Xdata

Processing, Analysis, Exploration, and Sharing of Big and/or Complex Data

The continuing advances and increasing pervasiveness of simulation methods and data acquisition and processing tools enable us to measure and characterize natural and artificial objects, environments, and processes in ever greater detail and at ever higher generation rates. The fields of science, engineering, and technology are increasingly defined by data-driven approaches and need scalable solutions to make the most of the vast masses of information available. The study, development, and application of methods and technologies for processing, analyzing, exploring, and sharing massive and/or complex data are, therefore, at the heart of all strategic research plans, both at the European and National scales and for regional smart specialization.

CRS4 actively contributes to this field of research and has now achieved a leading role in the national landscape. The institutional project XDATA, funded by the contribution under art. 9 L.R. 20/2015, aims to consolidate and strengthen the center's activities in this strategic area and is divided into two parallel strands of activity:

The first stream, leveraging synergies with initiatives at the national and international scale in the field of visual and data-intensive computing, focuses on scalable, and where possible shared and interoperable, enabling methods and technologies for acquiring, creating, processing, distributing and exploring complex and/or massive datasets from simulations or measurements of real phenomena, objects, environments or processes. In particular, we will target our interest on: distributed computing, automation and machine learning solutions to improve the scalability of all processes; adaptive and intelligent visual computing methods for both the processing and understanding of geometric and visual data and their presentation; and management and sharing solutions based on data and process modeling using open formalisms, with a specific focus on the traceability and reproducibility of each process step. These general solutions will then be applied in vertical solutions in application areas that will include digital medicine, cultural heritage, and, more generally, digital science, engineering, and society.
The second strand, on the other hand, focuses on the remote sensing supply chain, where the need emerges for a systematic structuring of processes for managing information flows, whether derived from satellite observation, aerial sensing, or ground-based networks, and the establishment of a persistent information base of aggregation of the time series of interest, functional for feeding models in the domains of interest and for multi-scenario representation of geographic output. The development of data fusion methodologies in the different spectral ranges, in line with the activities of ongoing projects, also requires the study of operational-type processing methodologies, especially where real-time requirements may be relevant. Application areas will mainly address the issues of resource access and environmental sustainability.

Included in the project are specific activities targeting: research, development, and technology transfer; pilot studies; maintenance of dedicated research and development infrastructure; scientific dissemination; standardization activities; and other activities aimed at achieving greater integration with the scientific community and public and private entities.

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