Open Research Data
Position of the ETH Domain
Adopted by the ETH Board on 13/14 May 2020

Table of Contents
Preamble ................................................................................................................................ 3
Why Open Research Data?..................................................................................................... 3
Challenges to address ............................................................................................................ 4
ORD: International and Swiss national context ..................................................................... 5
An ORD vision for the ETH Domain ........................................................................................ 7
Sources ................................................................................................................................... 92

Preamble
Open science practices are quickly becoming a prevalent paradigm in academic researchworldwide. Open Research Data (ORD) is at the core of open science, and new technologicaldevelopments facilitate the sharing and exploiting of data sets, large and small.
The six institutions of the ETH Domain have mandated an internal working group to draft aposition paper laying out a vision for ORD in the ETH Domain, including the motivations andchallenges related to ORD. The paper was submitted for consultation within the Domain’sinstitutions. The ETH Domain brings together some of the most important actors in the STEM
(Science, Technology, Engineering and Mathematics) education, research and innovation
landscape in Switzerland. Together, its six institutions represent over 22,000 employees andover 33,000 students (figures for 2019), and contribute significantly to Switzerland’s successful research landscape. The ETH Domain has already assumed a leading role in adopting theemerging open science practices that allow scientific research outputs – including publications, data and software – to be disseminated and made accessible.
With this document, the ETH Domain is promoting a pragmatic approach towards open research data in Switzerland. By doing so, it affirms its readiness to play a leading role in theimplementation of ORD.1 The aim of this approach is to balance the interests of data producers and data users. It advocates the wide adoption of ORD for publicly funded research, butalso acknowledges that norms vary considerably from one research discipline to another. Itis therefore important that data producers should choose which data (sub-)set they wish to
publish and when, and which license to apply to the published material. Institutional policies
and research support staff guide those choices by providing expert advice, as well as balancing the interests of the various stakeholders, who may sometimes have contradicting objectives. These diverse stakeholder groups include, for example, public funding agencies (e.g.
SNSF, EU, NIH etc.), spin-offs and companies that innovate based on ORD.
This document describes the motivation for the promotion of ORD and the challenges thatneed to be addressed. It outlines the international context of ORD and a vision of a pragmatic ORD approach for the ETH Domain. It is anticipated that some of the initiatives developed by the ETH Domain institutions to support ORD may be extended to all interested parties in the Swiss education, research and innovation landscape.

Why Open Research Data?
Research results are increasingly described in, or based on, digital data which – dependingon their volume, complexity and sensitive nature – can be readily disseminated. Open Research Data are typically accessible publicly and can be used, reused and redistributed – provided that the data source is correctly attributed. ORD can therefore be used for further research, analysis or interpretation, as far as legally permissible and ethically justifiable. Two
categories of research data can benefit from being shared openly: 1) data associated withcf. the mandate of the Federal Council to the ETH Domain: "Massnahmen für eine zukunftsorientierte
Datenpolitik der Schweiz", 9 May 2018;https://www.admin.ch/gov/de/start/dokumentation/medienmitteilungen.msg-id-70694.html andhttps://www.newsd.admin.ch/newsd/message/attachments/52302.pdf

13

publications (e.g. for further analyses, verification, validation), and 2) additional data sets
not directly related to a particular publication (e.g. complete data sets from monitoring programs, of which only parts were used in publications). Both these categories can be of interest to data producers as well as researchers not involved with the data collection, or to otherparties outside the academic community (civil society actors, industry, etc.).
There may be various motivations for making research data openly available, including thefollowing:
1. Science often benefits from multiple evaluations of the same data sets by researcherswith different backgrounds, perceptions and ideas. ORD allows – and stimulates –new research and discoveries, as researchers can make use of valuable data eventhough they had not been involved in collecting it.
2. ORD incentivises the publication of well described and citable scientific data sets. It
clarifies their authorship and ownership. To facilitate the use of data by others, datasets should be published under suitable licensing arrangements and be readily identifiable by digital object identifiers.
3. ORD makes research more transparent and allows published results to be reproduced, or to be included in meta-analyses.
4. ORD supports the longevity and long-term accessibility of data sets.
5. ORD facilitates collaborations within and beyond established networks, within the research community or with other parties outside the research community (civil society
actors, industry, etc.). Researchers not belonging to established networks, such as
young researchers, may particularly benefit from public access to research output
that is otherwise confined to established networks.
6. ORD can be exploited commercially and may also foster the emergence of new business models for university spin-offs and beyond.
7. ORD can strengthen the impact of individual research projects and the overall impactof science on the economy and society. Furthermore, it helps to increase the visibilityof researchers and institutions.

