Asterio Kiyoshi Tanaka

The Ecobase project: database and web technologies for environmental information systems

A very large number of data sources on environment, energy, and natural resources are available worldwide. Unfortunately, users usually face several problems when they want to search and use relevant information. In the Ecobase project, we address these problems in the context of several environmental applications in Brazil and Europe. We propose a distributed architecture for environmental information systems (EIS) based on the Le Select middleware developed at INRIA. In this paper, we present this architecture and its capabilities, and discuss the lessons learned and open issues.

An architecture to support information sources discovery through semantic search

In most scenarios, different information sources coexist and their content overlap, thus requiring domain knowledge to discover, understand and integrate information. In general, information sources are not designed for integration and their descriptive metadata do not suffice to enable IIS to consistently and unambiguously discover which information sources contain the required data to be integrated. This paper proposes an architecture to discover information sources through the use of semantic search techniques on top of corporative metadata repositories. Our experiments using a prototype of the proposed architecture obtained positive results with regard to precision and recall.

GeoOlap: An Integrated Approach for Decision Support

The integration of information from different sources within the enterprise is one of the basis for implementing successful Decision Support Systems (DSS). Typically a DSS supplies analytical information obtained and transformed from large data warehouses. Recently, the geographical component of information has become more important due to the growing use of this type of information in logistics, marketing, and other applications. This work describes GeoOIap, a decision support approach that proposes a method to develop decision support applications that integrates analytical and georeferenccd elements from the ground up - at the design stage - and OLAP (On-Line Analytical Processing) and GIS (Geographical Information System) technologies to visualize the results. Additionally, this paper describes PostGeoOIap, an open source general-purpose tool, which supports GeoOlap and that allows developers to easily build decision support applications. A case study is presented to validate the proposed ideas.

Combining Mediator and Data Warehouse Technologies for Developing Environmental Decision Support Systems

Governmental and environmental agencies have recognized that data Warehouses (DWs) oriented to the environmental domain can have a deep impact on the ability to preserve the environment. However, extracting environmental data from external sources in order to load them into the data organization area of a DW is much more complex when compared with conventional DWs. In environmental DWs, extraction is frequently based on autonomous, heterogeneous external sources distributed over the Web. In order to improve this process, we propose an architecture that combines a middleware system and DW technology. The use of this architecture has been achieved through the implementation of a tool called LSExtract, which has been built on top of a middleware system called Le Select. Its goal is to locate and extract relevant and accurate information from heterogeneous data sources over the Web, extract data published by Le Select, and load it, after some transformations, into the data organization area of an environmental DW.

A SERVICE-BASED APPROACH FOR DATA INTEGRATION BASED ON BUSINESS PROCESS MODELS

Business-IT alignment is gaining more importance in enterprises, and is already considered essential for efficiently achieving enterprise goals. This led organizations to follow Enterprise Architecture approaches, with the Information Architecture as one of its pillars. Information architecture aims at providing an integrated and holistic view of the business information, and this requires applying a data integration approach. However, despite several works on data integration research, the problem is far from being solved. The highly heterogeneous computer environments present new challenges such as distinct DBMSs, distinct data models, distinct schemas and distinct semantics, all in the same scenario. On the other hand, new issues in enterprise environment, such as the emergence of BPM and SOA approaches, contribute to a new solution for the problem. This paper presents a service-based approach for data integration, in which the services are derived from the organization’s business process models. The proposed approach comprises a framework of different types of services (data services, concept services), a method for data integration service identification from process models, and a metaschema needed for the automation and customization of the proposed approach in a specific organization. We focus on handling heterogeneities with regard to different DBMSs and differences among data models, schemas and semantics.

ICT STRATEGIC PLANNING AT PUBLIC HIGHER EDUCATIONAL ORGANIZATIONS: BUILDING AN APPROACH THROUGH ACTION RESEARCH AT UNIRIO

This papers main contribution is the description of the process and experience in developing Information and Communication Technology strategic planning at a Brazilian public higher education institution. Action research was used as the scientific method and each of its research steps are presented. It also presents the instruments that were built for assessing organizational needs, the institutional diagnosis form, the required adaptations in the SISP ICT strategic planning model, as well as the reflections about the ICT strategic development process for this particular organizational context. The results evidence the feasibility of use and adaptability of the SISP ICT strategic planning model, enabling the effective ICT strategic development in similar contexts.

Agregação inteligente de RSS utilizando uma taxonomia construída colaborativamente

Continuous RSS content aggregation makes users to face problems caused by excess of information, such as the retrieval of low relevant items and the repetitive consumption of information about the same fact. Thats why intelligent RSS aggregators try to capture user wishes, applying content filtering and classification to aggregate only relevant information during the aggregation process. In this context, the intelligent aggregation process here described has the premise of using collaboration to construct a taxonomy of the terms and concepts extracted from the RSS items, allowing the user to select relevant subjects for aggregation. The validation of this process still depends on the development of a prototype and the analysis of the results of a case study to verify the quality of the aggregated content.