Schema Vacuuming in Temporal Databases

Temporal databases facilitate the support of historical information by providing functions for indicating the intervals during which a tuple was applicable (along one or more temporal dimensions). Because data are never deleted, only superceded, temporal databases are inherently append-only resulting, over time, in a large historical sequence of database states. Data vacuuming in temporal databases allows for this sequence to be shortened by strategically, and irrevocably, deleting obsolete data. Schema versioning allows users to maintain a history of database schemata without compromising the semantics of the data or the ability to view data through historical schemata. While the techniques required for data vacuuming in temporal databases have been relatively well covered, the associated area of vacuuming schemata has received less attention. This paper discusses this issue and proposes a mechanism that fits well with existing methods for data vacuuming and schema versioning

A BPMN-Based Design and Maintenance Framework for ETL Processes

Business Intelligence (BI) applications require the design, implementation, and maintenance of processes that extract, transform, and load suitable data for analysis. The development of these processes (known as ETL) is an inherently complex problem that is typically costly and time consuming. In a previous work, we have proposed a vendor-independent language for reducing the design complexity due to disparate ETL languages tailored to specific design tools with steep learning curves. Nevertheless, the designer still faces two major issues during the development of ETL processes: (i) how to implement the designed processes in an executable language, and (ii) how to maintain the implementation when the organization data infrastructure evolves. In this paper, we propose a model-driven framework that provides automatic code generation capability and ameliorate maintenance support of our ETL language. We present a set of model-to-text transformations able to produce code for different ETL commercial tools as well as model-to-model transformations that automatically update the ETL models with the aim of supporting the maintenance of the generated code according to data source evolution. A demonstration using an example is conducted as an initial validation to show that the framework covering modeling, code generation and maintenance could be used in practice

Creation and management of versions in multiversion data warehouse

ABSTRACT A data warehouse (DW) provides an information for analytical processing, decision making, and data mining tools. On the one hand, the structure and content of a data warehouse reflects a real world, i.e. data stored in a DW come from real production systems. On the other hand, a DW and its tools may be used for predicting trends and simulating a virtual business scenarios. This activity is often called the what-if analysis. Traditional DW systems have static structure of their schemas and relationships between data, and therefore they are not able to support any dynamics in their structure and content. For these purposes, multiversion data warehouses seem to be very promising. In this paper we present a concept and an ongoing implementation of a multiversion data warehouse that is capable of handling changes in the structure of its schema as well as simulating alternative business scenarios

Design Patterns for Description-Driven Systems

In data modelling, product information has most often been handled separately from process information. The integration of product and process models in a unified data model could provide the means by which information could be shared across an enterprise throughout the system lifecycle from design through to production. Recently attempts have been made to integrate these two separate views of systems through identifying common data models. This paper relates description-driven systems to multi-layer architectures and reveals where existing design patterns facilitate the integration of product and process models and where patterns are missing or where existing patterns require enrichment for this integration. It reports on the construction of a so-called description-driven system which integrates Product Data Management (PDM) and Workflow Management (WfM) data models through a common meta-model.Comment: 14 pages, 13 figures. Presented at the 3rd Enterprise Distributed Object Computing EDOC'99 conference. Mannheim, Germany. September 199

Developing Predictive Molecular Maps of Human Disease through Community-based Modeling

The failure of biology to identify the molecular causes of disease has led to disappointment in the rate of development of new medicines. By combining the power of community-based modeling with broad access to large datasets on a platform that promotes reproducible analyses we can work towards more predictive molecular maps that can deliver better therapeutics

A Comparative Study: Change Detection and Querying Dynamic XML Documents

The efficient management of the dynamic XML documents is a complex area of research. The changes and size of the XML documents throughout its lifetime are limitless. Change detection is an important part of version management to identify difference between successive versions of a document. Document content is continuously evolving. Users wanted to be able to query previous versions, query changes in documents, as well as to retrieve a particular document version efficiently. In this paper we provide comprehensive comparative analysis of various control schemes for change detection and querying dynamic XML documents

Modélisation des transformations pour l'évolution de modèles multidimensionnels

La modélisation et l'entreposage des données ont constitué, depuis plus d'une décennie, une problématique de recherche pour laquelle différentes approches ont été proposées. Ces approches se focalisent sur des aspects statiques de l'entrepôt de données. Or, l'évolution du système d'information qui alimente un entrepôt peut avoir un impact sur ce dernier et peut conduire, par conséquent, à l'évolution de son modèle multidimensionnel. Dans ce contexte évolutif, nous proposons une démarche dirigée par les modèles pour automatiser la propagation de l'évolution du modèle de la source de données relationnelle vers l'entrepôt. Cette démarche est fondée sur deux modèles d'évolution ainsi qu'un ensemble de règles de transformation formalisées en Query/View/Transformation. Nous développons un prototype logiciel nommé DWE (« Data Warehouse Evolution ») qui supporte cette démarche

A Decathlon in Multidimensional Modeling: Open Issues and Some Solutions

The concept of multidimensional modeling has proven extremely successful in the area of Online Analytical Processing (OLAP) as one of many applications running on top of a data warehouse installation. Although many different modeling techniques expressed in extended multidimensional data models were proposed in the recent past, we feel that many hot issues are not properly reflected. In this paper we address ten common problems reaching from defects within dimensional structures over multidimensional structures to new analytical requirements and more