Marite Kirikova

Explanatory capability of enterprise models

Abstract Enterprise modelling technology prescribes systematic use and computer-aided documentation of knowledge about enterprises. The basis of this technology is the enterprise model, assumed to be developed during the organisational analysis, re-engineering or requirements acquisition processes where it serves as an additional source of knowledge elicitation as well. Enterprise modelling technology is also potentially applicable in the area of organisational learning. The enterprise model usually consists of several sub-models that have user-oriented meta-knowledge structures for communication with human sources of information. The success of the methodology in different areas depends on its representative and explanatory capabilities. Theoretical examination of the explanatory capability of enterprise models from the points of view of Aristotle’s explanatory principles shows that explanatory capability of the models usually is limited. The situation can be improved by richer representations of human-related issues in the enterprise modelling frameworks.

Towards Extending BPMN with the Knowledge Dimension

At the root of the success of modeling, design, reengineering, and running business processes is effective use and support of organizational knowledge. Therefore, the relationships between a business process and organizational knowledge should be clearly documented. Several methods have already been elaborated that introduce the process dimension into knowledge management or a knowledge concept into business process modeling. However, the usability of these methods is restricted either by applicability only to knowledge-intensive processes or by relying on sophisticated or uncommon modeling techniques. Building on the experience accumulated by researchers working at the intersection of business process modeling and knowledge management, this paper proposes to extend the well-known Business Process Modeling Notation with the knowledge dimension so that using a common modeling technique it would be possible to relate different forms of knowledge, information and data to the business process model. The approach is demonstrated by a case study from a data base integration project at the Bioinformatics Company.

Knowledge Dimension in Business Process Modeling

Various business process modeling notations give an opportunity to include elements that belong to different enterprise architecture models in the business process representation. Each model that relates to the business process via its elements can be viewed as a dimension of the business process. Thus the organizational structure model (performer model), goal model, data model, location model, and other models represent a particular dimension of the business process. One of the dimensions that have not yet evolved into a model, which could be easily related to the business process, is knowledge dimension. The paper presents knowledge state transition model rooted into the notion of knowledge code, analyses knowledge representation capabilities of existing business process modeling languages, and proposes a business process activity template, which includes internal and external representations of knowledge dimension. The template helps to clarify several issues with respect to knowledge dimension of business process models and to move forward towards the business process modeling language that can incorporate all modes of knowledge included in knowledge state transition model.

Towards Flexible Information Architecture for Fractal Information Systems

In information systems development and usage the correspondence between concepts used at the business level and data structures processed at the computer systems level is to be established and maintained. The complexity of this task depends on the enterprise and information systems architectures that underlie a particular information system as well as on dynamic properties of information systems environment. In cases of heterogeneous domain ontologies and complex enterprise and information systems architectures, the fractal approach to information systems design can support balanced change propagation from business domain to computer systems domain that, in turn, allows to define and maintain flexible information architecture that supports business goals and processes. Fractal approach allows applying various systems development methods at different administrative levels of the business organization and thus can accelerate the IS development process and change management during the systems maintenance.

Analysing Enterprise Models from a Fractal Organisation Perspective - Potentials and Limitations

The paper focuses on the use of the fractal paradigm in enterprise modeling. It investigates whether the properties of fractal organizations can be applied in business analysis and whether this results in useful outcomes and new insights. Based on an adaptation and operationalization of properties of fractal organizations, two real-world cases are analyzed using the adapted properties. The contributions of this paper are (1) to adapt fractal organisation properties for use in analysis of enterprise models, (2) to present practical examples from two cases showing the application of the fractal organisation properties, and (3) to identify potentials and limitations of using fractal organisation perspective in enterprise model analysis.

Quality of study programs: an ecosystems perspective

The quality of study programs is one of the issues that are essential in the turbulent global environment universities nowadays operate in. Quality may be considered in terms of different quality standards trying to follow their guidelines formally and practically. This paper takes a different view of the quality issue with respect to the study programs in the field of engineering, namely, the quality of the study program is considered from the ecosystem perspective and value exchange between different members of the ecosystem is taken as a central object of interest in defining and supporting the high quality of the program. While analysis of value exchange and detection of changes in the value provision and request are not a natural part of the university teaching process, appropriate models and support systems can help to understand the value exchange process in the educational ecosystem. The understanding of the value exchange process, in turn, helps to identify and monitor knowledge requirements for developing high quality study programs.

