At its core, the DaSCH Service Platform (DSP) serves as a repository, which ensures the collection, preservation, and accessibility of data in line with established FAIR principles. It covers four main functionalities:

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• Collection and analysis of data.

• Data must be archived to ensure long-term integrity and availability.

• Metadata must be available and searchable to ensure findability of all deposited data.

• All openly accessible data must be published and retrievable in human readable as well as machine readable form.

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In line with the service agreement for the period 2025-2028 between the Swiss National Science Foundation (SNSF) and DaSCH, we will make fundamental changes to the DSP in the course of the next four years to enhance its functionality, scalability, and usability.

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The architecture of the current single, monolithic system encompasses a Virtual Research Environment, an Archive and a Presentation Environment. This system will be split up into a modular structure with separated components. Each component will focus on specific functionalities while remaining closely integrated with each other:

 

• Virtual Research Environment: A dedicated component to facilitate data collection, processing, and analysis within the platform.

• Archiving: This module will ensure the long-term preservation and consistency of data. By adhering to archival standards like OAIS, it will provide a robust foundation for maintaining the integrity of research data over time.

• Discovery and Re-Use: This component will facilitate the discovery and presentation of data, providing access to data and metadata through user interfaces and APIs.

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Diverging needs arise from different stages of the research data lifecycle. By separating the components, each component can directly address the specific needs of the researchers in the respective phase of the research data lifecycle. Furthermore, this modular design will enhance the platform’s ability to integrate with external systems, such as third-party VREs, metadata aggregators, or future Swiss and international EOSC nodes, where interoperability is no longer limited to data alone. The seamless integration of tools, workflows, and services is essential to create a cohesive ecosystem that supports research across disciplines and borders.