Our goal is increasing the users’ value and experience and decreasing the implementation time for web portals. To achieve this goal we adopt a subject-centric perspective on information architecture. The fundament of this approach is that portals should be driven by subject-centric models of the portals’ domains. Out of these domain models, the interaction and interface design of the portals is self-evident. Amongst others, the international industry standard Topic Maps is a portal technology and an implementation of the subjectcentric modelling paradigm. With ActiveTM we introduce a technology, which implements a Model-driven approach to automatically create domain-customised, subject-centric portal engines, based on Topic Maps. ActiveTM has proved as technique for reducing the implementation cost of portals enormously and the implied subject-centricness increases the users’ value and experience significantly.
A user-centric architecture of infotainment content adaptation to the context is presented. The architecture uses component technologies in term of business logic and functionalities offered by social web (OpenID, FOAF) and semantic descriptions of MPEG-7 and MPEG-21. Technological alternatives are discussed and adapted to the specificity of vehicle applications in terms of scalability and platform mobility. The requirements of the architecture are motivated by the presentation of a scenario.
Web 2.0 platforms such as media sharing and social network sites (SNS) concern people in everyday life to a great extent. People are enabled to reach out to various media and up to now, it is nearly impossible to use digital identities ex ante or to recreate users’ identities ex post across different platforms. In this paper, we explore important methodologies in Web 2.0 such as cross-media analysis and social pattern based analysis based on a survey in this area, aiming at cross-platform information diffusion across social network sites. Open issues are discussed to explore the challenges and solutions in this new research area.
This paper introduces a new model of personalized usage of the internet that is based on technologies of user representation, artificial intelligence and semantic augmentation of the content. By taking advantage of internet’s unprecedented dynamics, compared to traditional media, this user representation model incorporates cognitive, mainly, psychology theories, combined with parameters that constitute more traditional approaches in user profiling (such as demographics, expertise, etc). The purpose of this research is to alleviate difficulties that massive approaches impose on areas such as education and information processing, by integrating intelligent adaptive characteristics into web applications; this can lead to a highly adapted to each user’s needs content and more effective, in our case, learning.
In this paper, we introduce a so-called DyVT tool (Dynamic social network Visualization Tool) to support spatiotemporal knowledge visualization and discovery in dynamic social networks. The dynamic aspects of social networks refer to contextualized information such as spatial, temporal as well as users’ personalized information. We also define an XML-based target language incorporating emerging formats like DyNetML, KML, and GraphML. It also provides means to express, store and interchange the dynamic aspects of complex dynamic social network data. Based on this language, users can animate and personalize spatiotemporal knowledge extracted from social network data like email threads or blogs. In addition, a Java based graphical user interface is also available to enable nonexperienced users to customize knowledge visualization easily. A mashup with Google maps for spatiotemporal visualization is provided. With this tool spatiotemporal knowledge on an IBM DB2 Mailing list database containing 69 mailing lists and 56389 mails altogether is well explored.
With the current shift in web technology called Web 2.0, many e-learning experts compare the traditional view of e-learning with the expected level of e-learning services and find common problems with present LMS platforms. Primarily, we will identify the most important properties of an E-learning 2.0 platform. Secondly, a prototype, Java-based opensource E-learning 2.0 platform L2 will be introduced and evaluated.
Information Realisation is the process of presenting data as Textual, Graphical or Audial information to a human user. In this paper, we discuss the importance of this concept with respect to the accessibility of Semantic Web data to a diverse target audience. We provide an ontological point of view, defining the expressive characteristics and application domain of representation formats, thus presenting a system which produces representations customised to the user environment and the nature of the source data. Our approach considers the semantics of the data, not just the structure, and aims to present the information in the most semantically appropriate manner for the given target environment. We provide examples of a simple data set being realised as popular target representation formats: textual (XHTML, RSS); graphical (SVG, X3D); and audial (SoundML, VoiceXML).
Many of today’s biomedical applications and those which are likely to arise in the future require the long-term-storage of irreplaceable living cell samples by means of cryopreservation. Besides storing cell samples, managing a large amount of sample information and executing a high number of different preparation protocols are business processes of cryobanks and cryo-biomedical labs, as well as exchanging samples, their data and preparation protocols between different such institutions. All those processes need to be highly reliable and compatible to the potentially long storage time of cell samples which might be up to centuries. Wrong knowledge about samples or about preparation protocols may be lethal. This paper describes a method which is the fundament for a reliable knowledge management of biological cell samples and of preparation protocols. Moreover, it is the fundament for the ChameleonLab® infrastructure which is a workflow management system (WfMs) matching the particular needs of cryobanks and biomedical labs. Principles and prototypic implementation of ChameleonLab® are described and the integration into the “Eurocryo” demonstration and research cell bank is shown. After discussing a first system evaluation, additional requirements are identified.
In this paper we address and discuss the approach of learning employee skills from data based on XML structured profiles and their representation as a Bayesian network. For extracting new information we use a dependency analysis approach. Many enterprise resource management systems (ERP) come along with integrated modules for Human Resource Management (HRM). One main task of HRM is to manage, improve and deploy the right skills at the right time. These processes are well known as skill management. Furthermore the problem of finding hidden or implicit dependencies between employee skills is considered. Using an information theoretical approach to construct a powerful skill representation as graphical model is recommendable. To demonstrate the achievement of the learned network structure, a test scenario is given, where historical reference project data is used.
Modern computational Problem Solving Environments (PSEs) become more and more complex and knowledge intensive in terms of their integrated toolsets, in particular for engineering design search and optimization. Whether these toolsets can be assembled effectively to produce satisfactory results depends heavily on using the best domain practice and following decisions made by skilled engineers in practical situations. In this paper, a knowledge based approach is used to acquire this knowledge from existing sources and model it in a maintainable fashion. Ontologies are used to develop the conceptualization of a knowledge base. In order to reuse this knowledge to provide guidance at knowledge intensive points, we propose a knowledge based advisor, which can give a context-aware critique to guide users through effective operations of building domain workflows. The concept of a state panel is proposed to collect system state information, which is then reasoned about together with various task models in the JESS (Java Expert System Shell) environment. Two reasoning strategies are designed for different advising styles. A multilayer and client-server style architecture is proposed to illustrate how this advisor can be deployed to make available its knowledge advising service to a real workflow construction PSE in a maintainable fashion. Throughout we use the example of these knowledge services in the context of design optimization in engineering.