DiSSCo Transition Abridged Grant Proposal

Abstract

The Distributed System of Scientific Collections (DiSSCo) is a pan-European Research Infrastructure (RI) initiative. DiSSCo aims to bring together natural science collections from 175 museums, botanical gardens, universities and research institutes across 23 countries in a distributed infrastructure that makes these collections physically and digitally open and accessible for all forms of research and innovation. DiSSCo RI entered the ESFRI roadmap in 2018 and successfully concluded its Preparatory Phase in early 2023. The RI is now transitioning towards the constitution of its legal entity (an ERIC) and the start of its scaled-up construction (implementation) programme. This publication is an abridged version of the successful grant proposal for the DiSSCo Transition Project which has the goal of ensuring the seamless transition of the DiSSCo RI from its Preparatory Phase to the Construction Phase (expected to start in 2025). In this transition period, the Project will address five objectives building on the outcomes of the Preparatory Phase project: 1) Advance the DiSSCo ERIC process and complete its policy framework, ensuring the smooth early-phase Implementation of DISSCo; 2) Engage & support DiSSCo National Nodes to strengthen national commitments; 3) Advance the development of core e-services to avoid the accumulation of technical debt before the start of the Implementation Phase; 4) Continue international collaboration on standards & best practices needed for the DiSSCo service provision; and 5) Continue supporting DiSSCo RI interim governance bodies and transition them to the DiSSCo ERIC formal governance. The Project’s impact will be measured against the increase in the RI's overall Implementation Readiness Level (IRL). More specifically, we will monitor its impact towards reaching the required level of maturity in four of the five dimensions of the IRL that can benefit from further developments. These include the organisational, financial, technological and data readiness levels.