Handbook of Ontologies for Business Interaction

Handbook of Ontologies for Business Interaction

Peter Rittgen (University College Borås, Sweden)
Indexed In: SCOPUS View 1 More Indices
Release Date: November, 2007|Copyright: © 2008 |Pages: 452|DOI: 10.4018/978-1-59904-660-0
ISBN13: 9781599046600|ISBN10: 1599046601|EISBN13: 9781599046624|ISBN13 Softcover: 9781616926427
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Ontologies form an indispensable basis for modeling and engineering languages for business enterprise and information systems: fostering a need for the integration of structural and behavioral aspects in domain-oriented ontologies.

The Handbook of Ontologies for Business Interaction documents high-quality research addressing ontological issues that are relevant to the modeling of enterprises and information systems in general and business processes in particular covering both static and dynamic aspects of structural concepts. This authoritative handbook provides crucial reference content to researchers, practitioners, and scholars in the fields of language design, information systems, enterprise modeling, domain engineering, artificial intelligence, and the Semantic Web.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Agent-oriented enterprise model
  • Aristotelian ontologies
  • Business partner management
  • Demands of mobile users
  • ICT Management
  • Information system support for supply chain management
  • Knowledge management support of enterprise distributed systems
  • Language and algorithms for ontology merging
  • Model-driven business transformations
  • Ontology design
  • Organizational Memory
  • Organizational theories integration
  • OWL modeling
  • Partner selection in business interaction
  • Secure socio-technical systems
  • Semantic business process models
  • Semantic technologies
  • Socio-instrumental pragmatism

Reviews and Testimonials

In the Handbook of Ontologies for Business Interaction there is a strong focus on domain issues; but, domain issues also have considerable impact on the design of a foundational ontology, therefore there is also a section devoted to ontological foundations.

– Peter Rittgen, University College Borås, Sweden

The book will be of interest to researchers, practitioners, and scholars in the fields of language design, information systems, enterprise modeling, domain engineering, artificial intelligence, and the Semantic Web.

– Book News Inc. (2008)

Table of Contents and List of Contributors

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Even the well-disposed reader might ask the question: Why should we concern ourselves with ontologies for business interaction? The answers to this question are many-fold. For one, a renewed interest in ontologies has only recently been fueled by the efforts around the Semantic Web and Web 2.0 (Shadbolt, Hall, & Berners-Lee, 2006) where ontologies are a core technology. But the involvement of ontologies in today’s business world goes deeper than that. This is witnessed by the vast amount of literature on enterprise engineering (Davenport & Short, 1990; Fox, Gruninger, & Zhan, 1994; Gustas & Gustiene, 2004; Jochem, 2002) and enterprise modeling (Barrios & Nurcan, 2004; Fox, 1994; Fox, Barbuceanu, & Gruninger, 1996; Fox, Barbuceanu, Gruninger, & Lin, 1998; Fox & Gruninger, 1998; Gruninger & Fox, 1996; Jureta & Faulkner, 2005; Liles & Presley, 1996; Shinkawa & Matsumoto, 2001). These disciplines are at the heart of many information systems projects and ontologies play a central role even there (Dietz, 2006; Dietz & Habing, 2004; Fox, Barbuceanu, & Gruninger, 1996; Fox, Barbuceanu, & Gruninger et al., 1998; Guarino, 1998; Jackson, 2004; Kof, 2004; Opdahl & Henderson-Sellers, 2002; Uschold, King, Moralee, & Zorgios, 1998; Wand & Weber, 1989; Weber, 1997). But business interaction is a wide field and building ontologies for it is not a straightforward endeavor. There is not a unique vocabulary or terminology that we can use as a starting point but rather a multitude of languages that differ from industry to industry, from functional unit to functional unit, from organization to organization, and even from person to person. This makes it impossible to devise “the” business ontology. In order to cope with the intrinsic complexity of this task, ontology levels have been suggested.

Ontology Levels

Ontologies are typically divided into foundational (or top-level), domain, and application ontologies (Bugaite & Vasilecas, 2005). Foundational ontologies cover the most general categories that can be expected to be common to all domains, such as “individuals” vs. “universals” or “substantials” vs. “moments.” They are, therefore, domain-independent. Domain ontologies are tailored for a specific area of human activity, for example, medicine, electrical engineering, biology, or business. Application ontologies further restrict attention to a particular activity in a domain, for example, the diagnosis of lung diseases in medicine or a computer-based order handling system in business. Figure 1 shows the level architecture and names a few examples on each level.

