The Internet and related technologies have created enormous potential for disruptive innovations. Businesses engaging in e-commerce must constantly be examining opportunities and threats arising from disruptive change. Modeling techniques have been introduced to help visualize and reason about business models and strategies. This paper offers a modeling approach which characterizes a business model not in terms of flows or exchanges, but the strategic dependencies among various players. The business model is then analyzed in relation to the high-level strategy of the business. When a change arises, competitive scenarios are analyzed in terms of the strategic choices for the incumbent and new entrants. A historical case study from the telecom sector is used to illustrate.

We present details of a goal-oriented process for database requirements analysis. This process consists of a number of steps, spanning the spectrum from high-level stakeholder goal analysis to detailed conceptual schema design. The paper shows how goal modeling contributes to systematic scoping and analysis of the application domain, and subsequent formal specification of database requirements based on this domain analysis. Moreover, a goal-oriented design strategy is proposed to structure the transformation from the domain model to the conceptual schema, according to a set of user defined design issues, also modeled as goals. The proposed process is illustrated step-by-step using a running example from the design of a real-world, industrial biological database. We also report early progress towards building full tool support, by presenting a prototype that captures and stores design sessions in a queryable form. This facility makes it possible to answer questions that are hard, if not impossible, to answer using existing methodologies for database design.

We present a case study of a real-world industrial application which produced several versions of conceptual schema design for a biological database during its evolution. We apply the techniques of early requirements analysis to produce a goal model of the problem domain. We then show that by incorporating goal analysis in the design process we can account for the original schemas by tracing them back to stakeholder goals. Moreover, the goal-oriented analysis supports the systematic examination of the space of design alternatives, and better explains what the output of the design process (a conceptual schema) really means. Our results advocate the need for an extended design methodology for databases driven by stakeholder goals

In this paper we present a method for applying data warehouse and on-line analytical processing concepts to gene expression data management. This method has been employed in developing the data management system that is used to host Gene Logic's GeneExpress(R) database products.

This paper addresses the problem of physical query processing for large object-oriented, temporal knowledge bases. The major tasks being investigated are how to generate the space of all possible execution plans for a given knowledge base query and how to traverse this space in order to choose an efficient execution plan. The results of this work include: (a) the formulation of a set of access level operations which depend on the underlying storage model and the development of a cost model for estimating their cost; (b) the exploration of various optimization heuristics for selecting efficient execution plans for temporal path queries which make use of the join index relations that are provided by the storage model; and (c) a performance study that shows the benefits of join index based query processing techniques for knowledge bases compared to the traditional tuple-oriented (characteristic of the AI-DB coupling systems) and bulk join query processing approaches in database systems. ...

Secondary memory storage plays a major role in making large knowledge bases usable.This paper presents such a storage architecture for knowledge bases.In particular, the Controlled Decomposition Model, a flexible storage model which takes into account the numerous and expressive features of the knowledge representation model is defined.Second, the indexing problem for the knowledge base context 1s examined and the Temporal Join Index is proposed.An implementation technique for temporal indices, based on a spatial access method, is presented.Finally, an analytical and experimental performance study is conducted to account the performance limits of the proposed methods.

The authors describe a framework for query optimization for knowledge base management systems (KBMSs) based on the knowledge representation language Telos. The framework involves temporal and syntactic simplifications and semantic modification of the queries. Temporal simplification attempts to select parts of a knowledge base that are relevant to a query from a temporal viewpoint. Syntactic simplification exploits structural properties of the data model and attempts to transform the query into an equivalent and more efficient one. Semantic transformation uses knowledge specific to the application domain to transform a user-specified query into another form which gets the same answer and is processed efficiently. The three steps were integrated into a global algorithm for query optimization that utilizes all features of the considered KBMS.>