SCIENTIFIC METHODOLOGY AND WORK PACKAGES
DITAS consists of 7 work packages. A detailed work plan has been generated that adequately structures the efforts into manageable:
Requirement, Architecture and Validation Approach
- Analyse market, technical and SotA requirements to refine DITAS outcomes.
- Identify, engage and consult different types of stakeholders to understand how they expect to interact with the DITAS resulting outcomes: tools/framework/etc.
- Identify core technologies (standards, formats), projects and initiatives that are related to DITAS and create the foundation for collaboration.
- Analyse and define technical needs and constraints to specify technical requirements for the DITAS project.
- Provide the general approach to follow for verifying and validating the DITAS outcomes and architecture from component testing to Use Case validation.
Enhanced data management
- The definition of the data utility concept which drives the enhanced data management based on data virtualization (see WP3) able to take into account data scattered on different devices and inside federated cloud infrastructures and paying regard to security and privacy issues.
- A set of data movement strategies defined in terms of how data utility changes in case such mechanisms are enacted.
- A data utility-driven data storage to make the access to data across a federated infrastructure more efficient while ensuring that specified security- and privacy-related requirements are automatically fulfilled.
- The definition of the Virtual Data Container concept.
- Tools to support the development and deployment of cloud-based/data-intensive applications implementing the VDC paradigm for abstracting from the intricacies of the different platforms, storages systems, and network capabilities.
- Tools for taking advantage of a federated infrastructure of the data, allowing the application to leverage the best of locality and the Cloud.
- Modeling of application characteristics in order to satisfy the performance, security, and reliability requirements expressed in terms of data utility.
- A data movement enactor that, based on the information collected by the monitoring system, is able to select the most suitable data movement techniques.
- A distributed monitoring and analytics system that is able to collect information about how the application behaves with respect to the data management.
- An execution engine able to support the execution and the adaptation – through computational movement – of data-intensive application distributed among on-premises and on cloud resources.
- An Auditing and Compliance framework which will enforce data security and privacy policies across the DITAS architecture.
Real world case studies and integration
- To support the deployment and the integration of the results of the other WPs.
- To bring into action the DITAS framework for two real world use cases: Industry 4.0 and e-Health, where the data utility, and VDCs will be tested as design pattern and wrapper to address scenarios of complex access to data sources with different requirements.
- To test the technical implementation of the DITAS runtime environment as an efficient framework to address operational “devops” in terms of data movement and processing balancing local node and cloud computing models.
Impact, Communication, and Dissemination
- Maximize impact and knowledge transfer on scientific, academic and research communities with dissemination and training; collaboration and standardization strategies.
- Maximize impact in a wider audience by using communication actions in the market and stakeholders audiences to leverage awareness; engagement and uptake as a support tool for impact creation which maximizes engagement with stakeholders in the IoT ecosystem.
- Developing parallel routes that help maximizing impact by generating individual exploitation; fostering innovation and potential creation of business models with use case value extension; defining and implementing a long-term sustainability approach (and the necessary structure and resources) that ensure sustainability and community development; and nurturing opportunities with the innovation management process.
Project Management and Collaboration
- Manage and review all technical and research project tasks for successful achievement of the project goals, with reference to the technical and research objectives in term of concept definition, design, performances, timely delivery and validation.
- Ensure a timely financial monitoring and control of the project according to the conditions of the Contract.
- Define and monitor quality standards for the whole project.
- Define and implement communications procedures within the project and with external agents.
- Schedule and organise project meetings.
- Innovation management.