1,470 research outputs found

    Abstractions, accounts and grid usability

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    The vision of the Grid is one of seamless, virtual and constantly changing resources where users need not concern themselves about details, such as exactly where an application is running or where their data is being stored. However, seamless and virtual often imply a lack of control that users may be wary of, or even opposed to. Drawing upon our studies of HCI and of collaborative work, this paper examines whether the Grid development community should be taking this vision literally and argues for the need for accountability of systems ‘in interaction’. We give examples of an alternative approach that seeks to provide ways in which administrators, technical support and user communities can make sense of the behaviour of the complex socio-technical ensembles that are the reality of Grids

    SAGA reloaded: towards a generic platform for developing cooperative applications

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    Groupware specification and development has always been a complex task, requiring special attention to issues such as notification of cooperative actions and ensuring consistency of shared data. Some years ago SAGA was developed as a framework to build groupware applications based on a set of core web services that provide the most common cooperative functionalities. Despite its potential, the last few years brought some technological developments that placed new challenges. This paper presents a new generation of the SAGA platform that adds to the original framework features that emerged recently, namely the regulation of social interaction, incorporation of new communication technologies, connectors to several external services and interaction environments, and the addition of contextual information

    Towards a classification framework for social machines

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    The state of the art in human interaction with computational systems blurs the line between computations performed by machine logic and algorithms, and those that result from input by humans, arising from their own psychological processes and life experience. Current socio-technical systems, known as ‘social machines’ exploit the large-scale interaction of humans with machines. Interactions that are motivated by numerous goals and purposes including financial gain, charitable aid, and simply for fun. In this paper we explore the landscape of social machines, both past and present, with the aim of defining an initial classificatory framework. Through a number of knowledge elicitation and refinement exercises we have identified the polyarchical relationship between infrastructure, social machines, and large-scale social initiatives. Our initial framework describes classification constructs in the areas of contributions, participants, and motivation. We present an initial characterization of some of the most popular social machines, as demonstration of the use of the identified constructs. We believe that it is important to undertake an analysis of the behaviour and phenomenology of social machines, and of their growth and evolution over time. Our future work will seek to elicit additional opinions, classifications and validation from a wider audience, to produce a comprehensive framework for the description, analysis and comparison of social machines

    Towards Collaborative Scientific Workflow Management System

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    The big data explosion phenomenon has impacted several domains, starting from research areas to divergent of business models in recent years. As this intensive amount of data opens up the possibilities of several interesting knowledge discoveries, over the past few years divergent of research domains have undergone the shift of trend towards analyzing those massive amount data. Scientific Workflow Management System (SWfMS) has gained much popularity in recent years in accelerating those data-intensive analyses, visualization, and discoveries of important information. Data-intensive tasks are often significantly time-consuming and complex in nature and hence SWfMSs are designed to efficiently support the specification, modification, execution, failure handling, and monitoring of the tasks in a scientific workflow. As far as the complexity, dimension, and volume of data are concerned, their effective analysis or management often become challenging for an individual and requires collaboration of multiple scientists instead. Hence, the notion of 'Collaborative SWfMS' was coined - which gained significant interest among researchers in recent years as none of the existing SWfMSs directly support real-time collaboration among scientists. In terms of collaborative SWfMSs, consistency management in the face of conflicting concurrent operations of the collaborators is a major challenge for its highly interconnected document structure among the computational modules - where any minor change in a part of the workflow can highly impact the other part of the collaborative workflow for the datalink relation among them. In addition to the consistency management, studies show several other challenges that need to be addressed towards a successful design of collaborative SWfMSs, such as sub-workflow composition and execution by different sub-groups, relationship between scientific workflows and collaboration models, sub-workflow monitoring, seamless integration and access control of the workflow components among collaborators and so on. In this thesis, we propose a locking scheme to facilitate consistency management in collaborative SWfMSs. The proposed method works by locking workflow components at a granular attribute level in addition to supporting locks on a targeted part of the collaborative workflow. We conducted several experiments to analyze the performance of the proposed method in comparison to related existing methods. Our studies show that the proposed method can reduce the average waiting time of a collaborator by up to 36% while increasing the average workflow update rate by up to 15% in comparison to existing descendent modular level locking techniques for collaborative SWfMSs. We also propose a role-based access control technique for the management of collaborative SWfMSs. We leverage the Collaborative Interactive Application Methodology (CIAM) for the investigation of role-based access control in the context of collaborative SWfMSs. We present our proposed method with a use-case of Plant Phenotyping and Genotyping research domain. Recent study shows that the collaborative SWfMSs often different sets of opportunities and challenges. From our investigations on existing research works towards collaborative SWfMSs and findings of our prior two studies, we propose an architecture of collaborative SWfMSs. We propose - SciWorCS - a Collaborative Scientific Workflow Management System as a proof of concept of the proposed architecture; which is the first of its kind to the best of our knowledge. We present several real-world use-cases of scientific workflows using SciWorCS. Finally, we conduct several user studies using SciWorCS comprising different real-world scientific workflows (i.e., from myExperiment) to understand the user behavior and styles of work in the context of collaborative SWfMSs. In addition to evaluating SciWorCS, the user studies reveal several interesting facts which can significantly contribute in the research domain, as none of the existing methods considered such empirical studies, and rather relied only on computer generated simulated studies for evaluation

    Artificial Neural Network for Cooperative Distributed Environments

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    A Framework for Data Sharing in Computer Supported Cooperative Environments

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    Concurrency control is an indispensable part of any information sharing system. Co-operative work introduces new requirements for concurrency control which cannot be met using existing applications and database management systems developed for non-cooperative environments. The emphasis of concurrency control in conventional database management systems is to keep users and their applications from inadvertently corrupting data rather than support a workgroup develop a product together. This insular approach is necessary because applications that access the database have been built with the assumptions that they have exclusive access to the data they manipulate and that users of these applications are generally oblivious of one another. These assumptions, however, are counter to the premise of cooperative work in which human-human interaction is emphasized among a group of users utilizing multiple applications to jointly accomplish a common goal. Consequently, applying conventional approaches to concurrency control are not only inappropriate for cooperative data sharing but can actually hinder group work. Computer support for cooperative work must therefore adopt a fresh approach to concurrency control which does promote group work as much as possible, but without sacrifice of all ability to guarantee system consistency. This research presents a new framework to support data sharing in computer supported cooperative environments; in particular, product development environments where computer support for cooperation among distributed and diverse product developers is essential to boost productivity. The framework is based on an extensible object-oriented data model, where data are represented as a collection of interrelated objects with ancillary attributes used to facilitate cooperation. The framework offers a flexible model of concurrency control, and provides support for various levels of cooperation among product developers and their applications. In addition, the framework enhances group activity by providing the functionality to implement user mediated consistency and to track the progress of group work. In this dissertation, we present the architecture of the framework; we describe the components of the architecture, their operation, and how they interact together to support cooperative data sharing
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