S&T Research Data Management Guide by University of Twente

FACULTY OF SCIENCE AND TECHNOLOGY (S&T)

S&T RESEARCH DATA MANAGEMENT GUIDE PUBLISH DATE 26-02-2021 VERSION 1.18

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COLOFON Organisation: University of Twente Board: Faculty of Science and Technology (S&T) / Technische Natuurwetenschappen (TNW)

Title: S&T RESEARCH DATA MANAGEMENT GUIDE

Version: 1.18

Date: 26-02-2021 Document Maintenance: N.M. Koster (S&T)

Contact: rdmsupport-TNW@utwente.nl

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CONTENTS Introduction ...................................................................................................................... 5 Setting ........................................................................................................................... 5 Needs of S&T researchers ............................................................................................ 5 How to read and use this document ............................................................................ 6 S&T specific RDM guidelines ........................................................................................... 7 Benefits of research data management ....................................................................... 7 FAIR principles .............................................................................................................. 7 Research Data is public, ‘unless’ .................................................................................. 8 Awareness and culture ................................................................................................. 8 Privacy regulations........................................................................................................ 8 Data management plan (DMP) ..................................................................................... 9 Overview research data management S&T ................................................................ 11 Data collection ............................................................................................................ 13 Data storage................................................................................................................ 14 Data documentation ................................................................................................... 15 Data registration ......................................................................................................... 15 Data analyses .............................................................................................................. 16 Data sharing and exchange ........................................................................................ 16 Ownership of data and project results ....................................................................... 17 Data archiving ............................................................................................................. 18 RDM costs .................................................................................................................. 18 Other concepts on RDM ............................................................................................. 19 Exceptions .................................................................................................................. 19 S&T RDM guide; availability, improvements and help ............................................... 19 Appendices ..................................................................................................................... 22 Appendix A - S&T clusters .......................................................................................... 22 Appendix B - Repositories for research data .............................................................. 23 Appendix C - Intellectual property rights.................................................................... 24 Appendix D - Document management ...................................................................... 25

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INTRODUCTION The information in this guide applies to all professionals who conduct and support research within the faculty of Science and Technology (S&T, Dutch: Technische Natuurwetenschappen, TNW). It concerns all activities which are part of conducting research; generating, processing, interpreting, archiving, publishing and sharing research data. For ease of reading the faculty will further be referred to as ‘S&T’ in this document. S&T commits to the Research Data Management Policy which applies to all faculties of the University of Twente. Professionals to which this S&T Guide applies should therefore know the contents of the general UT policy. The S&T Guide aims at making concrete what is needed for S&T Research to achieve the main goal of good data management; to help generate the best possible research. All working rules mentioned in this guide are supplement to the general UT policy and should be read and handled as such. For ease of reading the policy which applies UT wide will further be referred to as ‘general UT policy’ and research data management as ‘RDM’. The S&T board is responsible for this RDM Guide. The board, however, delegates the decision making mostly to a process of reaching consensus among the RDM working group for S&T. This is a group of people with a focus on RDM and who are involved in structurally evaluating RDM in practice and this S&T RDM Guide. This guide aims to be normative, clear and readable. Therefore, it cannot and does not describe all rules and guidelines possibly needed concerning RDM. The fact that something is not mentioned in this guide does not mean it is not applicable. This policy does not address possible unwanted behavior either. It rather addresses the needs of S&T researchers for good RDM practice.

SETTING Types of data and analyses used within S&T Research vary greatly due to the broad scope of research programs. There is a strong collaboration with industrial partners and other national and international research institutes. Research is largely funded by industrial and other external partners, as well as science foundations. Research is also embedded in the UT institutes MESA+ (institute for nanotechnology) and TechMed Centre, which succeeded the former MIRA Institute for biomedical technology and technical medicine. Some projects are also carried out with the third UT Institute; Digital Society Institute (DSI). S&T research programs cover a broad scope ranging from physics, chemistry, and nanotechnology to biomedical and health technologies. Research is organized in 11 clusters (see Appendix A S&T clusters). Central are the Principal Investigators who provide input for scientific development of the cluster together. The broad scope of research fields and the vast number of researchers and their needs, ask for a S&T RDM Guide which provides rules where needed and guidelines which allow variation when possible.

NEEDS OF S&T RESEARCHERS The S&T board and support staff facilitate researchers in numerous areas, including RDM. For this reason, several sessions have been held by support staff, from both LISA and S&T, and researchers of multiple groups. Together, the needs of S&T researchers on this subject were investigated. Concluding: researchers express the need for clear rules and guidance from support staff with regard to: • research proposals regarding RDM conditions set by funders • research contracts regarding RDM issues: for example ownership, procedures, etc. • describing responsibilities within the research group regarding RDM • data management plans (=DMPs) which are helpful to researchers and their supervisors • Group RDM Guides with concrete working rules which are helpful on a group level • where to best get extra storage considering the type of project and costs • which software / ICT services to use considering the type of project and costs • what is needed for GDPR1 proof (Dutch: AVG-proof) RDM 1

General Data Protection Regulation 2016/679 is a regulation in EU law on data protection and privacy

