Diastema proposes an integrated environment for big data project development and management. It aims to meet the needs of big data technologies by providing “Data as a Service”. The primary target of this project is the effective and efficient use of all resources to fulfill the needs of its services. The eventual goal is the transformation of raw data into valuable information, which is achieved through a series of decisions, depending on the data requirements at each stage of the overall process.

The integrated infrastructure management environment consists of 5 different implementation layers that make up a full stack that facilitates data and application needs and are the following:

  • The foundations of the project, which are defined by the containers used for the data processing technologies and databases.
  • The User Interface with the set of technologies that enable data scientists to implement their data requirements and constraints.
  • The provision of “Data as a Service” in an efficient and flexible way, through data analysis and processing techniques using modern machine learning technologies.
  • The Process Modeling, that predicts the required data services, the required resources and maps the processes.
  • The Data Visualization, that refers to the environment that goes beyond the simple representation of data and its analysis, leading to customized visualizations in an automatic way according to the analysis of the applications and the semantics of the data.
Project Architecture

Diastema runs two pilot cases which cover different fields. The results are evaluated in heterogeneous environments, demonstrating the applicability and re-usability of the developed models and tools in different domains.

The first scenario is implemented using the platform of BioAssist and aims to effectively manage healthcare data. The second scenario aims to the effective management of digital shipping and uses the platform of Metis, that provides the integrated management of shipping resources, with the collection and analysis of data such as weather phenomena, cargo handling, fuel consumption, environmental protection and overall ship operation.

The implementation team consists of of four collaborating entities, with previous experience in National and European research projects. One of the participants is BioAssist, where in collaboration with the University of Piraeus Research Center, Ubitech and Metis, they compose a group of established executives in the IT field, with an extremely high level of academic education and many years of experience in their subject in similar projects.