The content on this page is currently being updated

Case Studies

WP4 is lead by Simon Coles. In this WP we will be running a series of case studies with a number of partners to develop exemplars and trials to scope PSDI. The objective of WP4 is to augment the community consultation and technology work (WPs 2/3) with focused, practical applications, testing particular aspects of the infrastructure. Through a combination of test implementations and desk-based analysis, this WP will contribute domain specific results to the overall recommendations and specifications of this pilot project. These case studies will demonstrate the potential benefits of PSDI and indicate the work to be continued in later phases. Case studies have been selected to represent as many elements of the infrastructure and its user communities as possible. Topics explored in the case studies include exploring data pathways, combination, surfacing data and more.

In this Pilot phase we are undertaking work in 8 separate case studies run by researchers across our collaborating partners. The 8 case studies cover a wide range of the different research areas, techniques and infrastructure requirements. The case studies split into two categories, scientific disciplines and underpinning methods. The case studies predominantly span the pillars 1 to 3 (Facilities, institutes and hubs; National research facilities; Computational initiatives). However, they also touch on the more diverse 4th pillar (Institutions, groups and laboratories). The case studies will form the basis of a library of case studies, which will be supplemented with examples arising from WP2, and as we progress the project, will be opened up so that anyone can contribute a study and feed into the evolving requirements.

These 8 case studies are outlined below.

Scientific Disciplines

CS1: Data and Simulation driven understanding of catalytic activity

Aim: Demonstrate the practice and value of linking and combining data from across experimental data facilities.

CS2: Exploring CSD-Theory as a tool for assisting materials discovery

Aim: Assess the performance of the CCDC’s new CSD-Theory suite as a medium to link simulation and laboratory materials science in a multi-stage workflow involving computational crystal structure prediction (CSP) (Southampton) and high-throughput automated synthesis and analysis (Liverpool)

CS3: Combining data sources in Materials Physics

Aim: Evaluate the requirements for storing experimental and Natural Language Processing (NLP) mined data.

Underpinning methods

CS4: Spectroscopic data infrastructure

Aim: Evaluate technology and data requirements to underpin spectroscopy characterisation techniques across all disciplines using the infrastructure

CS5: Data curation and availability at instrument-based facilities

Aim: To understand facility data management necessary to publish standalone datasets, to support e.g. formal publishing routes or for machine learning within the National Research Facility for lab-based X-ray CT

CS6: Process Recording and Digital Research Notebooks

Aim: Assess process recording requirements and the associated digital landscape. Investigate Digital Research Notebooks (DRN) and evaluate their suitability as generic recording systems to support diverse workflows

CS7: Data trust, sharing & preservation

Aim: Explore data trust and sharing framework for applicability to PSDI and develop recommendations for preservation and curation approaches

CS8: The Role of Structure in Physical Sciences Data Management

Aim: To probe the requirements for structure-specific metadata to support data management of specific resources, and understand the potential for linking, discovery and machine learning


The intended outputs of WP4 are:

  • Recommendations from case studies
  • Any specifications from case studies
  • Commonalities between case studies
  • Library of use cases