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• •

special procedures in research which involves human subjects / respondents how to work practically with FAIR principles, both during and after research projects

As a result of these sessions S&T management has invested in meeting these needs and has organized staff, means and materials. This S&T RDM Guide is an example of such activities. S&T management will continue with these activities in a structured and ongoing manner. Activities focus on supporting researchers in RDM in daily practice. This includes general UT policy, faculty rules and guidelines and group policy, such as ‘home made’ working rules and methods within a group. There is consensus among most researchers that the daily practice part of RDM is mainly the responsibility of the research groups. S&T management adheres to the general UT policy in which the whole of RDM is a shared responsibility and a joint effort of many employees. Roles and responsibilities are described in appendix 3 in the general UT policy. They concern employees in multiple departments and levels, which are visualized in Figure 1. The only difference is that S&T adds a faculty RDM-project management as a supporting role and responsibility. FIGURE 1: ROLES AND RESPONSIBILITIES RESEARCH DATA MANAGEMENT

Researcher Project coordinator

LISA*

S&P**

Research datamanagement

Head research group

S&T-RDMproject management

Rector magnificus Faculty board

*Library, ICT Services and Archive (service department) ** Strategy & Policy (service department)

HOW TO READ AND USE THIS DOCUMENT The general UT policy states several rules and guidelines. This S&T RDM Guide makes some of these rules and guidelines concrete, adapting to S&T needs. All following tables are S&T specific rules or guidelines, which are not already stated in the general UT policy. The combined tables are available in a worksheet to serve as a practical checklist for research groups. If a table states “researchers describe” it should be read as a working rule, something which should be the case in daily practice. Text from the general UT policy is copy-pasted as little as possible for several reasons. Text which is copied/quoted is written in Italic and/or shown as a “quote”. The general UT policy and this guide use the term ‘research project’. There is no possible strict definition for this term. S&T considers a research project; a set of research activities that form a logical whole based on for example: their common data management scheme, belonging to one scientific article, being carried out during one PhD-program, through one allocated source of funding, or performed under one ‘OFI-number’. Another often used term is ‘data’ for which the definition in the general UT policy is: “Research data is both physical and digital data, that is collected, created and/or used in the framework of a research project and (partly) intended to produce and validate research findings. In the context of research data management also data related materials, such as models, instruments, lab notebooks, protocols, questionnaires and informed consents must be taken into account.”

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S&T SPECIFIC RDM GUIDELINES BENEFITS OF RESEARCH DATA MANAGEMENT Benefits of RDM are described in the general UT policy. Summarized, these are: • reputation and impact • quality, efficiency, safety and integrity • re-use, new results and new collaborations Within S&T joined efforts focus on the fact that these benefits should not remain a mere fact on paper but should be made an active part and main focus of the research group. BENEFITS OF RESEARCH DATA MANAGEMENT | S&T WORKING RULE S&T supervisors discuss benefits as described in the general UT policy and how to best achieve them as a structural item on the agenda in group meetings and/or individual sessions with researchers. S&T research groups document how to achieve the benefits, considering challenges and needs of the group and local circumstances, in a Group RDM guide and/or DMP S&T supervisors discuss the benefits of RDM in individual appraisal interviews with their researchers as an assessment of research performance. This takes place preferably once a year and, in case of PhDs, as part of the ‘qualifier’. The general UT policy states: “As a general starting point the UT RDM policy implies that faculties and/or research groups: • support the implementation of the FAIR-principles: Research data must be Findable, Accessible, Interoperable, and Re-usable • commit to the general principle that research data is classified as public data unless there are specific requirements to maintain the confidentiality of research data • stimulate awareness regarding RDM practices and develop a culture in which researchers • are stimulated to and rewarded for sharing data • include the provision of RDM training and support to researchers • facilitate solid infrastructure and tools for storing and archiving research data both during and after the research • monitor the development and execution of Data Management Plans (DMPs)

FAIR PRINCIPLES A set of guiding principles to make data findable, accessible, interoperable and reusable (FAIR) is provided in appendix 1 of the general UT policy. Further specification of these principles depends on the research field. It can often only be done on the research group level or even project level. Concrete practice examples are given on the S&T intranet. FAIR principles are often associated with public availability outside of the UT and mostly in the archiving stage after research. FAIR principles however, also have benefits during research and within the organization. These benefits can be found on all levels: the faculty, institute, cluster, research group or project level. For example, some benefits are: • Data becomes more manageable and analyses become more consistent. • FAIR related standards applied to datasets and metadata can save a lot of time for researchers. • Follow-up projects can more easily and consistently build on former work. It is a huge misconception that FAIR data equals ‘open’ or ‘public’. FAIR principles help to make data reusable. With the ‘A’ in FAIR, conditions can be set for access. Also, ‘open’ data are not necessarily reusable. They need to be FAIR to be able to reuse them. FAIR PRINCIPLES | S&T WORKING RULE S&T research groups describe how FAIR guiding principles are handled in a Group RDM Guide and/or DMP. The FAIR guiding principles that S&T researchers use include (international) standards for data formats, terminology and metadata as used by acknowledged national and/or academic institutes, CURRENTLY FOR EXAMPLE IN NL: 4TU, RDNL OR, FOR ‘HEALTH’ DTL OR NICTIZ. INTERNATIONALLY: FAIRSHARING.ORG, DUBLINCORE OR DIGITAL CURATION CENTRE AND FOR ‘HEALTH’ DATA DOCUMENTATION INITIATIVE.