It can be argued, though, whether three levels of ontology are adequate to cover the whole breadth of ontological endeavors. In the business domain, for example, we can identify any number of dimensions that justify further ontological levels. Let us consider a few examples. We distinguish between private-sector and public-sector organizations. Each organization belongs to some industry (banking, car manufacturing, retail, etc.) and it is divided into functional units such as procurement, production, marketing, sales, and so on. Along the hierarchy we have the strategic, tactical, and operational levels. In addition to these we might also consider a level below the application domain level, the personal level that takes into account, for example, the way in which an individual uses a particular information system for a particular task which is often different from the way others use the same system for the same or a similar task (Carmichael, Kay, & Kummerfeld, 2004; Dieng & Hug, 1998; Haase, Hotho, Schmidt-Thieme, & Sure, 2005; Huhns & Stephens, 1999).

Domain-level Ontologies

The diversity of phenomena along all these dimensions makes it difficult to find an adequate level of abstraction that fits the whole business domain. In organizational theory, a number of metaphors have been suggested to understand and explain organizational behavior at a high level of abstraction. Metaphors establish a link between a source field and a target field and explain phenomena in the target field in terms of the source field. For organizational theory as a target field the following source fields have been proposed: the machine metaphor (Scott, 1997), living systems (biology) (Kendall & Kendall, 1993), open systems (Flood, 2005), the brain metaphor (Gareth, 1997), learning systems (Senge, 1990), social networks (Davern, 1997), complex adaptive systems (Anderson, 1999), autopoietic social systems (Luhmann, 1990), and so on. Using a metaphor implies a shift of domain. Existing ontologies for the source domain can, therefore, be transferred to the business domain.

But metaphors also imply some severe restrictions. By viewing organizations as, for example, living systems, we fail to capture those parts of organizational behavior that are not found in biology. Established approaches to a business ontology draw therefore on a number of different related theories to develop a richer picture of the domain. Theoretical contributions can come from communication theories, for example, Speech Act Theory (Austin, 1962; Searle, 1969, 1979) and Theory of Communicative Action (Habermas, 1984); social theories, for example, actor network theory (Law, 1992; Walsham, 1997) or structuration theory (Giddens, 1984); economic theories, for example, agency theory (Jensen & Meckling, 1976; Ross, 1973) or transaction cost economics (Coase, 1937; Klein, Crawford, & Alchian, 1978; Williamson, 1975, 1981, 1985); and others.

Examples of existing approaches to a general ontology of the business domain are found in Dietz (2006), Fox, Barbuceanu, and Gruninger et al. (1998), Fox and Gruninger (1998), Goldkuhl (2002, 2005), Goldkuhl and Lind (2004b), and Uschold et al. (1998).

Application-level Ontologies

As such a general ontology of the business domain cannot be used directly in any concrete business application. It is therefore necessary to have at least one more level, the application ontology. Some researchers suggest additional levels, for example, task ontologies (Guarino, 1998). But instead of introducing a multitude of levels, we propose to interpret all these levels as different domain ontologies because most of the interesting problems already occur in the presence of a second level. So we just abstract from complexity levels that do not contribute to our discussion. We do not argue that a reduction to three levels is indeed sufficient. According to this definition, a domain ontology can be task-specific, company-specific, and so forth.

When we take a look at the application-ontology level we discover that the idea of having a separate ontology for every application is fraught with a severe problem, as many individuals and organizations make use of several applications within the context of a single task or business process. Let us consider two of the solutions that have been proposed to solve this problem. The first one, a bottom-up approach, aims at integrating the affected application ontologies, each of which could have been developed independently, to derive a higher-level domain ontology for the task or the specific organization. An example of this is given in Corbett (2003).

The second solution is top-down. It assumes the existence of a library of ontologies that is used to build an application ontology (e.g., on the task level) by re-using existing domain ontologies (e.g., on the business process level). Systems that support this are called ontology library systems. Examples of such systems are WebOnto (Domingue, 1998), Ontolingua (Farquhar, Fikes, & Rice, 1997), and SHOE (Heflin & Hendler, 2000).

