Donatello Elia

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The availability of systems able to process and analyse big amount of data has boosted scientific advances in several fields. Workflows provide an effective tool to define and manage large sets of processing tasks. In the big data analytics area, the Ophidia project provides a cross-domain big data analytics framework for the analysis of scientific,(More)
This work presents the I/O in-memory server implemented in the context of the Ophidia framework, a big data analytics stack addressing scientific data analysis of n-dimensional datasets. The provided I/O server represents a key component in the Ophidia 2.0 architecture proposed in this paper. It exploits (i) a NoSQL approach to manage scientific data at the(More)
The Ophidia project aims to provide a big data analytics platform solution that addresses scientific use cases related to large volumes of multidimensional data. In this work, the Ophidia software infrastructure is discussed in detail, presenting the entire software stack from level-0 (the Ophidia data store) to level-3 (the Ophidia web service front end).(More)
The analysis of large volumes of data is key for knowledge discovery in several scientific domains such as climate, astrophysics, life sciences among others. It requires a large set of computational and storage resources, as well as flexible and efficient software solutions able to dynamically exploit the available infrastructure and address issues related(More)
A case study on climate models intercomparison data analysis addressing several classes of multi-model experiments is being implemented in the context of the EU H2020 INDIGO-DataCloud project. Such experiments require the availability of large amount of data (multi-terabyte order) related to the output of several climate models simulations as well as the(More)
The need to apply complex algorithms on large volumes of data is boosting the development of technological solutions able to satisfy big data analytics needs in Cloud and HPC environments. In this context Ophidia represents a big data analytics framework for eScience offering a cross-domain solution for managing scientific, multi-dimensional data. It also(More)
In the context of the EU H2020 INDIGO-DataCloud project several use case on large scale scientific data analysis regarding different research communities have been implemented. All of them require the availability of large amount of data related to either output of simulations or observed data from sensors and need scientific (big) data solutions to run(More)
Climate and biodiversity systems are closely interlaced across a wide range of scales. To better understand the mutual interaction between climate change and biodiversity there is a strong need for multidisciplinary skills, tools and a large variety of heterogeneous, distributed data sources. In this regard, the EUBrazilCloudConnect project provides a(More)
The efficacy on bodyweight and the acceptability of a three month treatment with dexfenfluramine (Isoméride), combined with a prescribed diet, were evaluated in 336 women followed by a gynecologist for overweight. These women were divided into three groups, those in the sexually active age group (80%) and perimenopausal and post-menopausal women (20%) and(More)
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