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If the standards provided by these institutes are not appropriate, other discipline specific and community recognized standards for data formats, terminology and metadata are used. S&T researchers evaluate structurally if and how FAIR guiding principles are operationalized during a research project, as a rule of thumb: yearly, and at the end of a research project.

RESEARCH DATA IS PUBLIC, ‘UNLESS’ The general UT policy states that research data is publicly available as a general principle. It also mentions reasons why data can be partially or temporarily non-available. S&T research often includes collaboration with third parties from industry, the development of technology or ‘products’ and data of human subjects. In various cases, non-disclosure agreements (NDAs), intellectual property rights or personal data issues apply. These may cause exceptions to making (parts of) the data publicly available, and data may be closed or available under specific conditions. For example, a temporary embargo may apply. All repositories have requirements for storing data (see Appendix B - Repositories for research data). These requirements should be taken into account early on in research projects. RESEARCH DATA IS PUBLIC, ‘UNLESS’ | S&T WORKING RULE S&T Group RDM Guides or DMPs describe a section on: • whether (parts of the) data are marked as ‘publicly available’ or ‘restricted access’ • in case of restricted access: why, which are the ‘Restricted Data Elements’ and which conditions to access apply, or in case of a (future) temporary embargo; why and for how long • whether (future) publications in scientific journals are ‘open access’ or not Relevant research data belonging to published work is archived in an appropriate public repository, unless exceptions apply. In all other cases: data is archived in ISO 27001 certified storage hosted by or offered through the UT. In case the exception applies that a group uses other storage facilities: only ones audited by the UT CURRENTLY BY ICT AUDITORS OF LISA . Data with restricted access is accessible at the research group level (i.e. others involved in the project, not just the individual). Metadata and description of the project are publicly findable through the University of Twente Research Information System (see Data registration).

AWARENESS AND CULTURE Awareness and culture with regard to RDM depend on the research field and the people involved. Many S&T researchers manage their data in a way that meets high quality standards. This does not mean however that there is an overview and high awareness within a research group. Both are needed to, for example, simplify and improve practice and achieve the most benefit. AWARENESS AND CULTURE | S&T WORKING RULE S&T management organizes staff, means and materials designed to improve awareness, culture and benefits, rather than organizing ‘check and control’ measures. All researchers follow the RDM training a.s.a.p. and at least once during their research project(s), CURRENTLY: ONLINE TRAINING OFFERED BY THE UT THROUGH CANVAS. S&T researchers and support staff evaluate UT, faculty and group policy in practice jointly on an ongoing/structural basis. The head of the research group assigns a RDM support role to two or more researchers within the group. Tasks are described and shared with the ICT contact person of the group. Tasks meet local needs and are approved of by all group members.

PRIVACY REGULATIONS S&T research groups may handle personal data; any data about an identified or identifiable person. A name, birthdate, address, real ID-number or photograph can identify someone. But also other data that displays typical characteristics of a person can identify them, be it with often more effort. Think of one or more physical, physiological, genetic, psychological, economic, cultural or social characteristics of a person’s identity. Pseudonymized data is data for which a ‘key’ is available that can match the data with the identified person it belongs to. Anonymized data is data of which there is no such key and the identity of the person cannot be recovered. Only fully anonymized data is no longer personal data.

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Personal data may include special personal data. Think of biometric, genetic and other data which concern a person’s health, sexual behavior, race, religion, membership of a union or politic movement. Outside the European Union personal data as meant in the GDPR is referred to as ‘personally identifiable information (PII)’. Personal data in S&T research can be roughly divided in two groups: • data from persons not actively involved; for example data from biobanks, human blood or tissue, health records, existing repositories or former research • data from persons actively involved; for example participating in research activities as subjects or respondents DATA PRIVACY REGULATIONS | S&T WORKING RULE As a basic principle, research data does not include personal data which directly identifies persons (such as name, birthdate or real ID-numbers): personal data in S&T research are anonymized if possible. If anonymization is not possible, personal data is pseudonymized. In case of exceptions, such as for video footage of people, these are described in the Group RDM Guide or DMP. S&T Group RDM Guides or DMPs describe a section on: - whether data includes data which can identify persons and how - if so whether data is pseudonimized or anonymized and which procedures are involved - whether the personal data includes special personal data Research which involves interaction with, or data gathered from, human subjects is submitted to a domain specific ethics committee(-member)2. In case these subjects also actively participate: details are reviewed by an employee with knowledge of the WMO (Wet Medisch-Wetenschappelijk Onderzoek met mensen) and GCP (Good Clinical Practice). CURRENTLY THROUGH TECHMED CENTRE RESEARCH SUPPORT INCLUDING GCP-CERTIFIED STAFF.

