well-informed interactions between the services. We present the SemSorGrid4Env realisation of the architecture and illustrate its capabilities in the context of the example application
Utility driven adaptive workflow execution
No full textWorkflows are widely used in applications that require coordinated use of computational resources. Workflow definition languages typically abstract over some aspects of the way in which a workflow is to be executed, such as the level of parallelism to be used or the physical resources to be deployed. As a result, a workflow management system has responsibility for establishing how best to map tasks within a workflow to the available resources. As workflows are typically run over shared resources, and thus face unpredictable and changing resource capabilties, there may be benefit to be derived from adapting the task-to-resource mapping while a workflow is executing. This paper describes the use of utility functions to express the relative merits of alternative mappings; in essence, a utility function can be used to give a score to a candidate mapping, and the exploration of alternative mappings can be cast as an optimization problem. In this approach, changing the utility function allows adaptations to be carried out with a view to meeting different objectives. The contributions of this paper include: (i) a description of how adaptive workflow execution can be expressed as an optimization problem where the objective of the adaptation is to maximize some property expressed as a utility function; (ii) a description of how the approach has been applied to support adaptive workflow execution in grids; and (iii) an experimental evaluation of the resulting approach for alternative utility measures based on response time and profit
Efficient top-k query answering using cached views
No full textTop-k query processing has recently received a significant amount of attention due to its wide application in information retrieval, multimedia search and recommendation generation. In this work, we consider the problem of how to efficiently answer a top-k query by using previously cached query results. While there has been some previous work on this problem, existing algorithms suffer from either limited scope or lack of scalability. In this paper, we propose two novel algorithms for handling this problem. The first algorithm LPTA+ provides significantly improved efficiency compared to the state-of-the-art LPTA algorithm [26] by reducing the number of expensive linear programming problems that need to be solved. The second algorithm we propose leverages a standard space partition-based index structure in order to avoid many of the drawbacks of LPTA-based algorithms, thereby further improving the efficiency of query processing. Through extensive experiments on various datasets, we demonstrate that our algorithms significantly outperform the state of the art
Bottom-up evaluation of DataHiLog
No full textMany queries which may be useful in applications such as “data mining” and knowledge acquisition in databases cannot be expressed in traditional query languages such as SQL or Datalog because they lack the ability to query information regarding the schema of the database. We study the language DataHiLog introduced by Ross as a restriction of the language HiLog developed by Chen, Kifer and Warren. DataHiLog is still able to mix schema-level and instance-level queries, while avoiding the problem of infinite answers which can arise in HiLog. We show how the standard techniques for Datalog can be extended to provide a bottom-up evaluation mechanism for DataHiLog, and consider whether Datalog optimization techniques can also be extended to DataHiLog
FA + TA < FSA: Flexible score aggregation
No full textThe problem of aggregating scores, so as to provide a ranking of objects in a dataset according to different evaluation criteria, is central to many modern data-intensive applications. Although efficient (instance optimal) algorithms exist to this purpose (such as the Threshold Algorithm TA and its variants) none of them is able to deal with scenarios in which the function used to aggregate scores is only partially specified. This is the typical case when the function is a weighted sum, and the user is unable to provide precise values for the weights. In this paper, we consider the problem of processing multi-source top-k queries, when only constraints, rather than precise values, are available for the weights. After observing that the so-called Fagin's Algorithm (FA) can be adapted to solve the problem, yet only when no constraints at all are present (a case in which our queries will return the k-skyband of the dataset), we introduce the novel FSA algorithm, which we prove to be instance optimal for any set of constraints on the weights. We also propose several optimizations to the basic FSA logic so as to improve execution times. Experimental analysis on both real and synthetic datasets shows that our optimizations are indeed highly effective and that the increased flexibility provided by FSA introduces little overhead with respect to the case of classical top-k queries
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Optimizing utility in cloud computing through autonomic workload execution
No full textCloud computing provides services to potentially numerous remote users with diverse requirements. Although predictable performance can be obtained through the provision of carefully delimited services, it is straightforward to identify applications in which a cloud might usefully host services that support the composition of more primitive analysis services or the evaluation of complex data analysis requests. In such settings, a service provider must manage complex and unpredictable workloads. This paper describes how utility functions can be used to make explicit the desirability of different workload evaluation strategies, and how optimization can be used to select between such alternatives. The approach is illustrated for workloads consisting of workflows or queries
A semantic sensor web for environmental decision support applications
No full textSensing 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. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England
Right to farm laws
No full textIn the lead up to the 2015 State election it was reported in The Land that the Coalition Government and NSW Farmers had entered into “an unprecedented” memorandum of understanding. Among the “key commitments” entered into were the reform of biodiversity laws and consideration of “proposals for a Right to Farm policy during 2015”.
In July 2014, at its annual conference, NSW Farmers passed a motion calling for “right to farm” legislation. Based on an article by Graham Brown, a NSW Farmers’ executive councillor, that argument seems to have two main aspects:
primarily, granting immunity to farmers from litigation involving nuisance complaints, in particular those arising from the interface between the “smelly, sometimes noisy” realities of farming and “expanding urban centres”; and
secondarily, providing protection from regulatory imposition by governments, State and local, referred to as “hindrances” to land use, including the placing by local councils of e-zones over agricultural property.
The article by Graham Brown concluded:
"In the face of extractive issues, expanding urban centres and red and green tape on-farm, protecting and promoting our farmers’ ability to conduct business, manage the landscape, provide environmental stewardship and grow food, must be supported in legislation."
The case was expressly adopted on 23 June 2015 by Robert Brown MLC of the Shooters and Fishers Party. He spoke in favour of “right to farm” policy and, calling for a parliamentary inquiry into the issue, Mr Brown argued that:
"The increasing trend of urban sprawl has presented some grim implications when the interests of agriculture clash with the lifestyle expectations of semi-rural property owners on the fringes of urban areas, or indeed in whole regions of New South Wales."
This e-brief discusses the history and purpose of “right to farm” laws and their application in the US and Canada. The position in Australia is also discussed, as is the question of the place of such laws in the broader context of the system of planning legislation. 
Silence that matters: Understanding conversations in interdisciplinary collaboration
No full textIn our focus on spoken conversation we tend to forget that there are also things not said. In failing to acknowledge these silences, much of what is significant may be overlooked. This book presents the findings of ethnographic fieldwork in intra- and inter-university collaboration, including that of Dutch and Chinese scientists. It also offers theoretical insights into the connection between silence and social learning. Silence is analysed in four functions. Understanding these has major practical implications for improving the ways in which we work together.Science Education and Communicatio
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