Recipient organisationScience and Technology Facilities Council
Funding£6.4M
PeriodSept 2022 — Mar 2027
In plain English
AI plain-English summary
The UK’s physical sciences labs and facilities currently operate as isolated data islands, each with its own bespoke system for managing research outputs. The Physical Sciences Data Infrastructure (PSDI) aims to build a shared digital platform that lets researchers across chemistry, materials science, and related fields acquire, analyse, and reuse data as easily as researchers in other domains already do. Without this infrastructure layer, valuable data from past experiments is lost or locked away, while the accelerating pace of data generation outstrips researchers’ ability to exploit it. PSDI directly addresses this gap by creating a central “Hub” and seeding it with “Pathfinder” projects that demonstrate how to connect existing resources without forcing them into a single mould. If successful, PSDI could accelerate the discovery of new chemicals, materials, and devices critical for reaching a net-zero chemicals sector by 2041 and for reimagining drug discovery beyond small molecules. The project also establishes a community governance mechanism to ensure the infrastructure evolves with researchers’ needs. This is primarily an enabling infrastructure project—it does not itself make new materials, but it provides the digital backbone that could make future breakthroughs faster and more collaborative.
View original technical description
PSDI is a key enabler of Digital Chemistry and Materials Discovery, providing a platform to underpin the role of digital technologies and AI in enabling discovery across the Physical Sciences, and linking to data infrastructures in other domains. Through PSDI, researchers will be able to leverage the combination of the transformative potential of digital technologies with molecular and materials science principles to support their everyday working practice whilst at the same time accelerating discovery and innovation. PSDI will help drive the missions to achieve a Net Zero Chemicals Sector by 2041; reimagine materials discovery to accelerate technologies for Net Zero; and optimise drug discovery beyond small molecules. Today, each physical science research infrastructure, from individual laboratories to large facilities, has essentially its own isolated data ecosystem which are often bespoke with varying degrees of management. In contrast, many other domains have data-centric infrastructures for collecting and reusing data which act as community hubs and drivers of new methods and discoveries. There is a clear need within physical sciences for an additional infrastructure layer to enable researchers to acquire, analyse and share their data in addition to searching, using and aggregating a wide range of existing resources whilst ensuring that each dataset can remain dedicated to its specific application. There is a need to preserve and exploit outputs from past research while keeping pace with the increasing rate of data generation, the latter posing the greatest challenge and potential for innovation. New chemicals, materials and devices are key to a sustainable future, both environmentally and financially. The UK needs to invent its way out of seemingly conflicting targets of maintaining economic growth whilst making unprecedented strides towards an imminent net zero carbon output and PSDI will be the enabling vehicle for this approach. This phase of PSDI builds on the results of the PSDI pilot project which ran from November 2021 to March 2022 (www.psdi.ac.uk). In this second phase of PSDI, we will begin to implement the recommendations that were developed during the PSDI pilot phase. We will commence development of the PSDI "Hub" and a number of "Pathfinders" which will seed the population of the Hub. This Phase will also continue community engagement activities and initialise a community governance mechanism for PSDI, as well as exploring and evaluating possible future pathfinders.
Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.
Is something wrong? Let us know