Challenges to address
Sharing research data openly comes with a number of challenges, including the following:
1. Sharing data early may lead to unfair competition.
2. Data may be misinterpreted on purpose or due to lack of detailed contextualknowledge.
3. Reuse of carefully gathered data may not be sufficiently acknowledged by others.
4. Making data publicly available in a useful form requires substantial human resources
and infrastructure.

45. Long-term data storage and ensuring the long-term accessibility of data is costly, particularly for very large data repositories (of the order of petabytes), and the cost-benefit ratio for storing a particular data set may be difficult to determine. Substantial
technical developments are required to address data curation, data life-cycle management, data archiving, data formats as well as data access via suitable indexes.
ORD therefore requires long-term funding solutions for infrastructure and services
and careful decision-making with regard to expiry dates for individual data sets.
6. For legal, ethical, privacy or security reasons, some data may not be suitable for sharing, or may only be suitable for sharing after having been carefully validated.
7. Personal data, particularly but not exclusively in medical research, has to be anonymised and protected from re-identification.
These are important points that need to be carefully addressed. The ORD strategy of the ETH
Domain acknowledges these concerns and the need to put forward pragmatic solutions
which address them.
A governance framework that defines the rights and duties of data producers, data owners
and data users is needed. Indeed, a culture that gives proper credit to data producers needs
to be promoted, along with the requisite tools; and research communities need to develop
best practices for data citation. Such a framework should also define embargo periods during which data owners have an exclusive right to exploit the data and the opportunity to
publish the data in a citable way. Embargo periods may be discipline-specific. The reuse ofdata should be subject to a data licence to ensure that it is used in accordance with generally
accepted rules of scientific integrity. While the risk of results being misinterpreted is not confined to ORD, it will be accentuated for ORD, and the data user should be aware of this risk.
It is therefore important to acknowledge that there are valid legal, ethical, privacy or security reasons for not sharing data, but any restriction should be justifiable – and, ultimately,
justified.
A strategy should be formulated for the development of ORD-related infrastructure and services that responds to future demands and to develop funding schemes in order to support
these infrastructures and services in the long-term. Such infrastructure and services, including long-term data storage, must be financially sustainable and should avoid the drawbacks
experienced with the commercialisation of scientific publishing in the last century.