For research which involves interaction with human subjects, special personal data is managed in an ICT system suitable for either WMO-research (i.e. a Clinical Trial Management System (CTMS) including Electronic DataCapture of patient data (EDC) available through Techmed Centre research support staff. Or, in case of non-WMO-studies, in a system for which a Data protection impact assessment (DPIA) has been carried out and evaluated by RDM support staff, CURRENTLY THROUGH TECHMED CENTRE RESEARCH SUPPORT STAFF.

Personal data are handled according to UT privacy rules, including participant informed consent and reporting in the digital UT register based on GDPR-requirements (Dutch: AVG). Only fully anonymized data is exempt from reporting in that register since they are by law no longer personal data.

DATA MANAGEMENT PLAN (DMP) The general UT policy states that every research project3 must have a DMP. Projects within S&T research groups often have similar features regarding data management. Some groups addressed the need for Group RDM Guides. These can have benefits for researchers and their supervisors. They can offer clarity, save time, simplify procedures and improve awareness and consistency in practice. This is for example the case if they function as an umbrella for multiple DMPs in the group (see also Table 1). DATA MANAGEMENT PLAN | S&T WORKING RULE S&T groups write and maintain RDM Group Guides which include items to which DMPs can consistently refer (for example same order, type). Group RDM Guides and DMPs are stored directly accessible to the head of the research group, individual researchers and staff with the role of research support for S&T, CURRENTLY A PROJECT FOLDER SUCH AS ON P:DRIVE, MICROSOFT TEAMS OR A SHAREPOINT SITE FOR THE GROUP.

Roles and responsibilities as described in appendix 3 of the general UT policy with regard to DMPs are leading unless exceptions apply. Exceptions are documented in a Group RDM Guides and/or DMPs. 2

domain specific committee: with knowledge of ethical issues in the research field of interest, which may range from a broader ‘health’ or ‘engineering’ to a more specific ‘questionnaires with participants’ or ‘robotics’. 3 See How to read & use this document for definitions on ‘research project’

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DMPs generally consist of several topics. An overview of these topics is given on the following two pages. Each topic is addressed in more detail in the following sections. Table 1: Overview of various documents that contain rules and regulations regarding RDM. When writing a DMP, higher level rules and guidelines should be taken into account.

UT RDM policy: general rules and guidelines

S&T RDM Guide (this document): Faculty specific rules and guidelines

Group RDM Guide: Group specific rules and guidelines

Data management plan (DMP): Project specific rules and guidelines

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OVERVIEW RESEARCH DATA MANAGEMENT S&T

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DATA COLLECTION Data collection is one of the most important and defining parts of Research Data Management. It is an overarching term covering new data generation and acquiring previously generated data. Data acquisition is the process of capturing and measuring physical data and then converting the results into a digital form that is further manipulated by a computer program. Data aggregation is compiling information from databases with intent to prepare combined datasets for data processing. Keeping journals or logbooks of the course of actions, circumstances, problems and solutions is necessary in any scientific research. Notebooks also need to be maintained for legal purposes. They can serve as evidence in cases of patent and intellectual property matters. Electronic lab notebooks (ELNs) have some advantages compared to paper ones: • improving data integrity and accuracy • easier to search efficiently • easier to share with multiple users • automatic back-ups • easier to copy and reuse standard protocols. Hand written notes may remain necessary, e.g. in case of sketching or other situations for which an ELN and keyboard are not efficient or even possible. In that case, smartpens which digitalize handwriting can ease data management: notes can be ‘tagged’, split, copied or connected and timestamps are automatically logged with every word or drawing. Some smartpens even come with voicerecording during writing. If regular pen and paper are used and the paper is scanned to PDF: OCR (Optical Character Recognition) tools can be used to convert handwritten material as editable text for computer use. DATA COLLECTION | S&T WORKING RULE The equipment, (sensitivity of) measurement instruments and ICT infrastructure, software, and its version and other facilities used for collection are metadata which are described in a DMP and/or Group RDM Guide. Methods of data gathering, procedures, types and sources of data, volume and file formats, are described in laboratory notebooks, preferably electronic ones (ELN). Handwriting is done preferably with a smartpen. In the case of normal pen and paper, this is scanned to PDF afterwards (and thereby digitalized) on a regular basis. Overarching items such as metadata on test or calibration results, quality assurance, sustainability and reproducibility are described in a DMP and/or Group RDM Guide. CURRENTLY: THE MIS (MESA CLEANROOM INFORMATION SYSTEM) IS USED AS A RULE FOR SPECIFIC RESEARCH

Standards, such as CML (chemical markup language), are used which are accepted by publishers and which are supported by acknowledged lines of Open Source code. If data collection equipment and methods are integrated with those of further data processing and analysis, the nature of such integration is described in DMPs and/or Group RDM Guides. S&T RDM&ICT support staff can be contacted for assistance regarding digitalization (e.g. means and materials needed for this).

