Extensibility of Enterprise Modelling Languages

Die Arbeit adressiert insgesamt drei Forschungsschwerpunkte. Der erste Schwerpunkt setzt sich mit zu entwickelnden BPMN-Erweiterungen auseinander und stellt deren methodische Implikationen im Rahmen der bestehenden Sprachstandards dar. Dies umfasst zum einen ganz konkrete Spracherweiterungen wie z. B. BPMN4CP, eine BPMN-Erweiterung zur multi-perspektivischen Modellierung von klinischen Behandlungspfaden. Zum anderen betrifft dieser Teil auch modellierungsmethodische Konsequenzen, um parallel sowohl die zugrunde liegende Sprache (d. h. das BPMN-Metamodell) als auch die Methode zur Erweiterungsentwicklung zu verbessern und somit den festgestellten Unzulänglichkeiten zu begegnen. Der zweite Schwerpunkt adressiert die Untersuchung von sprachunabhängigen Fragen der Erweiterbarkeit, welche sich entweder während der Bearbeitung des ersten Teils ergeben haben oder aus dessen Ergebnissen induktiv geschlossen wurden. Der Forschungsschwerpunkt fokussiert dabei insbesondere eine Konsolidierung bestehender Terminologien, die Beschreibung generisch anwendbarer Erweiterungsmechanismen sowie die nutzerorientierte Analyse eines potentiellen Erweiterungsbedarfs. Dieser Teil bereitet somit die Entwicklung einer generischen Erweiterungsmethode grundlegend vor. Hierzu zählt auch die fundamentale Auseinandersetzung mit Unternehmensmodellierungssprachen generell, da nur eine ganzheitliche, widerspruchsfreie und integrierte Sprachdefinition Erweiterungen überhaupt ermöglichen und gelingen lassen kann. Dies betrifft beispielsweise die Spezifikation der intendierten Semantik einer Sprache

ON THE USE OF NATURAL LANGUAGE PROCESSING FOR AUTOMATED CONCEPTUAL DATA MODELING

This research involved the development of a natural language processing (NLP) architecture for the extraction of entity relation diagrams (ERDs) from natural language requirements specifications. Conceptual data modeling plays an important role in database and software design and many approaches to automating and developing software tools for this process have been attempted. NLP approaches to this problem appear to be plausible because compared to general free texts, natural language requirements documents are relatively formal and exhibit some special regularities which reduce the complexity of the problem. The approach taken here involves a loose integration of several linguistic components. Outputs from syntactic parsing are used by a set of hueristic rules developed for this particular domain to produce tuples representing the underlying meanings of the propositions in the documents and semantic resources are used to distinguish between correct and incorrect tuples. Finally the tuples are integrated into full ERD representations. The major challenge addressed in this research is how to bring the various resources to bear on the translation of the natural language documents into the formal language. This system is taken to be representative of a potential class of similar systems designed to translate documents in other restricted domains into corresponding formalisms. The system is incorporated into a tool that presents the final ERDs to users who can modify them in the attempt to produce an accurate ERD for the requirements document. An experiment demonstrated that users with limited experience in ERD specifications could produce better representations of requirements documents than they could without the system, and could do so in less time

