171,449 research outputs found

    Mobile support in CSCW applications and groupware development frameworks

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    Computer Supported Cooperative Work (CSCW) is an established subset of the field of Human Computer Interaction that deals with the how people use computing technology to enhance group interaction and collaboration. Mobile CSCW has emerged as a result of the progression from personal desktop computing to the mobile device platforms that are ubiquitous today. CSCW aims to not only connect people and facilitate communication through using computers; it aims to provide conceptual models coupled with technology to manage, mediate, and assist collaborative processes. Mobile CSCW research looks to fulfil these aims through the adoption of mobile technology and consideration for the mobile user. Facilitating collaboration using mobile devices brings new challenges. Some of these challenges are inherent to the nature of the device hardware, while others focus on the understanding of how to engineer software to maximize effectiveness for the end-users. This paper reviews seminal and state-of-the-art cooperative software applications and development frameworks, and their support for mobile devices

    Applying a User-centred Approach to Interactive Visualization Design

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    Analysing users in their context of work and finding out how and why they use different information resources is essential to provide interactive visualisation systems that match their goals and needs. Designers should actively involve the intended users throughout the whole process. This chapter presents a user-centered approach for the design of interactive visualisation systems. We describe three phases of the iterative visualisation design process: the early envisioning phase, the global specification hase, and the detailed specification phase. The whole design cycle is repeated until some criterion of success is reached. We discuss different techniques for the analysis of users, their tasks and domain. Subsequently, the design of prototypes and evaluation methods in visualisation practice are presented. Finally, we discuss the practical challenges in design and evaluation of collaborative visualisation environments. Our own case studies and those of others are used throughout the whole chapter to illustrate various approaches

    Cross-middleware Interoperability in Distributed Concurrent Engineering

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    Secure, distributed collaboration between different organizations is a key challenge in Grid computing today. The GDCD project has produced a Grid-based demonstrator Virtual Collaborative Facility (VCF) for the European Space Agency. The purpose of this work is to show the potential of Grid technology to support fully distributed concurrent design, while addressing practical considerations including network security, interoperability, and integration of legacy applications. The VCF allows domain engineers to use the concurrent design methodology in a distributed fashion to perform studies for future space missions. To demonstrate the interoperability and integration capabilities of Grid computing in concurrent design, we developed prototype VCF components based on ESA’s current Excel-based Concurrent Design Facility (a non-distributed environment), using a STEP-compliant database that stores design parameters. The database was exposed as a secure GRIA 5.1 Grid service, whilst a .NET/WSE3.0-based library was developed to enable secure communication between the Excel client and STEP database

    A metric to represent the evolution of CAD/analysis models in collaborative design

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    Computer Aided Design (CAD) and Computer Aided Engineering (CAE) models are often used during product design. Various interactions between the different models must be managed for the designed system to be robust and in accordance with initially defined specifications. Research published to date has for example considered the link between digital mock-up and analysis models. However design/analysis integration must take into consideration the important number of models (digital mock-up and simulation) due to model evolution in time, as well as considering system engineering. To effectively manage modifications made to the system, the dependencies between the different models must be known and the nature of the modification must be characterised to estimate the impact of the modification throughout the dependent models. We propose a technique to describe the nature of a modification which may be used to determine the consequence within other models as well as a way to qualify the modified information. To achieve this, a metric is proposed that allows the qualification and evaluation of data or information, based on the maturity and validity of information and model

    Usability dimensions in collaborative GIS

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    Collaborative GIS requires careful consideration of the Human-Computer Interaction (HCI) and Usability aspects, given the variety of users that are expected to use these systems, and the need to ensure that users will find the system effective, efficient, and enjoyable. The chapter explains the link between collaborative GIS and usability engineering/HCI studies. The integration of usability considerations into collaborative GIS is demonstrated in two case studies of Web-based GIS implementation. In the first, the process of digitising an area on Web-based GIS is improved to enhance the user's experience, and to allow interaction over narrowband Internet connections. In the second, server-side rendering of 3D scenes allows users who are not equipped with powerful computers to request sophisticated visualisation without the need to download complex software. The chapter concludes by emphasising the need to understand the users' context and conditions within any collaborative GIS project. © 2006, Idea Group Inc

    The Management and Use of Social Network Sites in a Government Department

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    In this paper we report findings from a study of social network site use in a UK Government department. We have investigated this from a managerial, organisational perspective. We found at the study site that there are already several social network technologies in use, and that these: misalign with and problematize organisational boundaries; blur boundaries between working and social lives; present differing opportunities for control; have different visibilities; have overlapping functionality with each other and with other information technologies; that they evolve and change over time; and that their uptake is conditioned by existing infrastructure and availability. We find the organisational complexity that social technologies are often hoped to cut across is, in reality, something that shapes their uptake and use. We argue the idea of a single, central social network site for supporting cooperative work within an organisation will hit the same problems as any effort of centralisation in organisations. We argue that while there is still plenty of scope for design and innovation in this area, an important challenge now is in supporting organisations in managing what can best be referred to as a social network site 'ecosystem'.Comment: Accepted for publication in JCSCW (The Journal of Computer Supported Cooperative Work

    Sensemaking Practices in the Everyday Work of AI/ML Software Engineering

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    This paper considers sensemaking as it relates to everyday software engineering (SE) work practices and draws on a multi-year ethnographic study of SE projects at a large, global technology company building digital services infused with artificial intelligence (AI) and machine learning (ML) capabilities. Our findings highlight the breadth of sensemaking practices in AI/ML projects, noting developers' efforts to make sense of AI/ML environments (e.g., algorithms/methods and libraries), of AI/ML model ecosystems (e.g., pre-trained models and "upstream"models), and of business-AI relations (e.g., how the AI/ML service relates to the domain context and business problem at hand). This paper builds on recent scholarship drawing attention to the integral role of sensemaking in everyday SE practices by empirically investigating how and in what ways AI/ML projects present software teams with emergent sensemaking requirements and opportunities
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