Personalisation in Highly Dynamic Grid Services Environments

Human Computer Interaction (HCI) challenges in highly dynamic computing environments can be solved by tailoring the access and use of services to user preferences. In this era of emerging standards for open and collaborative computing environments, the major challenge that is being addressed in this chapter is how personalisation information can be managed in order to support cross-service personalisation. The authors’ investigation of state of the art work in personalisation and context-aware computing found that user preferences are assumed to be static across different context descriptions whilst in reality some user preferences are transient and vary with changes in context. Further more, the assumed preference models do not give an intuitive interpretation of a preference and lack user expressiveness. This chapter presents a user preference model for dynamic computing environments, based on an intuitive quantitative preference measure and a strict partial order preference representation, to address these issues. The authors present an approach for mining context-based user preferences and its evaluation in a synthetic m-commerce environment. This chapter also shows how the data needed for mining context-based preferences is gathered and managed in a Grid infrastructure for mobile devices.

Tools for Automatic Audio Management

The purpose of this chapter is to introduce tools for automatic audio management. The authors present applications which are already available for the users and describe the algorithms and methods behind these applications and their performance. They also discuss the concept of metadata, which is an important prerequisite for modern distributed personal content applications. The variety of automatic audio management tools is wide-ranging. This chapter covers audio segmentation and classification, query by example of audio, music retrieval and recommendation, and speech management, which they consider as being the most important aspects of audio information management. Computational complexity is one major concern in the present era of personal mobile devices and large multimedia collections available on the internet. Therefore they also introduce clustering and indexing techniques which are developed for faster access in large databases.

Measuring Information Propagation and Processing in Biological Systems

In this chapter the authors study the propagation and processing of information in dynamical systems. Various information management systems can be represented as dynamical systems of interconnected information processing units. Here they focus mostly on genetic regulatory networks that are information processing systems that process and propagate information stored in genome. Boolean networks are used as a dynamical model of regulation, and different ways of parameterizing the dynamical behavior are studied. What are called critical networks are in particular under study, since they have been hypothesized as being the most effective under evolutionary pressure. Critical networks are also present in man-made systems, such as the Internet, and provide a candidate application area for findings on the theory of dynamical networks in this chapter. The authors present approaches of annealed approximation and find that avalanche size distribution data supports criticality of regulatory networks. Based on Shannon information, they then find that a mutual information measure quantifying the coordination of pairwise element activity is maximized at criticality. An approach of algorithmic complexity, the normalized compression distance (NCD), is shown to be applicable to both dynamical and topological features of regulatory networks. NCD can also be seen to enable further utilization of measurement data to estimate information propagation and processing in biological networks.

Hierarchical Organization as a Facilitator of Information Management in Human Collaboration

The purpose of this chapter is to discuss the relationship between three entities: hierarchical organization, information management and human collaboration. This relationship is composed of two parts: the first part is the relationship between the hierarchical organization and information management where the role of the hierarchical organization to facilitate the information management processes is discussed. The second part is the relationship between information management and human collaboration where the role of information management to improve human collaboration in problem solving is discussed. The information management processes are illustrated through an information management life cycle model. This model has three major stages: active, semi-active and inactive stages and has three major phases: creation, searching and utilization phases. The creation phase includes: information creation and using, information authoring and modifying and information organization and indexing. The searching phase includes: information storage and retrieving and information exchange. The utilization phase includes: information accessing and filtering processes. The arguments about the role of hierarchical organization in information management and human collaboration are also discussed. The author showed that the hierarchical organization acts as a facilitator for common information management processes which are required in team collaboration such as: information gathering, organization, retrieving, filtering, exchange, integration or fusion, display and visualization. Human collaboration models are discussed with emphasis on the team collaboration structural model which has four unique but interdependent stages of team collaboration. These stages are: team knowledge construction, collaborative team problem solving, team consensus, and product evaluation and revision. Each stage has four levels: meta-cognition process which guides the overall problem solving process, the information processing tasks which is required by the team to complete each collaboration stage, the knowledge required to support the information processing tasks and the communication mechanisms for knowledge building and information processing. The author focused on the role of information management to improve human collaboration across the four collaboration stages of the team collaboration structural model. He showed that the hierarchical organization is more efficient for information management processes and team collaboration rather than other alternative organizations such as flat, linear and network organizations.

