Open Research Data Portal

A Vision for Open Research Data (ORD)

The open sharing of research data is essential for progress and excellence in all scientific fields and research disciplines. ORD makes research results transparent and more robust by enabling the re-use of data. It facilitates research collaboration across disciplines and institutions, fostering creativity and innovation. The ability to see and understand what research is doing is of great value to society and is becoming a vital resource in addressing global challenges.

The ETH Domain* is a cooperative network that contributes to the positioning of Swiss research on the international stage. The ETH Domain set out their vision for ORD in a position paper on how a common ORD future should be built, in which the challenges of sharing data (e.g. ethical, legal, personal, security, financial and embargo) are carefully addressed. Bringing ORD to a next level, however, depends first and foremost on the commitment of the researchers, the availability of suitable infrastructure and supporting services, and an environment that values ORD as an important research output.

By realising this vision, the ETH Domain underlines its ambition to play a leading role in the implementation of the ORD.

*The ETH Domain comprises the two Federal Institutes of Technology – ETH Zurich and EPFL in Lausanne – and the four Research Institutes – Paul Scherrer Institute (PSI), Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Swiss Federal Laboratories for Materials Science and Technology (Empa) and Swiss Federal Institute of Aquatic Science and Technology (Eawag). It is strategically managed by the ETH Board.

An ORD Program for the ETH Domain

The ETH Board has now launched an ORD program for the institutions of the ETH Domain under its supervision. This ambitious program aims at promoting pioneering projects related to ORD, jointly driving process and infrastructure developments, and offering information and training on the topic of ORD across institutions. It thus promots estabishing an increasingly coherent path through the research process.

The ORD program of the ETH Domain runs from the beginning of 2020 until the end of 2024. Within the framework of this program, measures were definied to promote and improve the practice of ORD synergistically at all institutions of the ETH Domain.

The ORD measures of the ETH Domain are coordinated with the National ORD Strategy that is being developed in coalition with the Swiss Science National Foundation (SNSF), the Academies of Science (A+) and swissuniversities.

This website provides an up-to-date overview of the status of the multi-year programme. You can also read about how these pages are gradually developing into a central online ORD resource for all researchers in the ETH Domain.

Open Research Data Projects in Focus

AI module for gap-filling TreeNet time series

WSL

In a recent WSL research project (deepT - internal grant no. 202011N2099), a machine learning model was developed for gap-filling multi-channel time series data. The goal is to incorporate this model into the automated near real-time TreeNet data acquisition infrastructure. This addition will allow TreeNet dendrometer data users to fill time series gaps automatically using artificial intelligence.

Open and Reproducible Materials Science Research (PREMISE)

ETH Zurich, Empa, PSI

This project seeks to promote and establish FAIR ORD practices in Materials Science, with a focus on streamlining the treatment of experimental and simulation data on the same footing. Metadata standards for interoperability between electronic lab notebooks (ELNs)/lab information management systems (LIMSs) and workflow management systems (WFMSs) will be developed in the field of Materials Science, and combined with ontological semantic annotations. Best practices for integrating ORD into the research process will be collected, designed, and disseminated. Pilot use cases (focusing in particular on microscopies, spectroscopies, and battery research) that are applicable broadly to Materials Science research will demonstrate the deliverables. Open platforms like openBIS and AiiDA+AiiDAlab will be enhanced to meet FAIR requirements. These advancements will enable seamless interoperability between ELN/LIMS and WFMS. The ultimate goal of the project is to contribute to autonomous laboratories, where AI-driven simulations and robotic experiments expedite materials discovery and characterization. See the website: https://ord-premise.org/

Open EM Data Network

ETH Zurich, EPFL, Empa, PSI, with swissuniversities partners UNIGE, UNIBE, UNIBAS, UNIL

The Open EM Data Network (OpenEM) in Switzerland will implement ORD practices for Electron Microscopy (EM). Cryo-EM has revolutionized protein structure determination, while materials science has seen a surge in possibilities, including 4D STEM data. This has led to increased data volumes and computational needs. OpenEM will extend PSI’s SciCat Data Catalog to provide open and FAIR access to EM data Swiss-wide. It aims to standardize data and metadata collection, streamline acquisition, facilitate data sharing, automate deposition in international ORD repositories, offer user training, and establish a sustainable structure beyond the project’s closure. A parallel initiative through the swissuniversities CHORD program funds the participation of partners outside the ETH domain. OpenEM complements the “EM frontiers” initiative to advance electron microscopy technology in Switzerland, included in the Swiss Roadmap for Research Infrastructures 2023. See the website: https://swissopenem.github.io/

Initiative for primary bio-NMR open research data

ETH Zurich

Nuclear Magnetic Resonance (NMR) spectroscopy, vital in structural biology, lacks an open database for primary data – multidimensional NMR spectra. These spectra are fundamental for in-depth protein analysis but remain largely inaccessible. The NMRprime initiative seeks to establish a FAIR-compliant database, integrating with the Protein Data Bank (PDB) and Biological Magnetic Resonance Bank (BMRB). NMRprime will facilitate spectrum uploads, automated annotation via machine learning, search capabilities, and open data access. The goal, in collaboration with PDB, BMRB, and journals, is to mandate NMR spectra deposition for bio-NMR projects, paralleling protein structure deposition in the PDB as is well-established for other methods in structural biology such as X-ray crystallography. NMRprime's expertise in bio-NMR and automated spectral analysis makes it the ideal candidate for this mission.

A Vision for Open Research Data (ORD)

An ORD Program for the ETH Domain

Open Research Data Projects in Focus

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