Multivalent Metadata : Exploiting the Layers of Meaning in Digital Resources

The rapid growth of the World Wide Web was due in part to the simplicity of the Hypertext Markup Language (HTML). It is anticipated that the next generation of web technology, coined the Semantic Web, by Tim Berners-Lee (1989, p. 1), will be driven by the Extensible Markup Language (XML). The XML suite of technologies provides a framework for the application of metadata, and hence semantic information, to web resources. Advantages of a semantic web include improved sharing and reuse of resources, enhanced search mechanisms and knowledge management. The knowledge or meaning contained in digital information may vary according to the perspective of the viewer and can be seen therefore as multivalent in nature. Semantic information that is highly relevant to one user may be of no interest to another. The aim of this project was to demonstrate the layers of meaning inherent in a data sample and how they could be encapsulated in metadata then accessed and manipulated using current technologies, thus leveraging the knowledge contained. Analysis of the data sample, a typical component of an online training product, determined meaningful ways in which the knowledge contained could be reused and adapted. From this analysis a set of test criteria was generated. Metadata was then created for the sample data and the tests implemented using a range of XML technologies

Mining and Visualizing Research Networks using the Artefact-Actor-Network Approach

Reinhardt, W., Wilke, A., Moi, M., Drachsler, H., & Sloep, P. B. (2012). Mining and Visualizing Research Networks using the Artefact-Actor-Network Approach. In A. Abraham (Ed.), Computational Social Networks. Mining and Visualization (pp. 233-268). Springer. Also available at http://www.springer.com/computer/communication+networks/book/978-1-4471-4053-5Virtual communities are increasingly relying on technologies and tools of the so-called Web 2.0. In the context of scientific events and topical Research Networks, researchers use Social Media as one main communication channel. This raises the question, how to monitor and analyze such Research Networks. In this chapter we argue that Artefact-Actor-Networks (AANs) serve well for modeling, storing and mining the social interactions around digital learning resources originating from various learning services. In order to deepen the model of AANs and its application to Research Networks, a relevant theoretical background as well as clues for a prototypical reference implementation are provided. This is followed by the analysis of six Research Networks and a detailed inspection of the results. Moreover, selected networks are visualized. Research Networks of the same type show similar descriptive measures while different types are not directly comparable to each other. Further, our analysis shows that narrowness of a Research Network's subject area can be predicted using the connectedness of semantic similarity networks. Finally conclusions are drawn and implications for future research are discussed

Networked experiments and scientific resource sharing in cooperative knowledge spaces

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Cooperative knowledge spaces create new potentials for the experimental fields in natural sciences and engineering because they enhance the accessibility of experimental setups through virtual laboratories and remote technology, opening them for collaborative and distributed usage. A concept for extending existing virtual knowledge spaces for the means of the technological disciplines (“ViCToR‐Spaces” ‐ Virtual Cooperation in Teaching and Research for Mathematics, Natural Sciences and Engineering) is presented. The integration of networked virtual laboratories and remote experiments (“NanoLab Approach”), as well as an approach to community‐driven content sharing and content development within virtual knowledge spaces (NanoWiki) are described

Use of ontology-based multi-agent systems in the biomedical domain

Coordination, cooperation and exchange of information is important to the medical community. We design a new ontology, called Generic Human Disease Ontology (GHDO), by merging and aligning existing medical ontologies. The concepts of the GHDO are organized into the following four dimensions: Types, Symptoms, Causes and Treatments of human diseases. We also design a multi-agent system framework over different information resources. The multi-agent system uses the common GHDO ontology for query formulation, information retrieval and information integration. We conclude that this intelligent dynamic system provides opportunities to collect information from multiple information resources, to share data efficiently and to integrate and manage scientific results in a timely manner