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DATA STORAGE The general UT-policy states rules regarding storage. S&T considers storage in this S&T RDM Guide: all storage during research. After a research project the term archiving applies. Storage includes software packages and hardware such as portable devices (USB-sticks, laptops, etc.). Especially portables run a high risk concerning loss, damage, security issues and availability. Other storage matters concern research groups which need clusters to perform high performance computing. Other needs are those for non-digital storage, like written paper based material. This variety asks for S&T specific rules. DATA STORAGE | S&T WORKING RULE S&T researchers use non-portable digital regularly backed up storage designed for group use hosted by or offered through LISA, unless exceptions apply. CURRENTLY PROJECT FOLDERS, SUCH AS ON UT NETWORK DRIVE (‘P-DRIVE’) OR A SHAREPOINT SITE, RESEARCH DRIVE (= GROUP STORAGE, SURF SERVCE), OR SOFTWARE HOSTED BY LISA (UT). THE DECISION TOOL IS USED TO CHECK OPTIONS TO STORE DATA.

If storage for group use is not an option and private/personal storage is needed for research data, it is ISO 27001-certified and accessible to the head of the research group, CURRENTLY SURFDRIVE (=PRIVATE/PERSONAL STORAGE) IN WHICH FOLDERS ARE SHARED WITH THE HEAD OF THE RESEARCH GROUP AND SUPERVISORS AND WHICH CAN BE SYNCHRONIZED WITH A LAPTOP, OR OTHER SOLUTIONS MENTIONED IN THE DECISION TOOL. PRIVATE/PERSONAL STORAGE OFFERED BY THE UT IN THE FORM OF M-DRIVE IS NOT USED FOR RESEARCH DATA SINCE IT IS NOT ACCESSIBLE TO OTHERS.

Data on personal storage are moved to group storage in case the researcher is no longer employed at the research group. If other digital storage is needed (SaaS service, commercial cloud service, etc.) the reason why and type(-s) are documented in a Group RDM Guide or DMP and reviewed by S&T RDM support staff. US-based commercial cloud services such as Dropbox are not used. The only exception is if regular conditions do not apply and instead the additional conditions UT and for example google have agreed on. In case the exception applies that a research group plans, or already has, a separate storage facility needing servers, this facility is screened by the UT, CURRENTLY ICT ISO CERTIFICATION AUDITOR AT LISA-DSM (UT).

In case of portable devices, data is stored as short term as possible and backed-up regularly on non-portable storage accessible to the head of the research group. Data on the portable device are deleted a.s.a.p. and no later than ending the research task for which the data is needed. In case of portable devices AND confidential/personal data (as a rule pseudonymized): data are encrypted, CURRENTLY MEASURES AS DESCRIBED ON THE UT CYBER SECURITY WEBSITE. Non-digital research data and related materials, such as physical samples and paper lab notebooks, are handled according to procedures described in a Group RDM Guide and/or DMP. Digitalization is done if (technically) possible, such as scanning or data migration to electronic lab notebooks (ELNs) connected to a Laboratory Information System (LIS). These rules regarding data storage also apply to students that perform research within the group (e.g. bachelor/master assignments, internships).

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DATA DOCUMENTATION The general UT policy states several rules regarding documentation. Data documentation is ‘information about the research data’. The general UT policy states: “This documentation must also contain information about property rights and terms of use.” For this item; see the section below on ‘ownership’. DATA DOCUMENTATION | S&T WORKING RULE Group RDM Guides and/or DMPs include a section on description of data, metadata standards and interoperability. Metadata are documented according to FAIR guiding principles as described on the S&T intranet.

DATA REGISTRATION The general UT policy states several rules regarding data registration. The University of Twente Research Information System allows, among other things, relatively short and structured registration of metadata on datasets. It is also possible to link to other content, such as datasets. DATA REGISTRATION | S&T WORKING RULE Of currently ongoing and formerly finished research, metadata on datasets is registered in the Research Information System (i.e. PURE) using the ‘dataset’ tab. A manual for registering datasets in Pure can be found here.

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DATA ANALYSES Data analyses comprises of methods of interpretation of figures and numbers, and attempts to find rationale behind the emergence of main findings. Comparisons of research findings to those of others and the literature review are critically important. Analysis is also an ongoing iterative process where data is continuously collected and analyzed almost simultaneously. This is why the rules described in the data collection paragraph above should be read as symbiotic. DATA ANALYSES | S&T WORKING RULE Methods and procedures, statistical or other, of data cleaning, compression and computing are described in a DMP and/or Group RDM Guide. Location and properties of software, code, scripts and algorithms used in, or resulting from, analyses are described in a DMP and/or a Group RDM Guide and they include a version control system, such as Git, and file naming conventions. Standards acknowledged in the research field for documenting analyses are used. For example typesetting equations, typesetting software such as LaTeX and its formats and formatting conventions prescribed by scientific journals in the research field.

DATA SHARING AND EXCHANGE The general UT policy states several rules regarding sharing. Note that it focuses on sharing during research. For sharing after research projects, S&T refers to the section on ‘archiving’. When S&T rules and guidelines mentioned before are applied, no additional ones are needed, except for sharing/exchange with external partners or parties such as data-suppliers.

