Combining Objects with Rules to Represent Aggregation Knowledge in Data Warehouse and OLAP Systems

Les entrepôts de données reposent sur la modélisation multidimensionnelle. A l'aide d'outils OLAP, les décideurs analysent les données à différents niveaux d'agrégation. Il est donc nécessaire de représenter les connaissances d'agrégation dans les modèles conceptuels multidimensionnels, puis de les traduire dans les modèles logiques et physiques. Cependant, les modèles conceptuels multidimensionnels actuels représentent imparfaitement les connaissances d'agrégation, qui (1) ont une structure et une dynamique complexes et (2) sont fortement contextuelles. Afin de prendre en compte les caractéristiques de ces connaissances, nous proposons de les représenter avec des objets (diagrammes de classes UML) et des règles en langage PRR (Production Rule Representation). Les connaissances d'agrégation statiques sont représentées dans les digrammes de classes, tandis que les règles représentent la dynamique (c'est-à-dire comment l'agrégation peut être effectuée en fonction du contexte). Nous présentons les diagrammes de classes, ainsi qu'une typologie et des exemples de règles associées.Agrégation ; Entrepôt de données ; Modèle conceptuel multidimensionnel ; OLAP ; Règle de production ; UML

Combining Objects with Rules to Represent Aggregation Knowledge in Data Warehouse and OLAP Systems

Data warehouses are based on multidimensional modeling. Using On-Line Analytical Processing (OLAP) tools, decision makers navigate through and analyze multidimensional data. Typically, users need to analyze data at different aggregation levels (using roll-up and drill-down functions). Therefore, aggregation knowledge should be adequately represented in conceptual multidimensional models, and mapped in subsequent logical and physical models. However, current conceptual multidimensional models poorly represent aggregation knowledge, which (1) has a complex structure and dynamics and (2) is highly contextual. In order to account for the characteristics of this knowledge, we propose to represent it with objects (UML class diagrams) and rules in Production Rule Representation (PRR) language. Static aggregation knowledge is represented in the class diagrams, while rules represent the dynamics (i.e. how aggregation may be performed depending on context). We present the class diagrams, and a typology and examples of associated rules. We argue that this representation of aggregation knowledge allows an early modeling of user requirements in a data warehouse project.Aggregation; Conceptual Multidimensional Model; Data Warehouse; On-line Analytical Processing (OLAP); Production Rule; UML

Chemical shift imaging from simultaneous acquisition of a primary and a stimulated echo

An imaging method is presented for obtaining chemical shift images from only one acquisition. Images are acquired with the same spatial resolution as in regular spin-echo imaging. The sequence is based on the simultaneous acquisition of a spin echo and a stimulated echo in a single pass. The use of 90 degrees radiofrequency pulse flip angles results in the same proton density, T2 and T1 weighting for the two echoes. Application of this sequence to chemical shift imaging is discussed for three fat suppression techniques (chopper, CHESS, and hybrid). Imaging was performed on phatoms and volunteers. The image quality was the same as those obtained by the chopper and the hybrid methods and the acquisition time was reduced by a factor of two

A Framework for Auditing Web-Based Information Systems

The last decade has seen an unprecedented rate of development of Web-Based Information System (WBIS). Enormous investment is currently being made in WBIS systems. There is a concern about whether the true capability of WBIS is being realized. As a consequence, growing attention is being paid to assessing the inherent contribution of WBIS. In this paper, we propose a WBIS audit methodology. The latter has two main features: 1) it structures the audit process as a hierarchical evaluation tree, using an Analytic Hierarchy Process model, 2) it allows the evaluation of a WBIS according to a specific set of criteria based on quality, security and readability requirements. Unlike past approaches, our methodology allows independent auditors, companies and users to minimize the time and effort needed to evaluate WBIS. It has been applied to a real-life example which is described in the paper, allowing us to validate our WBIS audit approach

Roundtrip engineering of NoSQL databases

International audienceIn this article we present a framework describing a roundtrip engineering process for NoSQLdatabase systems. This framework, based on the Model Driven Engineering approach, is composed of aknowledge base guiding the roundtrip process. Starting from a roundtrip generic scenario, we proposeseveral roundtrip scenarios combining forward and reverse engineering processes. We illustrate ourapproach with an example related to a property graph database. The illustrative scenario consists ofsuccessive steps of model enrichment combined with forward and reverse engineering processes. Futureresearch will consist in designing and implementing the main components of the knowledge base