Understanding the Problems of Requirements Elicitation Process: A Human Perspective

Issues about requirements elicitation have been an ongoing problem area since the very earliest days of computing. However, incorrect requirements, misunderstood requirements, and many other requirement problems are still present in systems development projects. The purpose of this chapter is to look at the causes of problems in requirement elicitation process. We will look at these problems from the human perspective, trying to understand the role of human cognitive, emotional, motivational, and social processes. Our goal is to understand the aspects which should be taken into consideration when choosing requirement elicitation approaches and methods.

What is CIM: an information system perspective

Model driven architecture usually is represented by computation independent model, platform independent model, and platform specific model. It is assumed that transformations from computation independent model to platform specific model via platform independent model are possible. However, authors rarely discuss the contents of computation independent model, its validity and correspondence to the notion „computation independent”. Philosophically, from the point of view of organizational information systems pure computation independent models do not exist, because information technology solutions are threading through the way people think in their task performance, decision making and information search strategies. Considering information as interpreted data it is possible to distinguish between two inter-related models in the upper level of model driven architecture, namely, human intelligence information processing model and artificial intelligence information processing model, which are titled depending on the substance of the object that interprets the data available and recognizable in the business domain.

Advanced Enterprise Modeling

While the pace of change in the business sector accelerates ever more, the context for this change is becoming more complex. Today’s business environments entail cooperation with different organizations, rapidly changing business activities and processes, and an intensive competitive landscape. Enterprises therefore need the capability to respond quickly and efficiently to these challenges, and even to leverage them to competitive advantage. In this effort, they steadily transform themselves into becoming dynamic, proactive, connected, adaptive, or globally integrated organizations. The objective of this special issue is to bring attention to emerging research in enterprise modeling (EM) – a catalyst for development of IT solutions capable to follow the business of today. In its foundational terms, EM addresses a systematic analysis and modeling of goals and processes, organization and products structures, IT-systems or any other perspective relevant for the modeling purpose. EM research aims to solve business/IT alignment in a holistic manner by providing the techniques, languages, tools, and best practices for using models to represent organizational knowledge and information systems from different perspectives. Described complex business and technology conditions reinforce the role of EM in its responsibility to achieve alignment. Quality attributes such as agility, sensitivity, responsiveness, adaptability, autonomy, and interoperability are emerging as the norms for advanced enterprise models. It is no less important to develop methods to enable enterprise stakeholders to take advantage of those models in order to create business value. The content of the special focus issue is therefore conceived of bringing together novel research results in EM and the topics from the best papers of the 6th and 7th IFIP WG 8.1 conference on the practice of enterprise modeling (PoEM) held in 2012 and 2013. The focus of the PoEM conference series is on advances in the PoEM through a forum for sharing knowledge and experiences between the academic community and practitioners from industry and the public sector. PoEM was initiated in 2008; since its foundation it has been hosted in Sweden, the Netherlands, Norway, Germany, Latvia, and the UK. The six accepted papers reflect different topics of modern EM, including EM approaches addressing: business modeling for networked organizations; contextchanging and capability-driven organizations; transformation and integration of models for improved use from data and service perspectives; visualization solutions for business modeling. In addition to the research papers, the special issue includes two interviews with distinguished practitioners from the business sector: Mr. Sladjan Maras, ViceAssoc. Prof. J. Zdravkovic (&) Assoc. Prof. J. Stirna Stockholm University, Kista, 16440 Stockholm, Sweden e-mail: jelenaz@dsv.su.se

IT Knowledge Requirements Identification in Organizational Networks: Cooperation Between Industrial Organizations and Universities

ICT professionals face rapid technology development, changes in design paradigms, methodologies, approaches, and cooperation patterns. These changes impact relationships between universities that teach ICT disciplines and industrial organizations that develop and use ICT-based products. The required knowledge and skills of university graduates depend mainly on the current industrial situation; therefore the university graduates have to meet industry requirements which are stated at the time point of their graduation, not at the start of their studies. Continuous cooperation between universities and industrial organizations is needed to identify a time and situation-dependent set of knowledge requirements, which lead to situation aware, industry acknowledged, balanced and productive ICT study programs. This chapter proposes information systems solutions supporting cooperation between the university and the industrial organizations with respect to curriculum development in ICT area.