Proceedings of the First International Workshop on Mashup Personal Learning Environments

Wild, F., Kalz, M., & Palmér, M. (Eds.) (2008). Proceedings of the First International Workshop on Mashup Personal Learning Environments (MUPPLE08). September, 17, 2008, Maastricht, The Netherlands: CEUR Workshop Proceedings, ISSN 1613-0073. Available at http://ceur-ws.org/Vol-388.The work on this publication has been sponsored by the TENCompetence Integrated Project (funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org]) and partly sponsored by the LTfLL project (funded by the European Commission's 7th Framework Programme, priority ISCT. Contract 212578 [http://www.ltfll-project.org

A Semantic Wiki-based Platform for IT Service Management

The book researches the use of a semantic wiki in the area of IT Service Management within the IT department of an SME. An emphasis of the book lies in the design and prototypical implementation of tools for the integration of ITSM-relevant information into the semantic wiki, as well as tools for interactions between the wiki and external programs. The result of the book is a platform for agile, semantic wiki-based ITSM for IT administration teams of SMEs

Knowledge-Based Decision Support for Integrated Water Resources Management with an application for Wadi Shueib, Jordan

This book takes a two-staged approach to contribute to the contemporary Integrated Water Resources Management (IWRM) research. First it investigates sub-basin-scale IWRM modelling and scenario planning. The Jordanian Wadi Shueib is used as exemplary case study. Then, it develops a framework to collaboratively manage planning and decision making knowledge on the basis of semantic web technologies. Future IWRM initiatives can benefit from the valuable insights achieved in the presented study

Simple identification tools in FishBase

Simple identification tools for fish species were included in the FishBase information system from its inception. Early tools made use of the relational model and characters like fin ray meristics. Soon pictures and drawings were added as a further help, similar to a field guide. Later came the computerization of existing dichotomous keys, again in combination with pictures and other information, and the ability to restrict possible species by country, area, or taxonomic group. Today, www.FishBase.org offers four different ways to identify species. This paper describes these tools with their advantages and disadvantages, and suggests various options for further development. It explores the possibility of a holistic and integrated computeraided strategy

Mining Meaning from Wikipedia

Wikipedia is a goldmine of information; not just for its many readers, but also for the growing community of researchers who recognize it as a resource of exceptional scale and utility. It represents a vast investment of manual effort and judgment: a huge, constantly evolving tapestry of concepts and relations that is being applied to a host of tasks. This article provides a comprehensive description of this work. It focuses on research that extracts and makes use of the concepts, relations, facts and descriptions found in Wikipedia, and organizes the work into four broad categories: applying Wikipedia to natural language processing; using it to facilitate information retrieval and information extraction; and as a resource for ontology building. The article addresses how Wikipedia is being used as is, how it is being improved and adapted, and how it is being combined with other structures to create entirely new resources. We identify the research groups and individuals involved, and how their work has developed in the last few years. We provide a comprehensive list of the open-source software they have produced.Comment: An extensive survey of re-using information in Wikipedia in natural language processing, information retrieval and extraction and ontology building. Accepted for publication in International Journal of Human-Computer Studie

Managing Changes in Collaborative Networks: A Conceptual Approach

Collaborative Networks represent organizational forms that became omnipresent in today’s way of making business. Such organizational forms are often established in order to satisfy a complex customer need, which one company could not satisfy on its own. This means that the participating companies are to a certain degree dependent on each other. Managing inter-firm relationships by means of inter-organizational interdependencies represents an important Business-IT Alignment issue. In this paper, we present the Dependency-based Alignment Framework, which represents a conceptual approach for managing changes in Collaborative Networks from a holistic perspective. A detailed and methodologically well-founded approach in the definition and design of our framework is accompanied by a detailed investigation of relevant properties of this design artifact. To demonstrate the applicability of our framework in practice, we introduce a case study, which uses Semantic Media Wiki and the SPARQL query language. Finally, we evaluate our results in an argumentative and deductively descriptive way