ORD: International and Swiss national context
A paradigm shift is taking place in the academic research community towards more openness, and it is important that ORD best practice should not be developed in isolation within
the ETH Domain. Indeed, sharing research outputs openly – particularly data supporting results described in manuscripts submitted for publication in peer-reviewed journals – has become commonly accepted or even compulsory in an increasing number of disciplines over5the past two decades. Notable examples include structural biology, 2 genomics, and geosciences. Large research organisations (e.g. NASA 3 and CERN 4) and large projects in other disciplines (e.g. astronomy 5 and Public-Private Partnerships in Drug Discovery 6) have establishedtheir own data collections.
Most of the earlier movements towards ORD were field-specific efforts. They established
ORD and adopted standards with regard to metadata, data formats, etc. However, not all research disciplines have created such ORD frameworks. As a result, there are significant differences with regard to progress to date in implementing ORD.
More recently, funding agencies, such as the Swiss National Science Foundation 7, EuropeanCommission 8 and the National Institute of Health 9 in the United States, started to promote –or request – ORD practices for projects funded through their programmes and fundingschemes. In Europe, one non-field specific, publicly-funded portal for ORD is Zenodo 10. In addition, a European Open Science Cloud (EOSC) for research data is in the making. 11On the national level, ORD has mainly been promoted through institutional rather than fieldspecific actions. Swissuniversities – with the involvement of ETH Zurich and EPFL – is currently working on a national Open Research Data Strategy. 12 Within the ETH Domain theseactions consisted in establishing institutional ORD repositories13 14 15 and open data policies
as well as the promotion of an ORD culture, e.g. through incentives 16 and services to support
ORD implementation 17 18 19 20 21 22. The ETH Board has specified the strategic focus area
The Protein Data Bank (PDB) began as a grassroots effort in 1971, and by the early 1990s "virtually all journals
that publish crystal structures of biomacromolecules made deposition into the PDB archive a requirement forpublication". Berman HM, Kleywegt GJ, Nakamura H, Markley JL. The Protein Data Bank archive as an open
data resource. J Comput Aided Mol Des. 2014;28(10):1009–1014. doi:10.1007/s10822-014-9770-y
3
One example is the NASA EarthData portal: https://earthdata.nasa.gov
4
CERN Open Data Portal: http://opendata.cern.ch
5
The Sloan Digital Sky Survey, for example, represents "the most detailed three-dimensional maps of theUniverse ever made, with deep multi-color images of one third of the sky, and spectra for more than threemillion astronomical objects": https://www.sdss.org
6
Open Targets: https://www.opentargets.org and the Pistoia Alliance: https://www.pistoiaalliance.org
7
ORD policy by SNSF: http://www.snf.ch/en/theSNSF/researchpolicies/open_research_data/Pages/default.aspx
8
EU Science Hub of the Joint Research Centre (JRC): https://ec.europa.eu/jrc/en
9
Several data collections are curated and maintained by the National Center for Biotechnology Information:
https://www.ncbi.nlm.nih.gov
10
https://zenodo.org/
11
https://ec.europa.eu/research/openscience/index.cfm?pg=open-science-cloud
12
https://www.swissuniversities.ch/themen/digitalisierung/open-science13
https://opendata.eawag.ch
14
https://www.cscs.ch/publications/press-releases/2018/589/15
https://www.research-collection.ethz.ch/
16
Open Science Fund of EPFL https://www.epfl.ch/research/open-science/in-practice/open-science-fund/
17
Data Life-Cycle Management https://www.dlcm.ch/18
Data Champion Program of the EPFL Library https://www.epfl.ch/campus/library/services/servicesresearchers/rdm-contacts-communities/epfl-data-champions/19
https://opendata.eawag.ch/eawagrdm/
20
https://www.envidat.ch/
21
https://www.empa.ch/web/s909
22
https://openrdm.swiss26

"Data Science" as a strategic priority for the ETH Domain. Together, EPFL and ETH Zurich
have established the Swiss Data Science Center (SDSC). 23

An ORD vision for the ETH DomainWith ORD – and open science in general – it will hopefully become more straightforward tobuild on research work by other colleagues in the same field and beyond. This should makeit easier to test new scientific hypotheses using data and data workflows developed in earlierwork. ORD ensures that background information on data sets ("metadata") is available thatallows reanalysis of the data independently of the data producer and possibly even in a different context from the one originally intended. In addition, ORD can be used in new fields
and scientific approaches, particularly data science.
The culture and software environment of ORD and open science in general are emerging
only now. The definition of the FAIR (Findable, Accessible, Interoperable and Reusable 24)
principles for ORD enabled the objectives of ORD to be made specific for the first time. However, actually translating the FAIR principles into concrete forms of ORD is an ongoing process. It is expected that Switzerland can lead the development and implementation of innovative technical solutions. As past experience has shown, the practical application of ORD
that builds on these technological solutions will differ between scientific fields and follow
field-specific standards. Solutions will therefore need to be customised depending on thefield. Discussions on field-specific standards and technical solutions will need to take place inparticular in those research communities, in which international standards do not yet exist;
these discussions should be led in cross-institutional working groups in the different disciplines, potentially with input from other national and international actors.
As world-leading research organisations, the institutions of the ETH Domain believe that
ORD has the potential to further increase the visibility and the impact of their researchwithin the scientific community, the economy and society as a whole. The vision of the ETH
Domain is to foster a research environment that● supports ORD in research practice and creates an environment that values ORD, particularly in the context of evaluation committees on all levels;● promotes ORD practices for research projects that are publicly funded;● makes ORD tangible and visible as a catalyst for cutting-edge research andtechnology transfer;● creates new opportunities for researchers, companies and other entities by developing innovative infrastructure and services that make ORD searchable and allow external data analysis tools to exploit the data via APIs. Ready-made tools for visualising
ORD can increase the reuse of data, especially those in complex data sets;