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DATA SHARING | S&T WORKING RULE Data are shared/exchanged with external partners (non-UT) according to a signed agreement between parties regarding their research cooperation (also see Ownership of data and project results). Signed agreements are drawn up with S&T’s Contractoffice. Signed agreements are compatible with and refer to the Group RDM Guide and/or a DMP describing; terms of use, access and property rights, safe access or transfer procedures and the applicability of legal signed agreements (also see Ownership of data and project results).). Data is shared by giving others access to an ICT system in which data is stored, through links or accounts with certain rights, such as possible in Research Drive (groups) or SURFdrive (private). CURRENTLY: THE UT DECISION TOOL IS CHECKED FOR OPTIONS TO SHARE DATA.

If digital data need to be received from or send to a person, SURFfilesender is used. The exchange includes information about the research project and title of the data(-set). In case of privacy or commercially sensitive data, the encrypted option in SURFfilesender is used; a key to the data is sent separately to the recipient. Commercial services such as WeTransfer are not allowed due to security measures.

OWNERSHIP OF DATA AND PROJECT RESULTS The general UT policy states: “In principle, intellectual property rights on research data (“database right”) shall vest in UT”. At S&T, ownership of processed and analyzed research data and project results vary between or even within projects. Intellectual property rights involved include, but are not limited to, patents, copyrights on for example software and datasets. Related to ownership is the subject of the exploitation rights. These issues are arranged in project agreements, such a consortium agreements. Ownership, storage and access to data and other project results are directly affected by these agreements. S&T working rules are there for the protection against unethical or unlawful use of data by others, to prevent negative effects for the goal of the research and to maintain scientific integrity. DATA OWNERSHIP | S&T WORKING RULE Ownership of data and other project results generated by UT are arranged in a project agreement and follow the rules of the UT and (co-)funder. Agreements with external partners are drawn up with S&T’s Contract-Office. At the beginning of a research assignment for students (e.g. bachelor, master, interns), an agreement is drawn up with S&T’s Contract-Office regarding intellectual property rights. Whether intellectual property rights on research data are (fully) vested in the UT or not, follows from the project agreement and/or rules of the (co-)funder. Rules and statements in Group RDM Guides and/or a DMPs are compared and made compatible with project agreements and/or funder requirements. In case of doubt, S&T’s Contract-Office is consulted. Group RDM Guides or DMPs provide a checklist of documents which will make the conditions under which data may be collected, used, processed and shared clear to all parties involved.

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DATA ARCHIVING The general UT policy states several rules regarding archiving. Additional S&T rules or guidelines on this matter are mostly described in the paragraph Research Data is public, ‘unless’. They apply to data which is kept but not actively used or which is ‘frozen’. An example is a set belonging to one finished research project or publication. Data preservation is a (wider) related term; actions to ensure the long-term preservation and retention of the authoritative nature of digital objects (source: LCRDM). These actions are done before and during research. Appendix B - Repositories for research data offers additional guidance on this subject. DATA ARCHIVING | S&T WORKING RULE DMPs describe which data are ‘frozen’ and kept available after (part of) a research project is finished. Group RDM Guides and/or DMPs describe where data is archived at the UT, which repository (see Appendix B - Repositories for research data) is used for archiving and terms of use, access and property rights, safe access or transfer procedures and the applicability of signed agreements with external partners or parties. The rules regarding data archiving also apply for students that perform research within the group (e.g. bachelor/master students, internships).

RDM COSTS A part of managing research data is the issue of costs. In general, the budget holder(s) of the research group ensure(s) that sufficient resources are available so that researchers can manage their data. The general UT policy mentions issues around costs and resources in the paragraph on ‘archiving’ and in the appendix on roles and responsibilities of the researcher, project

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coordinator/ supervisor(s) and the head of the research group. Issues are explained in for example “Funding research data management and related infrastructures” (Science Europe, may 2016). This serves as a guide for those who have issues or questions related to the matter. RDM COSTS | S&T WORKING RULE Groups can submit their Group RDM Guide and/or DMP to S&T RDM&ICT support staff for assistance in budgeting and financial management of RDM. This includes, for example, applying for funding of data refinement and publishing in data paper journals.

OTHER CONCEPTS ON RDM Data governance and data curation are both terms often used in the light of RDM. Even though important terms, these are not specified with rules or guidelines in this document. Both encompass a broad area of which many items already addressed in this guide. RDM Governance is the process of policymaking and management that guides and oversees research in a consistent and structured manner (source: LCRDM). Data curation is the activity of managing the use of data from its point of creation to ensure it is available for discovery and reuse in the future (source: LCRDM). Research data management is also related to the subject of scientific integrity. This S&T RDM Guide offers rules and guidelines supportive of, or conditional to, maintaining scientific integrity. Other concepts and terms are common in research data management. This S&T RDM Guide cannot and does not address all of them. It aims to be normative, clear and readable.

EXCEPTIONS The working rules in this S&T RDM Guide are composed with researchers. They are meant to improve quality and efficiency. Exceptions to the general UT policy and this S&T RDM Guide may be needed under certain circumstances to achieve such goals. They are therefore always allowed be it under two conditions: RDM EXCEPTIONS | S&T WORKING RULE Exceptions are judged on their merits by the head of the research group or research chair. This means that he/she has the responsibility to decide on exceptions based on their own pro’s and con’s. Exceptions should not result from for example temporary, subjective or biased matters. Exceptions to the UT RDM policy and this S&T RDM Guide are documented in Group RDM Guides and/or DMPs, clearly indicated as being an exception and motivated.