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

An Ontology-Based Approach for Closed-Loop Product Lifecycle Management

The main goal of the Product Lifecycle Management (PLM) is the management of all the data associated to a product during its lifecycle. Lifecycle data is being generated by events and actions (of various lifecycle agents which are humans and/or software systems) and it is distributed along the product's lifecycle phases: Beginning of Life (BOL) including design and manufacturing, Middle of Life (MOL) including usage and maintenance and End of Life (EOL) including recycling, disposal or other options. Closed-Loop PLM extends the meaning of PLM in order to close the loop of the information among the different lifecycle phases. The idea is that information of MOL could be used at the EOL stage to support deciding the most appropriate EOL option (especially to make decision for re-manufacturing and re-use) and combined with the EOL information it could be used as feedback in the BOL for improving the new generations of the product. Several PLM models have been developed utilising various technologies and methods towards providing aspects of the Closed-Loop PLM concept. Ontologies are rapidly becoming popular in various research fields. There is a tendency both in converting existing models into ontology-based models, and in creating new ontology-based models from scratch. The aim of this dissertation is to include the advantages and features provided by the ontologies into PLM models towards achieving Closed-Loop PLM. Hence, an ontology model of a Product Data and Knowledge Management Semantic Object Model for PLM has been developed. The transformation process of the model into an ontology-based one, using Web Ontology Language-Description Logic (OWL-DL), is described in detail. The background and the motives for converting existing PLM models to ontologies are also provided. The new model facilitates several of the OWL-DL capabilities, while maintaining previously achieved characteristics. Furthermore, case studies based on various application scenarios, are presented. These case studies deal with data integration and interoperability problems, in which a significant number of reasoning capabilities is implemented, and highlight the utilisation of the developed model. Moreover, in this work, a generic concept has been developed, tackling the time treatment in PLM models. Time is the only fundamental dimension which exists along the entire life of an artefact and it affects all artefacts and their qualities. Most commonly in PLM models, time is an attribute in parts such as "activities" and "events" or is a separate part of the model ("four dimensional models"). In this work the concept is that time should not be one part of the model, but it should be the basis of the model, and all other elements should be parts of it. Thus, we introduce the "Duration of Time concept". According to this concept all aspects and elements of a model are parts of time. Case studies demonstrate the applicability and the advantages of the concept in comparison to existing methodologies

C-EMO: A Modeling Framework for Collaborative Network Emotions

Recent research in the area of collaborative networks is focusing on the social and organizational complexity of collaboration environments as a way to prevent technological failures and consequently contribute for the collaborative network’s sustainability. One direction is moving towards the need to provide “human-tech” friendly systems with cognitive models of human factors such as stress, emotion, trust, leadership, expertise or decision-making ability. In this context, an emotion-based system is being proposed with this thesis in order to bring another approach to avoid collaboration network’s failures and help in the management of conflicts. This approach, which is expected to improve the performance of existing CNs, adopts some of the models developed in the human psychology, sociology and affective computing areas. The underlying idea is to “borrow” the concept of human-emotion and apply it into the context of CNs, giving the CN players the ability to “feel emotions”. Therefore, this thesis contributes with a modeling framework that conceptualizes the notion of “emotion” in CNs and a methodology approach based on system dynamics and agent-based techniques that estimates the CN player’s “emotional states” giving support to decision-making processes. Aiming at demonstrating the appropriateness of the proposed framework a simulation prototype was implemented and a validation approach was proposed consisting of simulation of scenarios, qualitative assessment and validation by research community peers.Recentemente a área de investigação das redes colaborativas tem vindo a debruçar-se na complexidade social e organizacional em ambientes colaborativos e como pode ser usada para prevenir falhas tecnológicas e consequentemente contribuir para redes colaborativas sustentáveis. Uma das direcções de estudo assenta na necessidade de fornecer sistemas amigáveis “humano-tecnológicos” com modelos cognitivos de factores humanos como o stress, emoção, confiança, liderança ou capacidade de tomada de decisão. É neste contexto que esta tese propõe um sistema baseado em emoções com o objectivo de oferecer outra aproximação para a gestão de conflitos e falhas da rede de colaboração. Esta abordagem, que pressupõe melhorar o desempenho das redes existentes, adopta alguns dos modelos desenvolvidos nas áreas da psicologia humana, sociologia e affective computing. A ideia que está subjacente é a de “pedir emprestado” o conceito de emoção humana e aplicá-lo no contexto das redes colaborativas, dando aos seus intervenientes a capacidade de “sentir emoções”. Assim, esta tese contribui com uma framework de modelação que conceptualiza a noção de “emoção” em redes colaborativas e com uma aproximação de metodologia sustentada em sistemas dinâmicos e baseada em agentes que estimam os “estados emocionais” dos participantes e da própria rede colaborativa. De forma a demonstrar o nível de adequabilidade da framework de modelação proposta, foi implementado um protótipo de simulação e foi proposta uma abordagem de validação consistindo em simulação de cenários, avaliação qualitativa e validação pelos pares da comunidade científica