https://datascience.ch/; https://ethrat.ch/en/eth-domain/sfa/data-science
Wilkinson, Mark D.; Dumontier, Michel; Aalbersberg, IJsbrand Jan; Appleton, Gabrielle; et al. (15 March2016). "The FAIR Guiding Principles for scientific data management and stewardship". Scientific Data. 3:160018. doi:10.1038/sdata.2016.18.
23247● creates new opportunities for researchers in Switzerland and worldwide that are inclusive and transparent by providing ORD and associated tools.
The ETH Domain envisions an ORD environment with the following characteristics, among
others:● Accessibility of ORD: access to ORD will be open to the general public through achoice of corresponding licenses.
● Searchability of ORD: information on where to find research data, on how to access itand on its reusability is publicly accessible. Particular attention should be given to establishing indexes in research fields that do not yet have established solutions. Datasets will be findable through search engines and information on the reusability of theresearch data will be complemented with quantitative indicators. These indicators on
the use of the data can support decisions as to which data should be preserved forthe long term, thus avoiding wasteful data storage.
● Infrastructure that combines data repositories with tools for data visualisation andexploitation: pure data repositories will be replaced by or integrated with infrastructure that provides standard interfaces between data storage and computational facilities; the latter can be deployed as user-specific computational tools for data visualisation and exploitation. While the infrastructure can be distributed, it is recommended that the ETH Domain should aim in the long term to create an over-archingaccess portal and unified standards with regard to metadata, licensing and searchability.
The quality and speed of implementation of the ORD culture into the research environment
within the ETH Domain will depend not only on the commitment of the researchers but alsoon the availability of a suitable infrastructure, supporting services and an environment thatvalues ORD as an important research output. The ORD culture has to be brought to life, andresearchers – particularly new arrivals – must be made acquainted with it. A successful transition to an ORD research environment also requires new skills. The digitalisation of sciencemeans that all students and researchers from all fields are using computational methods toproduce, organise, analyse or share data at various levels of complexity. Therefore, all students and researchers in the ETH Domain – from Bachelor to postgraduate level – shouldhave access to training on research data management, data science, statistics and computational sciences.

8Sources
Research Data Management Policy (2017) DLCM, CH. Web. PDF.
Higher Education Funding Council for England, (2016) Concordat on Open Research Data.
Project Report. Higher Education Funding Council for England, UK. Web. PDF.
von der Heyde, Markus. (2019, May 22). Open Research Data: Landscape and cost analysis ofdata repositories currently used by the Swiss research community, and requirements for thefuture (Version 1.0.0). Zenodo. http://doi.org/10.5281/zenodo.2643460
Swedish Research Council. (2019) An outlook for the national roadmap for e-infrastructures
for research. ISBN 978-91-88943-07-1. Web. PDF
Verheul, Ingeborg, Imming, Melanie, Ringerma, Jacquelijn, Mordant, Annemie, Ploeg, JanLucas van der, & Pronk, Martine. (2019, May 6). Data Stewardship on the map: A study oftasks and roles in Dutch research institutes. Zenodo.
http://doi.org/10.5281/zenodo.2669150
Dunning, Alastair. (2018, June 26). TU Delft Research Data Framework Policy. Zenodo.
http://doi.org/10.5281/zenodo.2573160
Ashley, Kevin (2016) Developing Skills for Managing Research Data and Software in Open Research. Wellcome Trust. https://dx.doi.org/10.6084/m9.figshare.4133916
Directorate-General for Research and Innovation (European Commission) O'Carroll, Conor;
Hyllseth, Berit; Berg, Rinske van den; Kohl, Ulrike; Kamerlin, Caroline Lynn; Brennan, Niamh;
O’Neill, Gareth (2017) Providing researchers with the skills and competencies they need topractise Open Science - Publications Office of the EU. https://doi.org/10.2777/121253
Universities UK Open Research Data Task Force (July 2018) Realising the potential: final report of the Open Research Data Task Force. Web. PDF.
Universities UK Open Research Data Task Force (June 2017) Research data infrastructures inthe UK. Web. PDF.

9ETH BoardZurich and Bernwww.ethboard.ch
3 June 202010