The Structure of the Book

The structure of the book roughly follows the ontology levels stipulated above in the first three sections. We have decided, though, to drop the (unqualified) term domain ontology and the problematic term task/application ontology and rather speak of general vs. specialized domain ontologies instead. The remaining sections then deal with the development, use, and management of such ontologies. In a Handbook of Ontologies for Business Interaction, there is naturally a strong focus on domain issues as witnessed by the eight chapters in sections two and three. But domain issues also have considerable impact on the design of a foundational ontology. Evidence of this is given in Chapter III, where the authors identify problems in the business domain that call for the introduction of a unique object identifier already on the foundational level. We have therefore introduced a section that is devoted to ontological foundations. In the following, we give an overview of each section’s content.

Ontological Foundations

This section provides an introduction to ontologies and addresses foundational issues. The first chapter, Overview of Semantic Technologies, is written by Anne Cregan. It shows the importance of Semantic Technologies for the future of computing and the role that ontologies play in that context. It delivers a compact introduction into a wide field and helps the reader in developing a better appreciation of the remaining chapters that highlight particular aspects in greater detail.

The second chapter is authored by Marcus Spies and Christophe Roche and is titled Aristotelian Ontologies and OWL Modeling. It shows how Aristotelian ontologies can be realized with the Web ontology language (OWL). The authors argue for the benefits of the Aristotelian approach to ontological modeling and discuss a detailed example of an OWL representation of such an ontology. They also deliver a number of reasons indicating advantages of an epistemological approach over the commonly used object-oriented approach in the area of domain knowledge engineering.

The third chapter by Werner Ceusters and Barry Smith, Referent Tracking for Corporate Memories, concludes this section. The authors take a realist stance in approaching business ontologies with the aim of turning them into a more faithful representation of the targeted portion of reality. They suggest realism-based ontologies as the foundation, in particular, basic formal ontology and granular partition theory, to describe the generic aspects of corporate memories. Referent tracking is used to capture the specific aspects, such as keeping track of each individual business entity.

After the foundational issues relevant for business interaction have been discussed thoroughly in the first section, we proceed to the domain level in sections two and three. Section two discusses domain ontologies on a general level, that is, not restricted to a specific task or application within the business domain. The third section then takes up solutions that are more specialized, that is, directed towards a specific business issue such as security.

General Domain Ontologies for Business Interaction

General domain ontologies try to capture the business domain in its breadth. This means that they claim to address all the essential constituents of enterprises and their behavior. As a consequence, these approaches do not cover any particular issue or constituent at a greater level of detail. They can rather be seen as frameworks that outline the contours of the business world. Such a framework can be used as a frame of reference by more specialized ontologies to fill it with content. The first chapter in this section, Chapter IV in the book, is a good example of this approach: Ontology Design for Interaction in a Reasonable Enterprise by Aldo Gangemi and Valentina Presutti. Their framework is called content ontology design patterns (CODePs) where the constituents are described by modular, interoperable ontologies, for example, for descriptions and situations and plans. These CODePs can be used to reconstruct existing business modeling languages in terms of a common formal context.

Chapter V, Grounding Business Interaction Models: Socio-Instrumental Pragmatism as a Theoretical Foundation, by Göran Goldkuhl and Mikael Lind, takes a completely different approach towards a domain ontology for business interaction. Instead of following a line of philosophical reasoning the authors take their point of departure in experiences from action research projects and generalize them into a theory called business action theory. This theory, in turn, is grounded in a general, albeit informal ontology of the social realm, socio-instrumental pragmatism, where the focus is on social (inter)action that is mediated by artifacts.

Chapter VI, Towards a Meta-model for Socio-Instrumental Pragmatism, is authored by Peter Rittgen. It starts from the same ontology as the previous chapter but aims at a different goal: formalizing the existing framework of socio-instrumental pragmatism by concretizing and refining the basic constituents, for example, actors, actions, and objects, and by providing an axiomatization in the form of associations between the constituents. The author thus arrives at a metamodel that he applies to the reconstruction of an existing business modeling language to demonstrate the generality and descriptive power of the meta-model.

Chapter VII, Towards Organizational Self-Awareness: An Initial Architecture and Ontology, is written by the team of Marielba Zacarias, Rodrigo Magalhães, Artur Caetano, H. Sofia Pinto, and José Tribolet. They start from the assumption that self-awareness is an important prerequisite for business action, both human and organizational. But while self-awareness comes as a natural ingredient with human beings it has to be developed and maintained in the case of organizations. To support this endeavor the authors suggest an architecture and an ontology as a high-level business modeling framework. This framework combines social, organizational, and psychological theories with enterprise modeling approaches.

