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The answers to current our planet’s problems could be hidden in gigabytes of satellite imagery of the last 40 years, but scientists lack the means for processing such amount of data. To answer this challenge, we are building a scientific platform for handling big Earth observation data. We organized decades of satellite images into data cubes in order to put together data and analysis. Our platform allows to scale-up analysis to larger areas and longer periods of time. However, we need to provide scientists with tools and mechanisms to test and refine their routines before interacting with the Big data hosted in our platform. We believe that web services along collaborative analysis environments fit the hypothesis-test pattern followed by researchers while writing scientific computer code. Web services enable us to embed our platform’s data and algorithms into collaborative analysis environments such as Jupyter notebooks. To make our case, we prepared a Jupyter notebook where Earth observation scientists can interact with our platform through web services and the analytic capabilities of the programming language Python. Resumo. As respostas aos problemas globais atuais podem estar ocultas em gigabytes de imagens de satélite de observação da Terra adquiridas nos últimos 40 anos, mas nem sempre os cientistas possuem os meios para processá-las e transformá-las em informação. Para responder a esse desafio, estamos construindo uma plataforma cientı́fica para processar grandes volumes de dados de observação da Terra. Para isso, nós organizamos décadas de imagens de satélite em cubos de dados, a fim de juntar dados e análises. Nossa plataforma, está sendo concebida para permitir a anĺise de grandes ŕeas com dados de longos perı́odos de tempo mais longos. No entanto, precisamos fornecer aos cientistas ferramentas e mecanismos para testar e refinar suas rotinas antes de interagir com os dados hospedados em nossa plataforma. Acreditamos que os serviços Web e os ambientes de análise colaborativos encaixam com o padrão de hipótese-teste seguido pelos pesquisadores. Os serviços Proceedings XVIII GEOINFO, December 04th to 06nd, 2017, Salvador, BA, Brazil. p 7-16.

Reproducible geospatial data science: Exploratory data analysis using collaborative analysis environments