Applying Wikipedia to Interactive Information Retrieval

There are many opportunities to improve the interactivity of information retrieval systems beyond the ubiquitous search box. One idea is to use knowledge bases—e.g. controlled vocabularies, classification schemes, thesauri and ontologies—to organize, describe and navigate the information space. These resources are popular in libraries and specialist collections, but have proven too expensive and narrow to be applied to everyday webscale search. Wikipedia has the potential to bring structured knowledge into more widespread use. This online, collaboratively generated encyclopaedia is one of the largest and most consulted reference works in existence. It is broader, deeper and more agile than the knowledge bases put forward to assist retrieval in the past. Rendering this resource machine-readable is a challenging task that has captured the interest of many researchers. Many see it as a key step required to break the knowledge acquisition bottleneck that crippled previous efforts. This thesis claims that the roadblock can be sidestepped: Wikipedia can be applied effectively to open-domain information retrieval with minimal natural language processing or information extraction. The key is to focus on gathering and applying human-readable rather than machine-readable knowledge. To demonstrate this claim, the thesis tackles three separate problems: extracting knowledge from Wikipedia; connecting it to textual documents; and applying it to the retrieval process. First, we demonstrate that a large thesaurus-like structure can be obtained directly from Wikipedia, and that accurate measures of semantic relatedness can be efficiently mined from it. Second, we show that Wikipedia provides the necessary features and training data for existing data mining techniques to accurately detect and disambiguate topics when they are mentioned in plain text. Third, we provide two systems and user studies that demonstrate the utility of the Wikipedia-derived knowledge base for interactive information retrieval

24th International Conference on Information Modelling and Knowledge Bases

In the last three decades information modelling and knowledge bases have become essentially important subjects not only in academic communities related to information systems and computer science but also in the business area where information technology is applied. The series of European – Japanese Conference on Information Modelling and Knowledge Bases (EJC) originally started as a co-operation initiative between Japan and Finland in 1982. The practical operations were then organised by professor Ohsuga in Japan and professors Hannu Kangassalo and Hannu Jaakkola in Finland (Nordic countries). Geographical scope has expanded to cover Europe and also other countries. Workshop characteristic - discussion, enough time for presentations and limited number of participants (50) / papers (30) - is typical for the conference. Suggested topics include, but are not limited to: 1. Conceptual modelling: Modelling and specification languages; Domain-specific conceptual modelling; Concepts, concept theories and ontologies; Conceptual modelling of large and heterogeneous systems; Conceptual modelling of spatial, temporal and biological data; Methods for developing, validating and communicating conceptual models. 2. Knowledge and information modelling and discovery: Knowledge discovery, knowledge representation and knowledge management; Advanced data mining and analysis methods; Conceptions of knowledge and information; Modelling information requirements; Intelligent information systems; Information recognition and information modelling. 3. Linguistic modelling: Models of HCI; Information delivery to users; Intelligent informal querying; Linguistic foundation of information and knowledge; Fuzzy linguistic models; Philosophical and linguistic foundations of conceptual models. 4. Cross-cultural communication and social computing: Cross-cultural support systems; Integration, evolution and migration of systems; Collaborative societies; Multicultural web-based software systems; Intercultural collaboration and support systems; Social computing, behavioral modeling and prediction. 5. Environmental modelling and engineering: Environmental information systems (architecture); Spatial, temporal and observational information systems; Large-scale environmental systems; Collaborative knowledge base systems; Agent concepts and conceptualisation; Hazard prediction, prevention and steering systems. 6. Multimedia data modelling and systems: Modelling multimedia information and knowledge; Contentbased multimedia data management; Content-based multimedia retrieval; Privacy and context enhancing technologies; Semantics and pragmatics of multimedia data; Metadata for multimedia information systems. Overall we received 56 submissions. After careful evaluation, 16 papers have been selected as long paper, 17 papers as short papers, 5 papers as position papers, and 3 papers for presentation of perspective challenges. We thank all colleagues for their support of this issue of the EJC conference, especially the program committee, the organising committee, and the programme coordination team. The long and the short papers presented in the conference are revised after the conference and published in the Series of “Frontiers in Artificial Intelligence” by IOS Press (Amsterdam). The books “Information Modelling and Knowledge Bases” are edited by the Editing Committee of the conference. We believe that the conference will be productive and fruitful in the advance of research and application of information modelling and knowledge bases. Bernhard Thalheim Hannu Jaakkola Yasushi Kiyok