Maria Bergholtz

Anchor modeling - Agile information modeling in evolving data environments

Maintaining and evolving data warehouses is a complex, error prone, and time consuming activity. The main reason for this state of affairs is that the environment of a data warehouse is in constant change, while the warehouse itself needs to provide a stable and consistent interface to information spanning extended periods of time. In this article, we propose an agile information modeling technique, called Anchor Modeling, that offers non-destructive extensibility mechanisms, thereby enabling robust and flexible management of changes. A key benefit of Anchor Modeling is that changes in a data warehouse environment only require extensions, not modifications, to the data warehouse. Such changes, therefore, do not require immediate modifications of existing applications, since all previous versions of the database schema are available as subsets of the current schema. Anchor Modeling decouples the evolution and application of a database, which when building a data warehouse enables shrinking of the initial project scope. While data models were previously made to capture every facet of a domain in a single phase of development, in Anchor Modeling fragments can be iteratively modeled and applied. We provide a formal and technology independent definition of anchor models and show how anchor models can be realized as relational databases together with examples of schema evolution. We also investigate performance through a number of lab experiments, which indicate that under certain conditions anchor databases perform substantially better than databases constructed using traditional modeling techniques.

Abstraction, restriction, and co-creation: three perspectives on services

The recent surge in the interest of services has brought a plethora of applications of the service concept. There are business services and software services, software-as-a-service, platform-as-a-service, and infrastructure-as-a-service. There is also a multitude of definitions of the service concept. In this paper, we propose not a new definition of service but a conceptual model of the service concept that views services as perspectives on the use and offering of resources. The perspectives addressed by the model are: service as a means for abstraction; service as means for providing restricted access to resources; and service as a means for co-creation of value.

Towards a model of services based on co-creation, abstraction and restriction

The term service is today defined and used in a multitude of ways, and there is no usage characteristic that is common for all of these ways. As a consequence natural language terms used for describing services are ambiguous and often confusing. The lack of a common agreed upon definition of the term makes it difficult to understand and classify services as well as distinguish them from non-service concepts. In this paper, we do not propose a new definition of service but a model of services that helps in analysing the concept. The model is based on three perspectives: service as a means for co-creation of value, service as a means for abstraction, and service as a means for providing restricted access to resources.

Towards a Socio-Institutional Ontology for Conceptual Modelling of Information Systems

Most work on ontologies for conceptual modelling is based on the assumption that conceptual models represent a pre-existing reality, which they should faithfully reflect. This paper suggests an ontology for conceptual modelling of institutional domains taking into account also the prescriptive role of conceptual models, thereby supporting the design of information systems. The paper draws on the current ontological discourse in information systems engineering; descriptive vs prescriptive conceptual modelling; socio-materiality in terms of clarifying the relationships between physical and social domains; and ontological differences between (physical) properties and rights. The results of the paper can be used to support conceptual modelling in business analysis, in particular requirements elicitation of regulative aspects.

Towards a Sociomaterial Ontology

The management of social phenomena in conceptual modelling requires a novel understanding of the notion of representation. In particular, the principles for the existence and identification of objects need to be reconsidered. To do this, the paper draws on the current ontological discourse in information systems engineering and proposes a sociomaterial ontology for supporting conceptual modeling. The ontology shows how organisational entities are grounded in physical ones and how they can be understood in terms of deontic notions like privileges, duties and powers. The sociomaterial ontology is able to assist designers in creating understandable and robust conceptual models.

Resource, process, and use --- views on service modeling

Currently there exists a multitude of views of service creating problems for designers and users of models with respect to reasoning, description and classification of services. The diversity of conflicting views and definitions suggest that a multi-perspective approach is required to explicate the notion of service. The purpose of this paper is to introduce an integrated view of the service notion based on a literature survey. Our approach is to start with an analysis of service-as-a-resource and argue that this view will benefit from being complemented with a service-as-a-process view. These views are then integrated and represented in a conceptual model.

Institutional ontology for conceptual modeling

Conceptual models are intended to capture knowledge about the world. Hence, the design of conceptual models could be informed by theories about what entities exist in the world and how they are constituted. Further, a common assumption within the field of conceptual modeling is that conceptual models and information systems describe entities in the real world, outside the systems. An alternative view is provided by an ontological commitment that recognizes that the institutional world is constructed through language use and the creation of institutional facts. Such an ontological commitment implies that there is an institutional reality, which, to a great extent, is constructed using information infrastructures. Accordingly, conceptual models have not only a descriptive role but also a prescriptive one, meaning that modelers set up a framework of rules that restrict and enable people to construct institutional reality using information infrastructures. Understanding the prescriptive role of conceptual models may revive the area of conceptual modeling in the information systems research community. Reviving conceptual modeling through institutional modeling is motivated by the effect that implemented conceptual models have on information infrastructures and institutions. The purpose of this article is to propose an institutional ontology that can support the design of information infrastructures. The ontology is theoretically informed by institutional theory and a communicative perspective on information systems design, as well as being empirically based on several case studies. It is illustrated using a case study in the welfare sector. A number of guidelines for modeling institutional reality are also proposed.

CreatingWorlds with Words: Ontology-guided Conceptual Modeling for Institutional Domains

Conceptual modeling is often viewed as an activity of representing a preexisting world that should be faithfully mirrored in an information system. This view is adequate for modeling physical domains but needs to be revised and extended for social and institutional domains, as these are continuously produced and reproduced through communicative processes. Thereby, conceptual modeling moves beyond analysis and representation in order to cater also for design and creation. Following such a view on conceptual modeling, this paper proposes an ontology for modeling institutional domains. The ontology emphasizes the role of institutional entities in regulating and governing these domains through rules and rights that define allowed and required interactions. Furthermore, the ontology shows how these institutional entities are dependent on and grounded in material entities. Conceptual modelers can benefit from the ontology when modeling institutional domains, as it highlights fundamental notions and distinctions in these domains, e.g., the role of rights, the role of processes in creating institutional facts, and the difference between documents and institutional information. The ontology is illustrated using a case on public consultation management.

Towards a Model of Services Based on Cocreation, Abstraction and Rights Distribution

The term service is today defined and used in a multitude of ways, which are often ambiguous and contradictory. The absence of a commonly agreed-upon definition of the term makes it difficult to distinguish, describe and classify services. In order to address these issues, this chapter proposes a model of services that helps in analysing the concept. The model encompasses three perspectives: service as a means for cocreation of value, service as a means for abstraction and service as a means for distributing rights. The model does not suggest a definition of the term service but shows how the service concept can be analysed using a number of related concepts, like service resource, service process and service offering. The model has its theoretical foundation in the Resource-Event-Agent (REA) ontology and Hohfeld’s classification of rights.

Rights and Intentions in Value Modeling

In order to manage increasingly complex business and IT environments, organizations need effective instruments for representing and understanding this complexity. Essential among these instruments are enterprise models, i.e. com- putational representations of the structure, processes, information, resources, and intentions of organizations. One important class of enterprise models are value models, which focus on the business motivations and intentions behind business processes and describe them in terms of high level notions like actors, resources, and value exchanges. The essence of these value exchanges is often taken to be an ownership transfer. However, some value exchanges cannot be analyzed in this way, e.g. the use of a service does not influence ownership. The goal of this chapter is to offer an analysis of the notion of value exchanges, based on Hohfelds classification of rights, and to propose notation and practical modeling guidelines that make use of this analysis.