An Analysis of Service Ontologies

Services are increasingly shaping the world’s economic activity. Service provision and consumption have been profiting from advances in ICT, but the decentralization and heterogeneity of the involved service entities still pose engineering challenges. One of these challenges is to achieve semantic interoperability among these autonomous entities. Semantic web technology aims at addressing this challenge on a large scale, and has matured over the last years. This is evident from the various efforts reported in the literature in which service knowledge is represented in terms of ontologies developed either in individual research projects or in standardization bodies. This paper aims at analyzing the most relevant service ontologies available today for their suitability to cope with the service semantic interoperability challenge. We take the vision of the Internet of Services (IoS) as our motivation to identify the requirements for service ontologies. We adopt a formal approach to ontology design and evaluation in our analysis. We start by defining informal competency questions derived from a motivating scenario, and we identify relevant concepts and properties in service ontologies that match the formal ontological representation of these questions. We analyze the service ontologies with our concepts and questions, so that each ontology is positioned and evaluated according to its utility. The gaps we identify as the result of our analysis provide an indication of open challenges and future work

A methodology for structured ontology construction applied to intelligent transportation systems

The number of computers installed in urban and transport networks has grown tremendously in recent years, also the local processing capabilities and digital networking currently available. However, the heterogeneity of existing equipment in the field of ITS (Intelligent Transportation Systems) and the large volume of information they handle, greatly hinder the interoperability of the equipment and the design of cooperative applications between devices currently installed in urban networks. While the dynamic discovery of information, composition and invocation of services through intelligent agents are a potential solution to these problems, all these technologies require intelligent management of information flows. In particular, it is necessary to wean these information flows of the technologies used, enabling universal interoperability between computers, regardless of the context in which they are located. The main objective of this paper is to propose a systematic methodology to create ontologies, using methods such as a semantic clustering algorithms for retrieval and representation of information. Using the proposed methodology, an ontology will be developed in the ITS domain. This ontology will serve as the basis of semantic information to a SS (Semantic Service) that allows the connection of new equipment to an urban network. The SS uses the CORBA standard as distributed communication architecture

Re-imagining health and well-being in low resource African settings using an augmented AI system and a 3D digital twin

In this paper, we discuss and explore the potential and relevance of recent developments in artificial intelligence (AI) and digital twins for health and well-being in low-resource African countries. Using an AI systems perspective, we review emerging trends in AI systems and digital twins and propose an initial augmented AI system architecture to illustrate how an AI system can work in conjunction with a 3D digital twin. We highlight scientific knowledge discovery, continual learning, pragmatic interoperability, and interactive explanation and decision-making as important research challenges for AI systems and digital twins.Comment: Submitted to Workshop on AI for Digital Twins and Cyber-physical applications at IJCAI 2023, August 19--21, 2023, Macau, S.A.

Application of digital ecosystems in health domain

Digital Ecosystems (DES) have recently been introduced into the computer and information societies. A Digital Ecosystem is the dynamic and synergetic complex of Digital Communities consisting of interconnected, interrelated and interdependent Digital Species situated in a Digital Environment, that intereact as a functional unit and are linked together through actions, information and transaction flows. Digital Ecosystems integrate various cutting-edge technologies including ontologies, agent-based and self-organizing systems, swarm intelligence, ambient intelligence, data mining etc. The synergetic effects of these methodologies results in a more efficient, effective, reliable and secure system.The application of DES within the health domain would transform the way in which health information is created, stored, accessed, used, managed, analyzed and shared, and would bring an innovative breakthrough within bealth domain. In this paper, we illustrate how the DES Design Methodology can be implemented within the health domain. We focus on the key factors associated with the DES design. The design methodology framework allows better control over the design process and serves as a navigating tool during the Digital Health Ecosystems design

Salutogenic community building

A 'new' approach to community building is based on the concept of salutogenesis (a proactive approach to health promotion and prevention). Increasing organisational focus on sustaining healthy work forces requires a coherent mechanism for coping, social cohesion and community development. This research is based on a ten-month ethnographic study of social workers, health professionals and technologists of a Norwegian NGO involved in community health promotion. The aim was to develop a well-formed understanding of the three salutogenic criteria in terms of community-building processes. It was found that collaborating, planning (organising), and defining the community were the key areas of salutogenic community building. Based on a processual world view of context and action (change), the adaptation of a coherent conceptual framework for modelling practices allowed the identification of generic salutogenic practices in community building at a fundamental level: a non-compositional, non-substance semantico-ontological framework (semantic holism and process ontology)