Representation of Aggregation Knowledge in OLAP Systems

Decision support systems are mainly based on multidimensional modeling. Using On-Line Analytical Processing (OLAP) tools, decision makers navigate through and analyze multidimensional data. Typically, users need to analyze data at different aggregation levels, using OLAP operators such as roll-up and drill-down. Roll-up operators decrease the details of the measure, aggregating it along the dimension hierarchy. Conversely, drill-down operators increase the details of the measure. As a consequence, dimensions hierarchies play a central role in knowledge representation. More precisely, since aggregation hierarchies are widely used to support data aggregation, aggregation knowledge should be adequately represented in conceptual multidimensional models, and mapped in subsequent logical and physical models. However, current conceptual multidimensional models poorly represent aggregation knowledge, which (1) has a complex structure and dynamics and (2) is highly contextual. In order to account for the characteristics of this knowledge, we propose to represent it with objects and rules. Static aggregation knowledge is represented using UML class diagrams, while rules, which represent the dynamics (i.e. how aggregation may be performed depending on context), are represented using the Production Rule Representation (PRR) language. The latter allows us to incorporate dynamic aggregation knowledge. We argue that this representation of aggregation knowledge allows an early modeling of user requirements in a decision support system project. In order to illustrate the applicability and benefits of our approach, we exemplify the production rules and present an application scenario

ARTIFACT EVALUATION IN INFORMATION SYSTEMS DESIGN-SCIENCE RESEARCH – A HOLISTIC VIEW

Design science in Information Systems (IS) research pertains to the creation of artifacts to solve reallife problems. Research on IS artifact evaluation remains at an early stage. In the design-science research literature, evaluation criteria are presented in a fragmented or incomplete manner. This paper addresses the following research questions: which criteria are proposed in the literature to evaluate IS artifacts? Which ones are actually used in published research? How can we structure these criteria? Finally, which evaluation methods emerge as generic means to assess IS artifacts? The artifact resulting from our research comprises three main components: a hierarchy of evaluation criteria for IS artifacts organized according to the dimensions of a system (goal, environment, structure, activity, and evolution), a model providing a high-level abstraction of evaluation methods, and finally, a set of generic evaluation methods which are instantiations of this model. These methods result from an inductive study of twenty-six recently published papers

Diffusion imaging with a multi-echo MISSTEC sequence

An imaging method is presented to measure the water-diffusion coefficient. The sequence (MISSTEC) uses the simultaneous acquisition of a spin echo and several stimulated echoes with the same intensity except for diffusion weighting. The optimal number of stimulated echoes was calculated to minimize the diffusion coefficient error (D). D values obtained in vitro and in vivo were in good agreement with those from the spin-echo sequence (IntraVoxel Incoherent Motion [IVIM] method). The total acquisition time is half that of the classic IVIM method

Design issues in distributed management information systems.

Thesis. 1978. Ph.D.--Massachusetts Institute of Technology. Alfred P. Sloan School of Management.MICROFICHE COPY AVAILABLE IN ARCHIVES AND DEWEY.Includes bibliographical references.Ph.D

A pragmatic approach for identifying and managing design science research goals and evaluation criteria

International audienceThe effectiveness of a Design Science Research (DSR) project is judged both by the fitness of the designed artifact as a solution in the application environment and by the level of new research contributions. An important and understudied challenge is how to translate DSR project research goals into discrete and measurable evaluation criteria for use in the DSR processes. This position paper proposes an inclusive approach for articulating DSR goals and then identifying project evaluation criteria for these goals. The goals are organized hierarchically as utilitarian goals, safety goals, interaction and communication goals, cognitive and aesthetic goals, innovation goals, and evolution goals. Goals in a DSR project are identified pragmatically by considering the components of the context coupled with the hierarchy of goals. Based on the identified goals, the associated evaluation criteria are determined and organized along the same hierarchy. These criteria measure the ability of the artifact to meet its goals in itscontext (immediate fitness). Moreover, our approach also supports the innovation and research contributions of the project. The apex of the goal hierarchy addresses the identification of criteria measuring the fitness for evolution of the designed artifact, to accommodate for changes in goals or context