Second (Final) Report on EPOS-ICS Architecture

This deliverable describes the ICS-C final architecture. Based on user satisfaction with the architectural design and simple prototype of EPOS-PP (Preparatory Phase) the initial architecture was defined. During the period M1-M18 of EPOS-IP (Implementation Phase) the architecture was refined based on interactions with the TCS and presented at EPOS project meetings. During the period M19-M36 progressive iterative prototypes driven by evolving user requirements and aspirations have been developed allowing the architecture to be specified in much more detail and the components refined and implemented. For some components (ICS-D, CES) implementation is continuing because this requires especially close working with the TCS. Detailed work has been undertaken validating the ICS-C against the evolving and increasingly ambitious user requirements and – in particular – collecting the metadata describing the assets in the TCS to populate the catalog. The architecture has been designed using the latest advances in metadata (for the catalog) and architectural approach (microservices). A consistent spiral, agile systems development method has been used. As part of this work the teams of WP6 and WP7 of EPOS – each spread across several organisations – have been integrated into a functioning unit with appropriate skills and abilities for the tasks. There has been some delay in recruitment to provide the human resources required but this has been overcome and the work is on schedule

Data integration and FAIR data management in Solid Earth Science

Integrated use of multidisciplinary data is nowadays a recognized trend in scientific research, in particular in the domain of solid Earth science where the understanding of a physical process is improved and made complete by different types of measurements – for instance, ground acceleration, SAR imaging, crustal deformation – describing a physical phenomenon. FAIR principles are recognized as a means to foster data integration by providing a common set of criteria for building data stewardship systems for Open Science. However, the implementation of FAIR principles raises issues along dimensions like governance and legal beyond, of course, the technical one. In the latter, in particular, the development of FAIR data provision systems is often delegated to Research Infrastructures or data providers, with support in terms of metrics and best practices offered by cluster projects or dedicated initiatives. In the current work, we describe the approach to FAIR data management in the European Plate Observing System (EPOS), a distributed research infrastructure in the solid Earth science domain that includes more than 250 individual research infrastructures across 25 countries in Europe. We focus in particular on the technical aspects, but including also governance, policies and organizational elements, by describing the architecture of the EPOS delivery framework both from the organizational and technical point of view and by outlining the key principles used in the technical design. We describe how a combination of approaches, namely rich metadata and service-based systems design, are required to achieve data integration. We show the system architecture and the basic features of the EPOS data portal, that integrates data from more than 220 services in a FAIR way. The construction of such a portal was driven by the EPOS FAIR data management approach, that by defining a clear roadmap for compliance with the FAIR principles, produced a number of best practices and technical approaches for complying with the FAIR principles. Such a work, that spans over a decade but concentrates the key efforts in the last 5 years with the EPOS Implementation Phase project and the establishment of EPOS-ERIC, was carried out in synergy with other EU initiatives dealing with FAIR data. On the basis of the EPOS experience, future directions are outlined, emphasizing the need to provide i) FAIR reference architectures that can ease data practitioners and engineers from the domain communities to adopt FAIR principles and build FAIR data systems; ii) a FAIR data management framework addressing FAIR through the entire data lifecycle, including reproducibility and provenance; and iii) the extension of the FAIR principles to policies and governance dimensions.publishedVersio