S&T RDM GUIDE; AVAILABILITY, IMPROVEMENTS AND HELP This S&T Guide is available (digitally) on the S&T intranet. This guide is also communicated by other means so that every researcher can easily know about it and find it. A link to the electronic version of this document will be emailed to: • all S&T secretaries of research groups, to be forwarded to employees within the group • all S&T support staff with a role in RDM

S&T RESEARCH DATA MANAGEMENT GUIDE I 20

Structural evaluation of RDM in practice and this guide will offer ideas for improvement. The contributors of this guide have tried hard to avoid typos and other errors. Errors will be discovered nonetheless and other comments will arise. In the light of transparency, efficiency and reaching consensus, S&T will offer an online discussion forum to gather comments and share best-practices, CURRENTLY MICROSOFT TEAMS (S&T (TNW); RDM & ICT SUPPORT), a link to the team is available on the intranet. S&T – RDM IMPROVEMENT AND CONSENSUS Comments, experiences and ideas for improvement of this document and RDM practice are communicated through S&T-RDM Forum, CURRENTLY MICROSOFT TEAMS. All Frequently Asked Questions (FAQs) are shared by S&T support staff on S&T-RDM Forum, CURRENTLY MICROSOFT TEAMS (S&T (TNW); RDM & ICT SUPPORT).

New law, general UT policy, services or agreements may occur in daily practice before changes are described in a new version of this document. This does not have to be a problem: there is a consensus in the faculty that the task of keeping this document up-to-date should not stand in the way of adapting practice to new options. Nevertheless, this document is updated as soon as possible and no earlier than needed: roughly when improvements are substantial in both number and effort. Changes to this document are coordinated by means of the S&T-process: What

Who

offering ideas for improvement

all persons with a role/responsibility in RDM at the UT

collecting ideas for improvement

support staff with the role of RDM support

make a next version in concept, mark changes

staff with the role of document maintenance

review and adapt cycles

members of the S&T RDM working group / faculty board / Principal Investigators

finalize improved version, include marked changes

faculty board

make available / spread

support staff with the role of RDM-support and communications

S&T RESEARCH DATA MANAGEMENT GUIDE I 21

S&T RESEARCH DATA MANAGEMENT GUIDE I 22

APPENDICES APPENDIX A - S&T CLUSTERS CLUSTER

RESEARCH GROUPS & CHAIRS

Applied nanophotonics

Biomedical Photonic Imaging (BMPI) Complex Photonic Systems (COPS) Laser Physics and Non-linear Optics (LPNO) Optical Science (OS) Nanobiophysics (NBP) Adaptive Quantum Optics (AQO) Developmental Bioengineering (DBE) Applied Stemcell Technologies (AST) Biomaterials Science and Technology (BST)

Bioengineering technologies Energy materials and systems (EMS) Imaging and diagnostics

Membrane Science and Technology

Nano electronic materials (NEM)

LINK TO CLUSTER/ GROUP GUIDE *

Energy, materials & systems (EMS)

Physics of Fluids (PoF) Biomedical Photonic Imaging (BMPI) Magnetic Detection and Imaging (MD&I) Medical Cell BioPhysics (MCBP) Multimodality Medical Imaging (M3i) Membrane Surface Science (MSUS) Inorganic Membranes (IM) Soft Matter, Fluidic and Interfaces (SFI) Films in Fluids (FIF) Membrane Technology and Engineering for Water Treatment (MTEWT) Inorganic Materials Science (IMS) Interfaces and Correlated Electron Systems (ICE) Physics of Interfaces and Nanostructures (PIN) Computational Materials Science (CMS) Computational Chemical Physics (CCP) XUV Optics (XUV)

Department of molecules and materials (MOLMAT)

Biomolecular Nanotechnology (BNT) Molecular Nanofabrication (MnF) Sustainable Polymer Chemistry (SPC) Hybrid Materials for Opto-Electronic (HMOE)

Physics of fluids

Physics of Fluids (PoF)

Process and catalysis engineering

Catalytic Processes and Materials (CPM) Sustainable Process Technology (SPT) Mesoscale Chemical Systems (MCS) PhotoCatalytic Syntheses (PCS)

Soft matter

Bio-electronics (BE) Physics of Complex Fluids (PCF) Nano-biophysics (NBP)

Translational physiology

Clinical Neurophysiology (CNPH) Cardio-Respiratory Physiology (CRPH)

*Links to cluster and/or group RDM guides will be added in the future. This will make it easier for every cluster/research group to develop and improve own guidelines. Please contact the RDM&ICT support team if you need assistance with developing your own cluster/group guide. Please also inform them when the first version of your group guides is finished so that this can be shared with others.

