Proposta de métricas para avaliação de desempenho de Infraestruturas de Dados Espaciais - IDEs

Abstract

In this dissertation, titled 'Proposal for Metrics for Performance Evaluation of Spatial Data Infrastructures (SDIs),' we developed innovative metrics to measure the effectiveness of SDIs, with a detailed focus on DataGEO, a significant Brazilian case study. This work underscores the growing importance of spatial data and the strategic role of SDIs in optimizing decision-making. To address the technical, organizational, and political challenges inherent in the governance of spatial data, we propose objective metrics to evaluate the performance of SDIs, aiming to deepen the understanding of their impacts and assist in strategic decision-making for their management and evolution. The methodology encompasses the analysis of existing literature and the implementation of performance indicators in various key areas, considering both efficiency and effectiveness. DataGEO, as a case study, provided a practical application of these metrics. The analysis of this specific case revealed significant insights about the practical utility of the metrics, demonstrating their effectiveness in evaluating and improving spatial data infrastructures. The research explores the applicability of these metrics in other SDI contexts, aiming to assess their universality and adaptability. The conclusions emphasize the importance of SDIs in the current scenario of geospatial information management and the need for consistent evaluations to optimize their performance and social impact. This study highlights the need for robust and adaptable metrics that can guide continuous improvements in SDIs and provide concrete evidence of the added value of these infrastructures. This dissertation is expected to significantly contribute to the field of Spatial Data Infrastructures, offering tools and knowledge that can be applied to enhance and advance these essential infrastructures in modern spatial data management. The detailed analysis of DataGEO as a case study demonstrates the effectiveness of the proposed metrics and paves the way for future applications and research in the field of SDIs.