Joerg Evermann

A Critical Examination of Common Beliefs About Partial Least Squares Path Modeling

Partial least squares path modeling (PLS) was developed in the 1960s and 1970s as a method for predictive modeling. In the succeeding years, applied disciplines, including organizational and management research, have developed beliefs about the capabilities of PLS and its suitability for different applications. On close examination, some of these beliefs prove to be unfounded and to bear little correspondence to the actual capabilities of PLS. In this article, we critically examine several of these commonly held beliefs. We describe their origins, and, using simple examples, we demonstrate that many of these beliefs are not true. We conclude that the method is widely misunderstood, and our results cast strong doubts on its effectiveness for building and testing theory in organizational research.

Towards Ontologically Based Semantics for UML Constructs

Conceptual models are formal descriptions of application domains that are used in early stages of system development to support requirements analysis.The Unified Modeling Language was formed by integrating several diagramming techniques for the purpose of software specification, design, construction and maintenance. It would be advantageous to use the same modeling method throughout the development process of an information system, namely, to extend the use of UML to conceptual modeling. This would require assigning well-defined, real-world meaning to UML constructs.In order to model the real-world, we need to specify what might exist in the world, namely, an ontology. We suggest that by mapping UML constructs to well-defined ontological concepts, we can form clear semantics for UML diagrams. Furthermore, based on the mapping we can suggest ontologically-based intra- and inter-diagram integrity rules to guide the construction of conceptual models.In this paper we describe the results we obtained by mapping UML constructs to a specific well-formalized ontological model. In particular, we discuss the ontological meaning of objects, classes, and of interactions.

Ontology based object-oriented domain modelling: fundamental concepts

Understanding the business is an important step in information system (IS) development. Conceptual models are descriptions of the organizational context for which a system is developed, and are used to help understanding this context. However, conceptual modelling methods do not provide well-formalized ways to create domain descriptions. On the other hand, in the area of IS design and software modelling, languages exist (such as UML) that possess a high level of formality. Extending the use of these IS design languages to conceptual modelling, even though they have not been specifically intended for this, can lead to several advantages. In particular, it can enable the use of similar notation in several stages of system development. However, while object-oriented constructs such as “object” and “operation” have clear meaning in the context of software design, it is not clear what they might mean in terms of the application domain, and no rules or guidelines exist for using them to create useful descriptions of such domains. This paper suggests specific semantics for object-oriented constructs based on a mapping between ontologically derived concepts and object-oriented language constructs. The paper also proposes modelling rules to guide the construction of object-oriented conceptual models and to assure that such models describe only ontologically feasible application domain situations. While the results are applicable to object-oriented constructs in general, UML is used as an example. A case study to test the use of the proposed semantics and modelling rules is described.

Toward formalizing domain modeling semantics in language syntax

Information systems are situated in and are representations of some business or organizational domain. Hence, understanding the application domain is critical to the success of information systems development. To support domain understanding, the application domain is represented in conceptual models. The correctness of conceptual models can affect the development outcome and prevent costly rework during later development stages. This paper proposes a method to restrict the syntax of a modeling language to ensure that only possible configurations of a domain can be modeled, thus increasing the likelihood of creating correct domain models. The proposed method, based on domain ontologies, captures relationships among domain elements via constraints on the language metamodel, thus restricting the set of statements about the domain that can be generated with the language. In effect, this method creates domain specific modeling languages from more generic ones. The method is demonstrated using the Unified Modeling Language (UML). Specifically, it is applied to the subset of UML dealing with object behavior and its applicability is demonstrated on a specific modeling example.

A meta-level specification and profile for AspectJ in UML

Aspect-oriented programming (AOP) has become a mature technology. Increasingly, calls for support of AOP on the software model level are being voiced. This paper addresses these calls by offering a meta-model of AspectJ in UML. Using the UML extension mechanisms, this meta-model is at the same time a profile to support AspectJ modelling in UML. In contrast to previous work, this profile offers complete meta-level integration of all AspectJ concepts. The use of standard XMI based modelling allows the use of the profile in commercially available CASE tools and supports easy code generation.

Evaluating ontologies: Towards a cognitive measure of quality

Business process models are an important tool in understanding and improving the efficiency of a business and in the design of information systems. Recent work has evaluated business process modelling languages against upper-level ontologies on the assumption that these ontologies are adequate representations of the general process domain. In this paper, we present a method to test this assumption. Our method is based on principles of cognitive psychology and demonstrated using the BWW and SUMO upper-level ontologies.

Towards a cognitive foundation for knowledge representation

Abstract. Knowledge engineering, knowledge management and conceptual modelling are concerned with representing knowledge of business and organizational domains. These research areas use ontologies for knowledge representation. Ontologies are understood either in the philosophical sense as firm metaphysical commitments or in the looser sense of dictionaries or taxonomies.

A UML and OWL description of Bunge’s upper-level ontology model

A prominent high-level ontology is that proposed by Mario Bunge. While it has been extensively used for research in IS analysis and conceptual modelling, it has not been employed in the more formal settings of semantic web research. We claim that its specification in natural language is the key inhibitor to its wider use. Consequently, this paper offers a description of this ontology in open, standardized knowledge representation formats. The ontology is described both in UML and OWL in order to address needs of both semantic web and conceptual modelling communities.

Predicting process behaviour using deep learning

Abstract Predicting business process behaviour is an important aspect of business process management. Motivated by research in natural language processing, this paper describes an application of deep learning with recurrent neural networks to the problem of predicting the next event in a business process. This is both a novel method in process prediction, which has largely relied on explicit process models, and also a novel application of deep learning methods. The approach is evaluated on two real datasets and our results surpass the state-of-the-art in prediction precision.

Ontology Based Object-Oriented Domain Modeling: Representing Behavior

An important step in developing the requirements for an information system is analyzing the application domain. In this step, conceptual models are used for representing an application domain. However, while languages for software design are available and widely used, no generally accepted language exists for conceptual modeling. This work suggests the use of object-oriented software modeling languages also for conceptual modeling. Such use can support a more accurate transition from domain models to software models. As software-modeling languages were not intended for modeling application domains, their constructs lack the required semantics. While previous papers addressed the representation of structural elements of domains using object concepts, this paper addresses behavioral aspects, related to change and interaction. The proposed semantics are based on a mapping between ontological concepts that describe behavior and object-oriented constructs related to dynamics. Based on these mappings, modeling rules are proposed to guide the modeler in creating ontologically well-formed models. The mappings and rules are exemplified using UML and are demonstrated using a case study.