S&T RESEARCH DATA MANAGEMENT GUIDE I 23

APPENDIX B - REPOSITORIES FOR RESEARCH DATA This S&T Guide describes appropriate public repositories. Appropriate public repositories are those who are 1) acknowledged by Dutch universities or scientific research institutes; for example 4TU.ResearchData and DANS, or 2) offer community acknowledged certified services; for example the Core Trust Seal and are findable through community acknowledged online registries of repositories for research data; for example the re3data.org A registry is a list of repositories with information on where to find them and what type of data is in the repository. A repository stores the actual items. A data archive is a facility that moves data to an environment for long-term retention. A data archive is indexed and has search facilities, enabling data to be retrieved. Note that there is a difference between repositories for Open Access articles and for research data(-sets). Checklist requirements: 1)

Public repositories have requirements that are a matter from the start of a research project. These are for example listed in: • Preferred file formats, such as from 4TU.ResearchData • Deposit Guidelines • Deposit License Agreements

Funders have requirements. For example NWO (website accessed 10 December 2020) ‘expects researchers to: • Carefully manage all research data generated as part of NWO funded projects; • Preserve these data for at least ten years, unless legal provisions or disciplinespecific guidelines dictate otherwise; • As a minimum, share the research data that underlie research publications alongside those publications, unless this is prevented for reasons of privacy, public safety, ethical restrictions, property rights or commercial interests; • Deposit research data in a trusted repository in such a way that the data are as findable, accessible, interoperable and reusable (FAIR) as possible.’

Publishers, such as scientific / academic journals may have requirements as access to research data belonging to a scientific article or other research output.

4TU.ResearchData as well as DANS are two examples of repositories that can also be used for data that cannot be publicly available for everyone. They offer various access options: - Open access - Embargo (temporary restricted access, open after embargo period ends; embargo period can be chosen by uploader) - Restricted access (others will only get access to the data if the uploader confirms that they are allowed to access the data) In addition, at the time of writing this S&T RDM Guide, a beta version of the UT archive (Areda) is available. This archive should be used in the future to archive all research data at the UT. To publish data and make it available to others, the abovementioned repositories should still be used.

S&T RESEARCH DATA MANAGEMENT GUIDE I 24

APPENDIX C - INTELLECTUAL PROPERTY RIGHTS Developing and applying policy with regard to Intellectual Property on a support level of the UT is a matter of the Knowledge Transfer Office and of legal advisors concerned with IP policy for research projects, currently located at LISA. For more information contact them. As a summary to general IP-rules: Following the Collective Labour Agreement (Dutch: CAO) of Dutch Universities and UT’s Implementing Rules on Intellectual Property: i.

the employee is obliged to perform his duties to the best of his ability, to behave as a good employee and to act in accordance with the instructions given by or on behalf of the UT;

ii.

the employee is obliged to keep all information derived from his position confidential insofar as

iii.

this obligation either follows from the nature of the matter or has been expressly imposed on him;

iv.

if rules have been set up pertaining to agreements between the UT and third parties, an employee who participates in the implementation of such an agreement is obliged to behave in accordance with both the rules and the substance of the agreement in question;

an employee who, during or otherwise coinciding with the performance of his duties, creates a possibly patentable invention or copyright-protected work (for example software), is obliged to report this in writing to the UT and must submit sufficient data to enable the UT to assess the nature of the invention or copyright-protected work; and

vi. vii. viii.

without prejudice to some provisions of some acts (for example the State Patents Act and the Copyright Act), the employee, if and insofar he is entitled to other than moral rights to the invention, the variety or the work, for which the obligation to report set out in point (iv) exists, shall transfer these rights to the UT in whole or in part if so requested, in order to enable it to make use of them in the context of fulfilling its statutory duties within a term to be established later.

Summarized, in general the ownership of project results and the intellectual property rights thereto that are generated by UT-employees shall vest in UT.

S&T RESEARCH DATA MANAGEMENT GUIDE I 25

APPENDIX D - DOCUMENT MANAGEMENT VERSION

AUTHOR(S)

1.18

Koster, N.M.; Fricke, S.S.

Document maintenance and small updates

NAME

POSITION

ORGANISATION

Asseldonk, E. van Becht, H. Benes, N. Borggreve, E.J.A. Burie, R. Drent, M. Fricke, S.S. Haken, B. ten Herek, J. Hofmeijer, J. Kolkman, R. Lammertink, R. Lammertink-Spenkelink, C. Nales-Vogt Olijslager, W. Putten, M. van Rampeltshammer, W.F. Roosmalen, P. van Schoonheyt, C. Steenbergen, W. Stevens, R. Tibben, T. Veld, R.C. van ‘t Verdonschot, N. Versluis, M.

associate professor information specialist vice dean education contract management S&T managing director librarian research data steward S&T and ET full professor dean full professor manager knowledge&technology transfer full professor clinical research coordinator contract management S&T project coordinator / IT auditor full professor PhD candidate legal advisor managing director full professor / vice dean research S&T assistant professor ICT account manager PhD candidate scientific director full professor

ET-BW LISA-EIS S&T S&T-FIN TechMed Centre LISA-EIS LISA-EIS S&T-MD&I S&T S&T-CNPH Novel-T S&T-SFI TechMed Centre S&T-FIN LISA-DSM S&T-CNPH ET-BW Novel-T S&T S&T-BMPI S&T-POF LISA-DSM ET-BW TechMed Centre S&T-POF

Distribution & contribution