Supporting awareness in heterogeneous collaboration environments

Rapid technological advancements have made it possible for humans to collaborate as never before. However demands of group work necessitate distributed collaboration in very heterogeneous environments. Heterogeneity as in various applications, platforms, hardware and communication infrastructure. User mobility, lack of availability and cost often make imposing a common collaboration environment infeasible. Awareness is essential for successful collaboration. Awareness is a key design criterion in groupware but often collaboration occurs with applications not designed to support useful awareness. This dissertation deals with the issue of effective group awareness support in heterogeneous environments.;Awareness propagation is effective if the appropriate amount of information, relevant to the user\u27s sphere of activity is delivered in a timely, unobtrusive fashion. Thus issues such as information overload, and distraction have to be addressed. Furthermore ability to establish the appropriate balance between awareness and privacy is essential. Enhanced forms of awareness such as intersubjectivity and historical awareness are often invaluable. Heterogeneous environments significantly impact the above quality factors impeding effective awareness propagation. Users are unable to tailor the quality of awareness received.;Heterogeneity issues that affect awareness quality are identified. An awareness framework is proposed that binds various sources of awareness information. However for effective awareness support, physical integration must be augmented by information integration. As a solution, an awareness model is proposed. Specification of the awareness model and framework\u27s architecture and features is the key contribution. The proposed model has been validated through simulations of realistic collaboration involving human participation. Scenarios created, have tested the model\u27s usefulness in enhancing the quality of group work by propagating effective awareness among users. To accomplish the same, an Awareness Simulator application has been created. In the validation process, efforts made to create an experimental methodology revealed some techniques related to awareness evaluation in CSCW, which are proposed. Various issues required to successfully engineer such awareness frameworks are identified and their impact on requirements such as security and performance, discussed. With various standards and technologies that can be harnessed to create awareness frameworks, there is great promise that barriers in heterogeneous collaboration environments can be overcome

A CONCEPTUAL FRAMEWORK FOR MOBILE GROUP SUPPORT SYSTEMS

The rapid development of wireless communication and mobile devices has created a great opportunity to support mobile group coordination at a more efficient level than before. This article presents a framework for Mobile Group Support Systems (MGSS) that considers four dimensions: supporting whom, supporting what, where to support and how to support. A good MGSS design should take consideration with the characteristics of each dimension: the system should be able to support mobile users working jointly with members from multiple parties; using available and advanced mobile technology, the system should be able to support context freedom, context dependent, and ad hoc coordination under dynamic, uncertain, frequent disrupting, time and space stretched and fluid context. To meet these requirements, we discuss the issues related to three basic functions of MGSS: mobile communication, group coordination, and context awareness

Collaborative trails in e-learning environments

This deliverable focuses on collaboration within groups of learners, and hence collaborative trails. We begin by reviewing the theoretical background to collaborative learning and looking at the kinds of support that computers can give to groups of learners working collaboratively, and then look more deeply at some of the issues in designing environments to support collaborative learning trails and at tools and techniques, including collaborative filtering, that can be used for analysing collaborative trails. We then review the state-of-the-art in supporting collaborative learning in three different areas – experimental academic systems, systems using mobile technology (which are also generally academic), and commercially available systems. The final part of the deliverable presents three scenarios that show where technology that supports groups working collaboratively and producing collaborative trails may be heading in the near future

Exploiting tacit knowledge through knowledge management technologies

The purpose of this paper is to examine the contributions and suitability of the available knowledge management (KM) technologies, including the Web 2.0 for exploiting tacit knowledge. It proposes an integrated framework for extracting tacit knowledge in organisations, which includes Web 2.0 technologies, KM tools, organisational learning (OL) and Community of Practice (CoP). It reviews a comprehensive literature covering overview of KM theories, KM technologies and OL and identifies the current state of knowledge relating to tacit knowledge exploitation. The outcomes of the paper indicate that Internet and Web 2.0 technologies have stunning prospects for creating learning communities where tacit knowledge can be extracted from people. The author recommends that organisations should design procedures and embed them in their Web 2.0 collaborative platforms persuading employees to record their ideas and share them with other members. It is also recommended that no idea should be taken for granted in a learning community where tacit knowledge exploitation is pursued. It is envisaged that future research should adopt empirical approach involving Complex Adaptive Model for Tacit Knowledge Exploitation (CAMTaKE) and the Theory of Deferred Action in examining the effectiveness of KM technologies including Web 2.0 tools for tacit knowledge exploitation

Activity-Centric Computing Systems

• Activity-Centric Computing (ACC) addresses deep-rooted information management problems in traditional application centric computing by providing a unifying computational model for human goal-oriented ‘activity,’ cutting across system boundaries. • We provide a historical review of the motivation for and development of ACC systems, and highlight the need for broadening up this research topic to also include low-level system research and development. • ACC concepts and technology relate to many facets of computing; they are relevant for researchers working on new computing models and operating systems, as well as for application designers seeking to incorporate these technologies in domain-specific applications

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Pervasive CSCW for smart spaces communities

Future pervasive environments will take into consideration not only individual users' interest, but also social relationships. In today's scenarios, the trend is to make use of collective intelligence, where the interpretation of context information can be harnessed as input for pervasive systems. Therefore, social CSCW applications represent new challenges and possibilities in terms of use of group context information for adaptability and personalization in pervasive computing. The objective of this paper is to present two enterprise scenarios that support collaboration and adaption capabilities through pervasive communities combined with social computing. Collaborative applications integrated with pervasive communities can increase the activity's quality of the end user in a wide variety of tasks