The Doris team is working on several key objectives to achieve the objectives for a FAIR data management within HPMC research data.

Accessibility and access rights, data security and sovereignty New user models to reuse very large data sets are being developed and supported by new or adjusted software, for instance to extract and harvest metadata, to post-process simulation or measurement data and to replicate data via containerization tools. Corresponding front ends, interfaces and documentations have to be provided in collaboration with infrastructure participants like LRZ, HLRS and JSC, as well as appropriate access rights, security and sovereignty mechanisms and a (creative commons) license system.

Support for third-party users & community-based training, provision of post-processing algorithms and modules To increase the acceptance of and the contribution to the developments created in NFDI4Ing, tutorials and workshops will be provided to the community along with the project progress and software development. Existing tools will be evaluated and adjusted to facilitate data provision, access and reuse for primary scientists as well as third-party users. Support and training will be supplied in close coordination with base services and community clusters.

Metadata definitions & terminologies, support to data-generating groups For HPC users, not only the physical relevant parameters and procedures have to be included in the metadata, but also information on how the data were exactly generated (exact specifications of the numerical method, boundary conditions, initial conditions, etc.). To reach maximum performance on the HPC systems, vendor-specific software on many levels (IO, optimization directives and procedures, memory-specific access, etc.) as well as special programming techniques are used. Together with the task area Base Services S-3, we will develop metadata standards, terminologies and a sub-ontology, enabling other researchers to find, interpret and reuse the data. In cooperation with pilot users, best-practice guidelines on metadata and terminologies are getting compiled.

Storage & archive for very large data Along with the involved service and infrastructure providers, methods and capabilities will be developed to store and archive these large data volumes. In accordance with Base Service S-4 “Storage and archive for very large data” front-end solutions will be implemented, providing searchable and accessible metadata information together with persistent URLs and DOIs.

Reproducibility on large-scale high-performance systems Reproducibility on large-scale and unique high-performance systems is an unsolved problem. Unlike in experiments, a standard is missing that would describe the level of reproducibility, which in turn may depend on the hardware and software platforms used. This conflict will be addressed defining minimum standards for reproducibility issues. Together with the system providers and pilot users, the efficiency of software containers will be evaluated for HPC environments. Best practice guidelines for reproducibility will be developed and published for HPMC users.