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

Using Ontologies for the Design of Data Warehouses

Obtaining an implementation of a data warehouse is a complex task that forces designers to acquire wide knowledge of the domain, thus requiring a high level of expertise and becoming it a prone-to-fail task. Based on our experience, we have detected a set of situations we have faced up with in real-world projects in which we believe that the use of ontologies will improve several aspects of the design of data warehouses. The aim of this article is to describe several shortcomings of current data warehouse design approaches and discuss the benefit of using ontologies to overcome them. This work is a starting point for discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure

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

OntoEng: A design method for ontology engineering in information systems

This paper addresses the design problem relating to ontology engineering in the discipline of information systems. Ontology engineering is a realm that covers issues related to ontology development and use throughout its life span. Nowadays, ontology as a new innovation promises to improve the design, semantic integration, and utilization of information systems. Ontologies are the backbone of knowledge-based systems. In addition, they establish sharable and reusable common understanding of specific domains amongst people, information systems, and software agents. Notwithstanding, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. On the basis of the gathered experience during the development of V4 Telecoms Business Model Ontology as well as the conducted integration of the related literature from the design science paradigm, this paper introduces OntoEng and its application as a novel systematic design method for ontology engineering

Business Process Innovation using the Process Innovation Laboratory

Most organizations today are required not only to establish effective business processes but they are required to accommodate for changing business conditions at an increasing rate. Many business processes extend beyond the boundary of the enterprise into the supply chain and the information infrastructure therefore is critical. Today nearly every business relies on their Enterprise System (ES) for process integration and the future generations of enterprise systems will increasingly be driven by business process models. Consequently process modeling and improvement will become vital for business process innovation (BPI) in future organizations. There is a significant body of knowledge on various aspect of process innovation, e.g. on conceptual modeling, business processes, supply chains and enterprise systems. Still an overall comprehensive and consistent theoretical framework with guidelines for practical applications has not been identified. The aim of this paper is to establish a conceptual framework for business process innovation in the supply chain based on advanced enterprise systems. The main approach to business process innovation in this context is to create a new methodology for exploring process models and patterns of applications. The paper thus presents a new concept for business process innovation called the process innovation laboratory a.k.a. the Ð-Lab. The Ð-Lab is a comprehensive framework for BPI using advanced enterprise systems. The Ð-Lab is a collaborative workspace for experimenting with process models and an explorative approach to study integrated modeling in a controlled environment. The Ð-Lab facilitates innovation by using an integrated action learning approach to process modeling including contemporary technological, organizational and business perspectivesNo; keywords

A Survey on Economic-driven Evaluations of Information Technology

The economic-driven evaluation of information technology (IT) has become an important instrument in the management of IT projects. Numerous approaches have been developed to quantify the costs of an IT investment and its assumed profit, to evaluate its impact on business process performance, and to analyze the role of IT regarding the achievement of enterprise objectives. This paper discusses approaches for evaluating IT from an economic-driven perspective. Our comparison is based on a framework distinguishing between classification criteria and evaluation criteria. The former allow for the categorization of evaluation approaches based on their similarities and differences. The latter, by contrast, represent attributes that allow to evaluate the discussed approaches. Finally, we give an example of a typical economic-driven IT evaluation

Designing a consulting services architecture model

textDuring my years of experience in the technology industry, it has become obvious that standard processes and methodologies within the engineering discipline are at a mature state. The realization though is that software engineering specifically lags behind. Most software engineering methodologies that I have studied focus on the mission of software development. It is this realization and the need for structure that led me to review existing methodologies used within my company's software services organization. The definition of what a successful software services methodology entails is rather limited. This report will provide a history of existing software engineering methodologies that I have studied, describe an initial services method that was being developed within my organization, develop a new model that addresses previous shortcomings and identify additional components required to further define a strong software services-oriented delivery methodology.Electrical and Computer Engineerin