The AI4EOSC project is scheduled for a total duration of 36 months. Its structure is designed to organize the work of the different partners in a coherent way as follows.
WP1 will perform the global oversight of the activities carried out within the project, ensuring that they are aligned with the AI4EOSC work plan, dealing with the management of the whole project management activities. WP2 will encompass the innovation and exploitation activities of the project, as well as the interaction with relevant projects under the EOSC and AI4EU realms. WP3 will tackle the requirement elicitation and the elaboration and refinement of the final AI4EOSC architecture, that will set the basis of the activities carried out by WP4 and WP5; interacting closely with WP6, that will lead the integration of the selected use cases to carry out co-design activities.Finally, WP7 deals with the quality of the software, service and data management aspects of the project, ensuring that the FAIRness of data is assessed and enforced.
The work plan schedule is divided in two different stages, delivering two incremental integrations carried out by the AI4EOSC project.
- The first stage is aimed at delivering a first platform providing customization capabilities as well as an improved provisioning and training layer. We will carry out the base integration of the platform with the EOSC-core services and other EOSC services, integrating as well an initial set of applications from those included in WP6.
- The second stage will refine the integration carried out in the 1st stage of the project, in order to fully integrate all the defined use cases and incorporate any further requirements that might have arisen. This phase will include a boost in the dissemination efforts (in the form of workshops of hackathons), in order to onboard external and additional use cases into the platform. During this phase we will deliver the final integration of the services in the EOSC portal, as they will reach a high TRL during this period.
This project has received funding from the European Union’s Horizon Research and Innovation programme under Grant agreement No. 101058593