Using Network Model Represent Metadata in Data Warehouse

Using network model metadata representation have becomes a necessity not only for better knowledge, but also to handle the overall database of a huge numbers of information This work is aimed at represent metadata using network model. A model network is prepared using the entity which is present in the database

An ETL Metadata Model for Data Warehousing

Metadata is essential for understanding information stored in data warehouses. It helps increase levels of adoption and usage of data warehouse data by knowledge workers and decision makers. A metadata model is important to the implementation of a data warehouse; the lack of a metadata model can lead to quality concerns about the data warehouse. A highly successful data warehouse implementation depends on consistent metadata. This article proposes adoption of an ETL (extracttransform-load) metadata model for the data warehouse that makes subject area refreshes metadata-driven, loads observation timestamps and other useful parameters, and minimizes consumption of database systems resources. The ETL metadata model provides developers with a set of ETL development tools and delivers a user-friendly batch cycle refresh monitoring tool for the production support team

A Catalog of Reusable Design Decisions for Developing UML/MOF-based Domain-specific Modeling Languages

In model-driven development (MDD), domain-specific modeling languages (DSMLs) act as a communication vehicle for aligning the requirements of domain experts with the needs of software engineers. With the rise of the UML as a de facto standard, UML/MOF-based DSMLs are now widely used for MDD. This paper documents design decisions collected from 90 UML/MOF-based DSML projects. These recurring design decisions were gained, on the one hand, by performing a systematic literature review (SLR) on the development of UML/MOF-based DSMLs. Via the SLR, we retrieved 80 related DSML projects for review. On the other hand, we collected decisions from developing ten DSML projects by ourselves. The design decisions are presented in the form of reusable decision records, with each decision record corresponding to a decision point in DSML development processes. Furthermore, we also report on frequently observed (combinations of) decision options as well as on associations between options which may occur within a single decision point or between two decision points. This collection of decision-record documents targets decision makers in DSML development (e.g., DSML engineers, software architects, domain experts).Series: Technical Reports / Institute for Information Systems and New Medi

A platform to support object database research

Databases play a key role in an increasingly diverse range of applications and settings. New requirements are continually emerging and may differ substantially from one domain to another, sometimes even to the point of conflict. To address these challenges, database systems are evolving to cater for new application domains. Yet little attention has been given to the process of researching and developing database concepts in response to new requirements. We present a platform designed to support database research in terms of experimentation with different aspects of database systems ranging from the data model to the distribution architecture. Our platform is based on the notion of metamodel extension modules, inspired by proposals for adaptive and configurable database management systems. However, rather than building a tailored system from existing components, we focus on the process of designing new components. To qualitatively evaluate our platform, we present a series of case studies where our approach was used successfully to experiment with concepts designed to support a variety of novel application domains

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

Model-driven development of Data Vault based data warehouses.

U tezi je razmatrano više problema vezanih za projektovanje i razvoj skladišta podataka, kao što su: - neusaglašenost skladišta podataka sa izvorima podataka, nastala kao rezultat permanentnih promena strukture izvora, - nekompletnost podataka u skladištu podataka, - heterogenost modela izvora i njihova semantička neusaglašenost - nepostojanje standardnog konceptualnog modela i modela strukture skladišta podataka...Several issues, related to the design and development of data warehouses, are analyzed in this thesis: - inconsistency between the data warehouse and data sources due to the permanent changes in the structure of the data sources, - incompleteness of the stored data, - heterogeneity of data source models and their semantic inconsistency, - absence of standardized conceptual or structural data warehouse models..

Diseño de un Almacén de Datos Históricos en el marco del desarrollo de software dirigido por modelos

Un Decision Support System (DSS) asiste a los usuarios en el proceso de análisis de datos en una organización con el propósito de producir información que les permita tomar mejores decisiones. Los analistas que utilizan el DSS están más interesados en identificar tendencias que en buscar algún registro individual en forma aislada [HRU96]. Con ese propósito, los datos de las diferentes transacciones se almacenan y consolidan en una base de datos central denominada Data Warehouse (DW); los analistas utilizan esas estructuras de datos para extraer información de sus negocios que les permita tomar mejores decisiones [GHRU97]. Basándose en el esquema de datos fuente y en los requisitos de información de la organización, el objetivo del diseñador de un DSS es sintetizar esos datos para reducirlos a un formato que le permita, al usuario de la aplicación, utilizarlos en el análisis del comportamiento de la empresa. Dos tipos diferentes (pero relacionados) de actividades están presentes: el diseño de las estructuras de almacenamiento y la creación de consultas sobre esas estructuras. La primera tarea se desarrolla en el ámbito de los diseñadores de aplicaciones informáticas; la segunda, en la esfera de los usuarios finales. Ambas actividades, normalmente, se realizan con escasa asistencia de herramientas automatizadas. A partir de lo expresado anteriormente Identificamos, por consiguiente, tres problemas a resolver: a) la creación de estructuras de almacenamiento eficientes para la toma de decisión, b) la simplificación en la obtención de la información sobre esas estructuras para el usuario final y, c) la automatización, tanto del proceso de diseño de las estructuras de almacenamiento, como en la elaboración iterativa de consultas por parte del usuario de la aplicación. La solución propuesta es el diseño de una nueva estructura de almacenamiento que denominaremos Historical Data Warehouse (HDW) que combina, en un modelo integrado, un Historical Data Base (HDB) y un DW; el diseño de una interface gráfica, derivada del HDW, que permite realizar consultas en forma automática y, por último, el desarrollo de un método de diseño que engloba ambas propuestas en el marco del Model Driven Software Development (MDD).Facultad de Informátic

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains