AEGLE

The AEGLE project aimed to build an innovative ICT solution addressing the whole data value chain for health based on cloud computing enabling dynamic resource allocation, HPC infrastructures for computational acceleration and advanced
visualization techniques. 
AEGLE had the main goals:
- Realize a multiparametric platform using algorithms for analysing big biodata including features such as volume properties, communication metrics and bottlenecks, estimation of related computational resources needed, handling data versatility and managing velocity
- Address the systemic health big bio-data in terms of the 3V multidimensional space, using analytics based on PCA techniques
- Demonstrate AEGLE’s efficiency through the provision of aggregated services covering the 3V space of big biodata. Specifically it will be evaluated in: a)big biostreams where the decision speed is critical and needs non-linear and multi-parametric estimators for clinical decision support within limited time, b)big-data from non-malignant diseases where the need for NGS and molecular data analytics requires the combination of cloud located resources, coupled with local demands for data and visualization, and finally c)big-data from chronic diseases including EHRs and medication, with needs for quantified estimates of important clinical parameters, semantics’ extraction and regulatory issues for integrated care
- Bring together all related stakeholders, leading to integration with existing open databases, increasing the speed of AEGLE adaptation
- Build a business ecosystem for the wider exploitation and targeting on cross-border production of custom multilingual solutions based on AEGLE