Change Management in Large-Scale Enterprise Information Systems

Abstract. The information infrastructure in today’s businesses consists of many interoperating autonomous systems. Changes to a single system can therefore have an unexpected impact on other, dependent systems. In our Caro approach we try to cope with this problem by observing each system participating in the infrastructure and analyzing the impact of any change that occurs. The analysis process is driven by declaratively defined rules and works with a generic and ex-tensible graph model to represent the relevant metadata that is subject to changes. This makes Caro applicable to heterogeneous scenarios and customizable to spe-cial needs.

Evolving information systems: meeting the ever-changing environment

To meet the demands of organizations and their ever-changing environment, information systems are required which are able to evolve to the same extent as organizations do. Such a system has to support changes in all time-and application-dependent aspects. In this paper, requirements and a conceptual framework for evolving information systems are presented. This framework includes an architecture for such systems and a revision of the traditional notion of update. Based on this evolutionary notion of update (recording, correction and forgetting) a state transition-oriented model on three levels of abstraction (event level, recording level, correction level) is introduced. Examples are provided to illustrate the conceptual framework for evolving information systems

Lattice-structured Domains, Imperfect Data and Inductive Queries

. The relational model, as proposed by Codd, contained the concept of relations as tables composed of tuples of single valued attributes taken from a domain. In most of the early literature this domain was assumed to consist of elementary items such as simple (atomic) values, dened complex data types or arbitrary length binary objects. Subsequent to that the nested relational or non-rst normal form model allowing set-valued or relation-valued attributes was proposed. Within this model an attribute could take multiple values or complete relations as values. This paper presents a further extension to the relational model which allows domains to be dened as a hierarchy (specically a lattice) of concepts, shows how dierent types of imperfect knowledge can be represented in attributes dened over such domains, and demonstrates how lattices allow the accommodation of some forms of inductive queries. While our model is applied to at relations, many of the results given are applicable also to nested relations. Necessary extensions to the relational algebra and SQL, a justication for the extension in terms of application areas and future research areas are also discussed.