Chapter VIII, An Agent-Oriented Enterprise Model for Early Requirements Engineering, by Ivan J. Jureta, Stéphane Faulkner, and Manuel Kolp, concludes this section. The authors aim at supporting the communication between business and IT experts at the requirements stage of an information systems development project. Their approach is supposed to facilitate the creation of a specific enterprise model that captures knowledge about the organization and its processes and that can be used to build an agent-oriented requirements specification of the information system to be built and the organizational environment in which it operates. To this end they develop an integrated metamodel or ontology of an enterprise in general that includes concepts from the managerial and information systems domains. These general concepts are instantiated with concrete entities from the particular organization. The ontologies for business interaction contained in this section target the whole business. The following section addresses specific business activities such as ICT management, or particular aspects of business such as security and organizational memory.

Specialized Domain Ontologies for Business Interaction

The first chapter in this section, Chapter IX in the book, is written by Roy Gelbard and Abraham Carmeli. Its title is Towards an Ontology of ICT Management: Integration of Organizational Theories and ICT Core Constructs. It introduces a basic ontology of ICT management that comprises the concepts policy, project, assets and evaluation. The authors then go on to refine this core ontology by studying the possible contributions that some of the major organizational theories can make: stakeholder theory, theory of fit, theory of behavioral integration, agency theory, transaction cost theory, and theory of images of organization.

Chapter X, KnowledgeEco: An Ontology of Organizational Memory, is authored by Hadas Weinberger, Dov Te`eni, and Ariel J. Frank. It provides a specialized domain ontology for the memory of an organization. The development of this ontology follows a five-step process, two steps of which are elaborated in the chapter: analysis and structuring, and evaluation. The former addresses the classification of concepts derived from the literature and how they are mapped to ontological constructs. The results of this step are then validated in the evaluation step by assessing the conceptual coverage of the ontology.

Chapter XI, An Ontology for Secure Socio-Technical Systems, is written by Fabio Massacci, John Mylopoulos, and Nicola Zannone. The authors start by identifying the interface between organizations and their information systems as the primary source of security risks. In order to address security issues we therefore have to model the information systems together with their organizational environment. The authors provide a modeling language for this purpose that comprises a number of relevant concepts based on permission, delegation, and trust, and their Datalog semantics.

Chapter XI concludes this section and also the first half of the book and addresses the foundational and domain levels. The remaining sections deal with development, application, and management of business interaction ontologies. The next section, Section IV: Building Business Interaction Ontologies, shows how a concrete instance of an ontology can be created and filled with content.

Building Business Interaction Ontologies

This section contains two chapters that deal with the development of particular ontologies. The first one, Chapter XII in the book, is written by Paul Jackson and Ray Webster: Linking Ontological Conceptions and Mapping Business Life Worlds. The authors present a method for eliciting knowledge for the design of a corporate intranet within a government agency to solve knowledge management-related issues, for example, work duplication, document location, and accessing tacit expertise. The method combines soft systems methodology, causal cognitive mapping, and brainstorming to create a knowledge ontology using UML class diagrams. It is suitable for understanding nonroutine but rigorous knowledge and making it accessible to the designers of solutions.

Chapter XIII, Modeling Semantic Business Process Models, is authored by Agnes Koschmider and Andreas Oberweis. It focuses on the integration of business processes at the interface between partners in a value chain or network. This integration is tedious because partners do not only differ in the way they organize their processes but also in the languages they speak. This chapter attempts to solve the integration of diverging vocabularies by enriching the process modeling language of Petri nets with the Web ontology language (OWL).

Applying Ontologies in a Business Context

Section V subsumes five chapters that apply ontologies in a specific business context, for example, in the form of a case study in a particular company or a number of cases studies in an industry. The first chapter in this section, Chapter XIV in the book, is written by Juhnyoung Lee. Its title is Ontologies for Model-Driven Business Transformation. This chapter applies ontology to a model-driven approach to business analysis and transformation. It relates business processes and components on the one hand to IT solutions and capabilities on the other hand at different stages of the transformation. This is done by semantic models that show potential causes of problems during transformation and help with the identification of possible solutions. The authors also present a corresponding ontology management system that can be used in modeldriven business transformation.

