Use cases

Use case class 1: Validating and publishing scientific data collections

Scientific data collections produced by individuals or science collaborations are more valuable when made available to the broader community in a manner consistent with the FAIR principles. Doing so requires efficient tools for making the data accessible through standard protocols for selection and retrieval. Support is also needed for metadata provision, minting DOIs, etc. Furthermore, infrastructure is needed to create workflows that can be used for vetting such data for publication and subsequent analysis. The availability of these data collections would then enable new cross-experiment/cross-collaboration data sharing, ultimately leading to new scientific discoveries.

Use case class 2: analysis of local or distributed data sets

Analysing distributed or local data sets consitutes a core element of the scientific enterprise and for this it is essential to deploy a data management system that enables data finding, efficient data movement, and the execution of compute jobs. It is also crucial for users to be able to control and monitor these analyses through a uniform portal interface. Three types of  analyses needs to be supported: downloading intermediate data sets from an archive to a local compute platform, moving the data to a large scale shared compute resource, extremely  large datasets where the so-called code-to data approach needs to be adopted. The PUNCH4NFDI science portal will provide a working solution for PUNCH and other communities.

Use case class 3: execution of analysis of numerical simulations

Numerical simulations play a fundamental role in the interpretation of experimental data. The production of these data is computationally expensive and often large quantities of data are  produced, Therefore, additional structures and tools are needed to support the optimised use of simulation data and to enable the accessibility and analysis of these simulations through a  common set of tools. PUNCH will provide several actions that will optimise the performance of the most commonly used codes and will moreover provide easy-to-use tools that will allow an  easy publication of the data which requires also the development of corresponding metadata standards.

Use case class 4: community-overarching data challenges

A large amount of research data of different origin and without a common structure is produced by experimental and theoretical groups. These data are often useful in further scientific  studies, but in many cases are not available within a FAIR context. A cross experiment analysis with combined data sets would allow to reduce systematic uncertainties and has the  potential to provide new physical insights. The main challenge in realizing this use case is then to make such preprocessed data sets available in a format that will enable a common  analysis. PUNCH4NFDI will provide interfaces and corresponding physics models.

Use case class 5: real-time challenges, data irreversibility

In experiments of high-energy physics and upcoming astronomical observatories, data are taken at rates much too high to be storable in long-term archives. This use case class addresses  the challenge of extracting in real-time the tiny subset of ”interesting data” out of huge data streams in an automated way. The tools and methods currently used are not sufficient to cope  with future demands. PUNCH4NFDI will develop methods for coping with the challenges due to ”data irreversibility”, as decisions on what part of the incoming data streams need to be  rejected have to be taken in real-time and the unavoidable resulting loss of information is mostly not reversible.