Abstract:The quest for interoperability is one of the main driving forces behind international organizations such as OGC and W3C. In parallel, a trend in systems design and development is to break down GIS functionalities into modules that can be composed in an ad hoc manner. This component-driven approach increases flexibility and extensibility. For scientists whose research involves geospatial analysis, however, such initiatives mean more than interoperability and flexibility. These efforts are progressively shielding these users from having to deal with problems such as data representation formats, communication protocols or pre-processing algorithms. Once scientists are allowed to abstract from lower level concerns, they can shift their focus to the design and implementation of the computational models they are interested in. This paper analyzes how interoperability and componentization efforts have this underestimated impact on the design and development perspective. This discussion is illustrated by the description of the design and implementation of WebMAPS, a geospatial information system to support agricultural planning and monitoring. By taking advantage of new results in the above areas, the experience with WebMAPS presents a road map to leverage system design and development by the seamless composition of distributed data sources and processing solutions.
This paper analyzes how interoperability and componentization efforts in the geospatial domain have an underestimated impact on the user perspective, directly affecting model development. This discussion is illustrated by the description of the design and implementation of WebMAPS, a geospatial information system to support agricultural planning and monitoring.
The exploration and production of oil and gas lead to many logistics challenges. In the case of the Brazilian offshore production, the operation size and the fact that the exploration occurs up to 300 km apart from the coast make these challenges even greater. There are many thousands of different types of materials, hundreds of suppliers, as well as hundreds of different destinations served by distinct routes. In short, this is a complex system, in which it is necessary to deal with an intrinsically combinatorial problem of sharing resources, such as warehouses, ports and means of transportation. Logistics processes need to deliver the materials in time, making sure that the production is not affected. In addition, operational costs and immobilized capital must be minimized. It is crucial to evaluate distribution probabilities for lead-times, identify bottlenecks and predict the effect of adopting specific policies for supply, picking and transportation. In order to address these issues, it is necessary to answer complex what-if queries that take into account the temporal relations, either specified or dictated by the process dynamics, between the events. Since all operations are logged, a substantial amount of historical data is generated. However, these data do not necessarily cover all situations, simply because certain feasible and relevant combinations of events may not have occurred during the period that data is logged. This motivates the use of simulations that generate huge amounts of data augmenting the (logged) historical data, and making big data analytics necessary. In this paper, we briefly describe the process of model building based on historical data as well as the construction of a simulation engine that permits efficient large scale simulations. The simulation results, together with the logged historical data are subjected to big data analytics in order to create global prediction models. The proposed methodology aims to answer complex what-if queries about the logistics processes with a high degree of efficiency and prediction accuracy. The software tool, based on this methodology, is designed so that a decision maker can interactively detect critical situations and study the global effect of changes in policies. Some examples of queries that can be supported by this research are: (i) estimation of distribution probabilities for lead-times under varied circumstances; and (ii) probability of critical materials shortage during periods of high demand.
Alexandre Oliva destaca-se dentre todas as pessoas que contribuíram, direta ou indiretamente, neste trabalho por três razões. Em primeiro lugar Oliva é a figura central na concepção e desenvolvimento do MOP de Guaraná, sobre o qual todo este trabalho se baseia. Em segundo lugar, Oliva contribuiu no conteúdo desta dissertação através de inúmeras discussões, sendo inclusive um dos principais revisores do texto. Em terceiro e último lugar, Oliva é amigo meu, por quem tenho profundo respeito e admiração.Luiz Eduardo Buzato, meu orientador, me convidou a fazer parte do seu time, acreditou no meu potencial mesmo durante as adversidades, e respeitou meu espaço vital intelectual. Por tudo isso, e pelo que não foi dito, obrigado.Agradeço a todos os colegas do LSD (Laboratório de Sistemas Distribuídos) pelas "viagens" intelectuais, pelo seu tempo e, sobretudo, pelas críticas.Fábio F. Silveira e Acauan P. Fernandes são duas pessoas que eu não conheço pessoalmente, apenas conheço eletronicamente. Muito obrigado pelas perguntas. A necessidade de outrem daquilo que se produz é um poderoso motivador.Oswaldo José Afonso Franziu e Marco Antônio Garcia Rossi, meus empregadores, sou grato a vocês por permitirem minha atuação na GPr Sistemas em tempo parcial, permitindo assim a minha pós-graduação. Sou grato a vocês por serem meus mentores na vida profissional extra-acadêmica. Não poderia ter tido melhores.A todos meus outros amigos eu agradeço por continuarem meus amigos sempre que eu dizia: "não posso porque tenho que trabalhar na dissertação".A meu irmão André, obrigado por ser meu melhor amigo. A meus pais, pelo exemplo e pelo apoio. Muito obrigado' VIl ResumoEsta dissertação traz contribuições teóricas e práticas. :\o plano teórico, apresentamos uma unificação da terminologia de Reflexão Computacional, onde introduzimos o termo para-objeto. Após a compilação de uma série de critérios para se classificar protocolos de meta-objetos (MOPs), analisamos comparativamente os :VIOPs mais expressivos até o ano 2000 utilizando a terminologia e os critérios propostos por nós. Enfatizamos os MOPs implementados sobre a Máquina Virtual Java. l\a fronteira entre o plano teórico e prático, analisamos detalhadamente o MOP de Guaraná, utilizando a terminologia e critérios propostos.O MOP de Guaraná é um protocolo de meta-objetos (MOP), idealizado por Alexandre Oliva, Luiz Eduardo Buzato e Islene Calciolari Garcia, que almeja simplicidade, flexibilidade, reuso de código de meta-nível e independência de linguagem de programação. l\esta dissertação também propomos um modelo de programação para o meta-nível. Segundo este modelo, enunciamos os problemas típicos na programação de meta-nível, a partir dos quais enumeramos técnicas para contorná-los.No plano prático é descrita a implementação de GDK: Guaraná Development Kit, constituído por um conjunto de ferramentas que implementam as técnicas propostas e que auxiliam a programação de meta-nível. Entre os componentes do GDK, existem utilitários para depuração e composição de meta-objetos.
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