Chapter XV, Ontology as Information System Support for Supply Chain Management, is by Charu Chandra. It suggests a framework for information organization that is formalized as a reference model. This framework captures the specifics (e.g., dynamics and uncertainty) and functional requirements (e.g., information standardization and problem-orientation) of a supply chain which is interpreted as a managerial, dynamic, complex, and open system. It comprises an information modeling language that captures different aspects of the information system support for supply chains: a system taxonomy, a problem taxonomy, ontology, and ontology-driven information system.

Chapter XVI, Matching Dynamic Demands of Mobile Users with Dynamic Service Offers by Bernhard Holtkamp, Rüdiger Gartmann, Norbert Weißenberg, and Manfred Wojciechowski, describes the use of ontologies for personalized and situation-aware information and service supply of mobile users in different application domains. This is supported by a modular application ontology that is composed of upper-level ontologies for location and time and of domain-specific ontologies. This application ontology is used as a semantic reference model for a matching description of demands and offers in a service-oriented architecture.

Chapter XVII, Knowledge Management Support for Enterprise Distributed Systems, is written by Yun-Heh Chen-Burger, and Yannis Kalfoglou. It addresses issues associated with the overflow of information and the demand for semantic processing on the Web. The authors propose a semantic-based formal framework (ADP) that makes use of existing technologies to create and retrieve knowledge. Effectiveness is achieved by reusing and extending existing knowledge. The authors claim that the approach can also be used for organizational memories and knowledge management.

Chapter XVIII is jointly written by Carol Kort and Jaap Gordijn. It is titled Modeling Strategic Partnerships Using the e3value Ontology: A Field Study in the Banking Industry. The authors study a case from the banking industry where they evaluate strategic partnerships with the help of the so-called e3value ontology. The principle idea behind this approach is to model partnerships as networks for the mutual exchange of business values. It has been extended to cover investment arrangements and outsourcing which are relevant for strategic partnerships.

Chapter XIX, the final chapter of this section, is authored by Peter Weiß, Towards Adaptive Business Networks: Business Partner Management with Ontologies. The chapter investigates the support that ontologies can provide to manage business partner relations in large business communities. In such communities the task of building and maintaining a large number of relations becomes too complex to be handled by individual organizations or a central network manager. The chapter suggests an appropriate ICT infrastructure as a solution where ontologies offer support for communication processes and complex interactions of business entities in collaborative spaces.

Ontology Management

The first five sections of this book discussed how ontologies can be designed and deployed. The final section, Section VI, explores how they can be managed. One aspect of management is that of making ontologies dynamic, that is, providing a context-aware access to them. Chapter XX, POVOO: Process Oriented Views On Ontologies Supporting Business Interaction, by Eva Gahleitner and Wolfram Wöß, takes up this issue. The basic idea is to provide users with information that is meaningful in their current work context. This is achieved by generating views on ontologies which applications can use to query highly specialized knowledge bases.

Chapter XXI, Ontology-Based Partner Selection in Business Interaction, by Jingshan Huang, Jiangbo Dang, and Michael N. Huhns, views business networks as networks of service agents that describe their services in service descriptions. As each such description, and likewise each service request, is written in the light of the particular agent’s ontology, semantic inconsistencies arise that lead to undetected matches or wrongly assumed matches between offers and requests. To solve this issue the authors introduce a compatibility vector system, based on schema-based ontology-merging, to determine and maintain ontology compatibility and to help with the identification of suitable business partners.

Chapter XXII, A Language and Algorithm for Automatic Merging of Ontologies, by Alma-Delia Cuevas-Rasgado and Adolfo Guzman-Arenas, deals with an issue that arises in the creation of large ontologies, which are often built by merging smaller existing ontologies from relevant domains. Much of this work had to be done manually so far. The authors of this final chapter propose an automatic method for this task that can handle inconsistencies, redundancies, and different granularities of information.

Author(s)/Editor(s) Biography

Peter Rittgen received an MSc in computer science and computational linguistics from University Koblenz-Landau (Germany) and a PhD in economics and business administration from Frankfurt University (Germany). He is currently a senior lecturer at the School of Business and Informatics of the University College of Borås (Sweden). He has been doing research on business processes and the development of information systems since 1997, and has published many articles in these areas.