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Citizen science has emerged as a potent approach for environmental monitoring, leveraging the collective efforts of volunteers to gather data at unprecedented scales. Within the framework of the I-CHANGE project, MeteoTracker, a citizen science initiative, was employed to collect meteorological measurements. Through MeteoTracker, volunteers contributed to a comprehensive dataset, enabling insights into local weather patterns and trends. This paper presents the analysis and the results of the validation of such observations against the official Italian civil protection in situ weather network, demonstrating the effectiveness of citizen science in generating valuable environmental data. The work discusses the methodology employed, including data collection and statistical analysis techniques, i.e., time-series analysis, spatial and temporal interpolation, and correlation analysis. The overall analysis highlights the high quality and reliability of citizen-generated data as well as the strengths of the MeteoTracker platform. Furthermore, our findings underscore the potential of citizen science to augment traditional monitoring efforts, inform decision-making processes in environmental research and management, and improve the social awareness about environmental and climate issues. [ABSTRACT FROM AUTHOR]

A full hydro-meteorological (HM) simulation, from rainfall to impact on urban areas, is a multidisciplinary activity which consists in the execution of a workflow composed by complex and heterogeneous model engines. Moreover an extensive set of configuration parameters have to be selected consistently among the models, otherwise the simulation can fail or produce unreliable results. The DRIHM portal is a Web-based science gateway aiming to support HM researchers in designing, executing and managing HM simulations. The first version of the portal was developed during the DRIHM project using the gUSE science gateway toolkit. The lesson we learned is guiding a refactoring process that, together with a review of the most relevant technologies for the development of a science gateway, represent the focus of this paper. Beside the technological aspects, the need of a strong interplay between ICT and other domain-specific communities clearly emerged, together with coherent policies in the management of data, computational resources and software components that represent the ecosystem of a science gateways. [ABSTRACT FROM AUTHOR]

Extreme hydrometeorological events such as flash floods have caused considerable loss of life and damage to infrastructure over recent years. Flood events in the Mediterranean region between 1990 and 2006 caused over 4,500 fatalities and cost over €29 billion in damage, with Italy one of the worst affected countries. The Distributed Computing Infrastructure for Hydro-Meteorology (DRIHM) project is a European initiative aiming at providing an open, fully integrated eScience environment for predicting, managing, and mitigating the risks related to such extreme weather phenomena. Incorporating both modeled and observational data sources, it enables seamless access to a set of computing resources with the objective of providing a collection of services for performing experiments with numerical models in meteorology, hydrology, and hydraulics. The purpose of this article is to demonstrate how this flexible modeling architecture has been constructed using a set of standards including the NetCDF and WaterML2 file formats, in-memory coupling with OpenMI, controlled vocabularies such as CF Standard Names, ISO19139 metadata, and a Model MAP (Metadata, Adaptors, Portability) gateway concept for preparing numerical models for standardized use. Hydraulic results, including the impact to buildings and hazards to people, are given for the use cases of the severe and fatal flash floods, which occurred in Genoa, Italy in November 2011 and October 2014. [ABSTRACT FROM AUTHOR]

A full hydrometeorological (HM) simulation, from rainfall to impact on urban areas, is a multidisciplinary job, which relies on the execution of a workflow composed of complex and heterogeneous model engines. Moreover, the accuracy of the simulation is strongly dependent on an extensive set of configuration parameters, which have to be selected in a consistent way among the models. Within the Distributed Research Infrastructure for Hydro-Meteorology project, a Web-based science gateway was developed with the aim to support HM researchers in designing, executing, and managing HM experiments. The core of this science gateway is the portal, which takes care of generating all the configuration files and handles the execution of simulation steps on a heterogeneous computing infrastructure composed of high-performance computing, Grid resources, and Cloud resources. This paper presents technological insights about the implementation of the portal, with an analysis of the adopted technologies and infrastructures. Our experience highlights the need of coherent policies in the management of data, computational resources, and software components that represent the ecosystem to develop science gateways. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Hybrid Clouds seems able to offer their customers with differentiate solutions capable of providing more and personalized guarantees with respect to the basic service availability generally supplied. In the context of an Italian research project aimed to transfer ICT advancements from research centers towards ICT SMEs, the paper focuses on the design of a brokering tool for hybrid clouds capable to adequately respond to specific Quality of Service (QoS) constraints. Aimed at satisfying the highest number of user requests while trying maximizing the profit of the private provider, in the context of a posted price economic model, the proposed brokering algorithm may apply different allocation policies, based on the reservation of a quota of private resources to high-level QoS applications. [ABSTRACT FROM AUTHOR]

The Tissue MicroArray (TMA) technique is assuming even more importance. Digital images acquisition becomes fundamental to provide an automatic system for subsequent analysis. The accuracy of the results depends on the image resolution, which has to be very high in order to provide as many details as possible. Lossless formats are more suitable to bring information, but data file size become a critical factor researchers have to deal with. This affects not only storage methods but also computing times and performances. Pathologists and researchers who work with biological tissues, in particular with the TMA technique, need to consider a large number of case studies to formulate and validate their hypotheses. It is clear the importance of image sharing between different institutes worldwide to increase the amount of interesting data to work with. In this context, preserving the security of sensitive data is a fundamental issue. In most of the cases copying patient data in places different from the original database is forbidden by the owner institutes. Storage, computing and security are key problems of TMA methodology. In our system we tackle all these aspects using the EGEE (Enabling Grids for E-sciencE) Grid infrastructure. The Grid platform provides good storage, performance in image processing and safety of sensitive patient information: this architecture offers hundreds of Storage and Computing Elements and enables users to handle images without copying them to physical disks other than where they have been archived by the owner, giving back to end-users only the processed anonymous images. The efficiency of the TMA analysis process is obtained implementing algorithms based on functions provided by the Parallel IMAge processing Genoa Library (PIMA(GE)2 Lib). The acquisition of remotely distributed TMA images is made using specialized I/O functions based on the Grid File Access Library (GFAL) API. In our opinion this approach may represent important contribution to tele-pathology development. [ABSTRACT FROM AUTHOR]