Open Information Management in User-driven Health Care

This chapter discusses the role of open health information management in the the development of a novel, adaptable mixed-platform for supporting health care informational needs. This platform enables clients (patient users) requiring healthcare to enter an unstructured but detailed account of their dayto- day health information requirements that may be structured into a lifetime electronic health record. It illustrates the discussion with an operational model and a pilot project in order to begin to explore the potential of a collaborative network of patient and health professional users to support the provision of health care services, and helping to effectively engage patient users with their own healthcare. Such a solution has the potential to allow both patient and health professional users to produce useful materials, to contribute to improved social health outcomes in terms of health education and primary disease prevention, and to address both pre-treatment and post-treatment phases of illness that are often neglected in the context of overburdened support services.

P2P-Based Management of Collaboration Communication Infrastructures

The use of information management tools in open and unbounded operational environments demands an efficient and robust communication infrastructure in order to allow the appropriate transmission of large amount of information and the collaboration among several humans located in geographically distant places, in different organizations, and usually involving several network administrative domains. In order to provide such efficient communication infrastructure, mechanisms for data network management must be used. However, traditional network management models do not provide the required support to the management of such networks. In this context, an alternative distributed network management model must be employed to the efficient management of the communication infrastructure required to support these information management tools. This chapter presents the use of peer-to-peer (P2P) technologies as support for the management of such networks. It presents a P2P-based distributed network management model and a network management environment that follows this model. The functionalities required for the environment are discussed, including its features, potentialities, and drawbacks.

User Culture, User-System Relation and Trust – The Case of Finnish Wikipedia

In this chapter the open-source based collaboration model of Finnish Wikipedia is examined from the perspective of user culture, which is the fundamental basis of Wikipedia’s project management. The concept of user culture in a mediated collaboration project is introduced and the user culture of Finnish Wikipedia is analyzed in terms of this concept. Also the concept of user-system-relation is presented and the relation between users and the socio-technical system of Wikipedia is examined. This analysis considers the crucial factors in the process of building a trusting relation between the user and the Wikipedia system. From the perspective of user-system-relation, the relationship of trust between the user and the system is much more important than the trust relations between individual users. This article explains the role of user culture and user culture design in a collaborative Web community and considers the nature of a trusting user-system-relation. Examination of one functional example of open information management gives understanding of management tools for open peer-collaboration in general.

Structures in Complex Bipartite Networks

A network structure of nodes and links is an informative way to study information systems. The network representation is valuable because it encodes the structure of the data. This chapter reviews recent advances in the field of network science with an emphasis on describing the structure of information networks. The author argues that bipartite networks constitute an important class of networks, and describes a method for detecting overlapping communities in bipartite networks. The author discusses the relevance of network communities to the future of organizing and understanding large datasets.

R2-IBN

In the age of information proliferation, openness, open information management, interconnectivity, collaboration and communication advances, extended enterprises must be up to date to the new strategic, economic and organizational structures. Consequently, intelligent software based on agent technology emerges to improve system design, and to increase enterprise competitive position as well. The competitiveness is based on the information management, cooperation, collaboration and interconnectivity. Thus, within these interconnectivity and cooperation, conflicts may arise. The automated negotiation plays a key role to look for a common agreement. Argumentation theory has become an important topic in the field of Multi-Agent Systems and especially in the negotiation problem. In this chapter, first, the proposed model MAIS-E2 (Multi-Agent Information System for an Extended Enterprise) is presented. Then an argumentation based negotiation framework: Relationship-Role and Interest Based Negotiation (R2-IBN) framework is presented, and within this framework, the authors focused mainly on, argument generation module via inference rules and argument selection module via fuzzy logic.

DYONIPOS

Efficient and effective knowledge management plays an increasingly important role in knowledge intensive organizations. The research project DYONIPOS focuses on detecting the knowledge needs of knowledge workers and automatically providing this required knowledge just in time. The prototype DYONIPOS generates new knowledge out of artifacts, while avoiding additional work and violations of the knowledge worker’s privacy. The knowledge is made accessible through semantic linkage of the relevant information from existing repositories. In addition DYONIPOS creates an individual and an organizational knowledge data base to achieve the knowledge. This chapter is structured as follows: the introduction section describes the current knowledge management approach and the new approach with use of the DYONIPOS prototype. The background section addresses the relation between the applied approach and the challenge in E-Government, summarizes the aims of the research project DYONIPOS and delivers also insight into the topic knowledge management by describing and criticizing the “SECImodel” according to Ikujiro Nonaka and Hirotaka Takeuchi. After this the research project DYONIPOS, the semantic and knowledge discovery technologies used are presented as well as the use case project DYONIPOS showing the results of the first and the second test and screenshots of the updated DYONIPOS application. The chapter concludes with presentation of the benefits and the technical advantages of the prototype DYONIPOS.