Platform

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

  • Collection and analysis of data
  • Data archival to ensure long-term integrity and availability
  • Metadata management to ensure findability of all deposited data
  • Publication and retrieval of openly accessible data in both human-readable and machine-readable formats

Platform Features

Data Management Infrastructure

Robust systems for storing and organizing research data with comprehensive metadata support. Our infrastructure ensures data integrity through systematic archival processes that adhere to international standards like OAIS, providing a solid foundation for maintaining research data over time.

Search & Discovery

Advanced search capabilities powered by comprehensive metadata indexing. The platform facilitates data discovery through intuitive user interfaces and programmatic APIs, enabling researchers to find and explore relevant datasets efficiently across disciplines.

Visualization Tools

Interactive tools for data analysis and presentation, integrated within our Virtual Research Environment. These tools support researchers throughout the data lifecycle, from initial collection and processing to final analysis and publication.

Security & Preservation

Enterprise-level security and long-term digital preservation following established archival standards. Our preservation strategy ensures data remains accessible and usable for future generations of researchers while maintaining the highest security standards.

Platform Evolution 2025-2028

In line with the service agreement between the Swiss National Science Foundation (SNSF) and DaSCH for 2025-2028, we are implementing fundamental changes to enhance the platform's functionality, scalability, and usability.

Modular Architecture Transition

The current single, monolithic system is being transformed into a modular structure with separated components, each focusing on specific functionalities while remaining closely integrated:

Virtual Research Environment

A dedicated component to facilitate data collection, processing, and analysis within the platform. This environment provides researchers with the tools needed during active research phases.

Archiving Module

This module ensures long-term preservation and consistency of data. By adhering to archival standards like OAIS, it provides a robust foundation for maintaining the integrity of research data over time.

Discovery and Re-Use Component

This component facilitates the discovery and presentation of data, providing access to data and metadata through user interfaces and APIs, supporting both human and machine interaction.

Integration Capabilities

This modular design enhances the platform's ability to integrate with external systems, including third-party Virtual Research Environments, metadata aggregators, and future Swiss and international EOSC nodes. Interoperability extends beyond data to include seamless integration of tools, workflows, and services, creating a cohesive ecosystem that supports research across disciplines and borders.

DSP 2025-2028

Fig. 1: Future architecture of the DaSCH Service Platform. May be subject to change.

Technical Specifications

  • FAIR Data Principles: Full compliance with Findability, Accessibility, Interoperability, and Reusability standards
  • RESTful API Access: Comprehensive programmatic access for data retrieval and integration
  • Multi-format Data Support: Support for diverse data formats across humanities disciplines
  • Scalable Architecture: Modular design enabling horizontal scaling and flexible deployment
  • Standards Compliance: Adherence to international archival and metadata standards
  • Interoperability: Seamless integration with external research infrastructures and EOSC nodes
  • Long-term Preservation: OAIS-compliant archival processes ensuring data longevity
  • Research Lifecycle Support: Integrated tools supporting all phases of the research data lifecycle