Magnus Lundqvist

Modelling Information Demand in an Enterprise Context: Method, Notation, and Lessons Learned

Information overload is perceived as a common problem in organisations and enterprises, which calls for new organisational and technological approaches for more pertinent and accurate information supply. The paper contributes to addressing this problem by proposing a method for information demand modelling, which contributes to capturing and understanding the information demand of roles in organisations. This method consists to a large extent of an application of enterprise modelling techniques. Illustrated by a case from automotive industries, lessons learned from information demand modelling are presented and discussed. This includes the specific perspective taken in the method for information demand analysis, common challenges experienced in demand modelling, and the validity of recommendations from participative enterprise modelling for information demand modelling. Furthermore, the paper introduces the notation applied for information demand models and discusses refinement process of this notation.

Information Demand Context Modelling for Improved Information Flow: Experiences and Practices

The paper addresses the field of modelling information demand context, which can be considered as an application of enterprise modelling techniques with focus on capturing information demands. Based on industrial cases from automotive industries, experiences and practices of information demand modelling are presented and investigated. This includes the specific perspective taken in the method for information demand analysis, common challenges experienced in demand modelling, the validity of practices from participative enterprise modelling for context modelling and practices of context modelling.

Moving towards automatic generation of information demand contexts: an approach based on enterprise models and ontology slicing

This paper outlines the first experiences of an approach for automatically deriving information demands in order to provide users with demand-driven information supply and decision support The presented approach is based on the idea that information demands with respect to work activities can be identified by examining the contexts in which they exist and that a suitable source for such contexts are Enterprise Models However, deriving contexts manually from large and complex models is very time consuming and it is therefore proposed that a better approach is to, based on an Enterprise Model, produce a domain ontology and from this then automatically derive the information demand contexts that exist in the model.

Modeling Collaborative Design Competence with Ontologies

Collaborative design in dispersed groups of engineers creates various kinds of challenges to technology, organization and social environment. Selected examples are knowledge sharing, coordination s ...

Transfer of Method Knowledge and Modelling in Distributed Teams – Lessons Learned

One of the traditional application areas for enterprise modelling is the context of improving business practice and management. In improvement situations an important dimension is better information flow in enterprises, i.e. to be able to provide the right information required to complete enterprise tasks. In order to systematically capture and analyse information demand, a method for information demand analysis has been developed. The subject of this paper is the use of this method in distributed teams of modellers, which requires transfer of method knowledge to the modellers, coordination of its application, systematic evaluation of lessons learned, and collection of change proposals for the method. The aim is to report on the process of method knowledge transfer and usage including the lessons learned and implications on the used method. The contributions are (1) lessons learned from the process of transferring method knowledge and performing the actual modelling in distributed teams, (2) implications for the method as such regarding alignment between different models-on-plastic (or paper) and electronic models, and (3) implications for the specific method notation.