D3.1 VA architecture (Application and Technical)

The objective of the AIDAVA project is to prototype an intelligent virtual assistant that will maximise automation in data curation & publishing of heterogeneous personal health data while empowering individual patients when automation is not possible due to lack of contextual information. The solution includes a backend and a frontend described in the solution design (see Deliverable D2.3. Solution Design).
This deliverable focuses on the technical and data architecture of the AIDAVA prototype and on its deployment, integration and testing with the different evaluation sites.
As the consortium intends to develop a reusable prototype, we first clarify the difference between product and prototype and confirm the importance of taking into account product constraints in the technical architecture to ensure reuse. We also define a set of architecture principles that guided the elaboration of the deliverable.
The technical framework relies on a microservices-based structure, encompassing numerous satellite applications and curation tools. These components will be seamlessly integrated to facilitate the automation process using predefined workflows that incorporate workflow orchestration tools. Additionally, the architecture encompasses connectivity with various medical partners. In this context, the system will acquire input data from file shares or databases and establish connections with health data intermediaries, receiving data either through API endpoints or by utilising SDKs.
The data architecture expands on the components identified in the solution design deliverable, from an implementation perspective.
As the AIDAVA project aims to test the solution in real life with real patients consenting to manage and curate their data, an important part of this deliverable relates to integration in the different evaluation sites, the needed hardware as well as deployment and testing.
This technical architecture is the consolidation of 1 year of efforts across different teams. It provides the consortium with a solid description of the solution that needs to be implemented to successfully meet the objectives of the project. While there are challenges ahead, there is confidence that the first generation (G1) of the prototype can be successfully developed and deployed. The technical architecture - and this document - will be updated for Generation 2 (G2) of the prototype, taking into account the results of the evaluation by patients and clinical sites, the need to integrate more powerful NLP curation tools and an improved human computer interaction front end developed in other work packages of the project.