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DLCM template for the
SNSF Data Management Plan


prepared by

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Please note

 Recommendations in this document are intended to illustrate the guidelines and other information provided by the SNSF for preparing Data Management Plans1. The SNSF’s guidelines are binding.

This document was prepared jointly by teams from the libraries of EPFL and ETH Zurich, with input from DLCM2 partners, and exists in adapted versions for the two universities. It can also be freely adapted to other institutions’ needs. The examples therefore do not cover all disciplines. Further examples from other subject areas and other feedback are welcome to info@dlcm.ch for possible inclusion in future revisions. 

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License Creative Commons CC BY-SA

 

 



Mandated by

1http://www.snf.ch/en/theSNSF/research-policies/open_research_data/Pages/default.aspx

2 http://www.dlcm.ch 




Table of Contents

 


1. Data collection and documentation

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4. Data sharing and reuse

 

 

 

 

 

 







SNSF Data Management Plan

 


Institution

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ETH Zurich

 


Responsibilities

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Principal Investigator:
(Specify name and email)

Data management plan contact person:
(Specify name and email)

 


Anchor
1. Data collection and documentation
1. Data collection and documentation

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* List of recommended file formats, for ETH Zurich:
https://documentation.library.ethz.ch/display/DD/File+formats+for+archiving

 

Examples of answer to be adapted to your research application

 

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Info
iconfalse
titleExample 1

The data produced from this research project will fall into two categories:

  1. The various reaction parameters required for optimization of the chemical transformation.

  2. The spectroscopic and general characterization data of all compounds produced during the work.

Data in category 1 will be documented in [file format].
Spectroscopic data in category 2 will be produced as [file format] and converted to [file format] for further use. Other characterisation data in this category will be collected in [file format].

We anticipate that the data produced in category 1 will amount to approximately 10 MB and the data produced in category 2 will be in the range of 4 - 5 GB.

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Info
iconfalse
titleExample 4 (from a real Eawag DMP)

There will be two categories of data: NEW data from this project and EXISTING data from the FOEN Lake Monitoring
program.


The NEW data will consist of several file types, all CSV real number format, which are all organized along the same principle: matrixes of times series with various channels, each corresponding to a sensor (number of sensors varies from 1 to10) and very different length, as the sampling frequency varies by several orders-of-magnitudes.

  1. 6 files of CO2, DO, PAR and temperature (24 files at a time; Figure 2), each file only 1 sensor (Delta = 10 min; continuous),
  2. Thetis profiles corresponding to time series (equivalent to depth series) of 10 sensors (Delta = 1 s; 5-10 times per day).
  3. 5 files of CO2 time series for short-term surface flux measurements (several files, one per month),
  4. meteodata file (eight sensors; continuous),
  5. T-Microstructure profiles files (6 sensors at 512 Hz; several files, once per month) and
  6. excel files for individual chemical samples (such as alkalinity, sediment trap estimates, ect; sporadic).

The EXISTING data is already available (CIPAIS, CIPEL) in excel sheets with matrices for the individual samplings and a variable number of parameters (~10 to ~25). The EXISTING data will not be modified and remains with the organizations. We will keep a copy on our computers during the project. We anticipate the data produced in category 1 to amount to several hundred MB for the moored and profiled sensor files and ~100 GB for the T-microstructure profiles; the EXISTING data in category 2 is in the range of ~20 MB.

 


Contact for assistance – ETH Zurich

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This relates to the FAIR Data Principle R1
http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf

 

Recommendations

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What standards, methodologies or quality assurance processes will you use?

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  • a data management system, such as an Electronic Laboratory Notebook / Laboratory Information System (ELN/LIMS). Within ETH domain, examples of used ELN/LIMS: openBISSLims.

 


Examples of answer to be adapted to your research application

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Info
iconfalse
titleExample 8 (template if you̕re using openBIS)

All files produced during this project will be stored in our Electronic Laboratory Notebook (ELN) and Laboratory Information Management System (LIMS) openBIS.

In this ELN, each scientist has a personal folder where to organize projects and experiments. Each experiment is described in the electronic notebook and all data related to the experiment is directly attached to it, in so called “datasets”. Each dataset is immutable, thus different file versions are stored in the lab notebook in different datasets with a manually generated version number. Very large datasets (100s of TBs) are not directly stored in openBIS datasets, but they are linked to the experimental description using an extension to openBIS called BigDataLink. This works similarly to the git version control software, so every time changes are made to the data, these need to be committed to openBIS, which automatically keeps track of the versioning.

 


Contact for assistance – ETH Zurich

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Scientific IT Services
https://sis.id.ethz.ch/

 

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1.3 What documentation and metadata will you provide with the data?

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This relates to the FAIR Data Principles I1, I2, I3, R1, R1.2 & R1.3
http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf.

 

Recommendations

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Indicate all the information required in order to be able to read and interpret the data (context of data) in the future. General documentation of the data is often compiled into a plain text or markdown README file. These formats may be opened by any text editor and are future proofed.

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* Metadata refers to “data about data”, i.e., it is the information that describes the data that is being published with sufficient context or instructions to be intelligible for other users. Metadata must allow a proper organization, search and access to the generated information and can be used to identify and locate the data via a web browser or web based catalogue.

 

Examples of answer to be adapted to your research application

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Info
iconfalse
titleExample 6 (template* if you̕re using openBIS)

In the data management system (openBIS ELN-LIMS), metadata are provided as attributes of the respective datasets. Based on the defined metadata schema, openBIS ELN-LIMS will be configured so that the required metadata is automatically assigned to datasets and / or manually provided by the researcher.

*Information required to read and interpret data (incl. metadata standards) to be filled by researchers.

 


Contact for assistance – ETH Zurich

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This relates to the FAIR Data Principle A1
http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf

 

Recommendations

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Description and management of ethical issues

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The ETH Zurich Compliance Guide
https://rechtssammlung.sp.ethz.ch/Dokumente/133en.pdf

 

Explain how these ethical issues will be managed, for example:

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If you consider that there are no ethical issues in your project, you can use the following statement:
There are no ethical issues in the generation of results from this project.

 


Ethical authorizations

If your project involves human subjects, an ethical authorization from either the cantonal ethics commission or the institutional ethics commission (ETH Zurich Ethics Commission) is needed. This depends on whether your project is invasive/non-invasive and whether or not health-related data is collected/used.

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Safety, Security, Health, Environment department (SSHE / SGU)
https://www.ethz.ch/en/the-eth-zurich/organisation/departments/safety-security-health-environment.html

 

 



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2.2 How will data access and security be managed?

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The main concerns regarding data security are data availability, integrity and confidentiality.

 


Define whether :

  • the level of the data availability risk is : low/medium/high.
  • the level of data integrity risk is : low/medium/high.
  • the level of data confidentiality is : low/medium/high.

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  • All data will be backed-up on a regular basis and access to backup media will be managed according to data access rules. Backups will be stored in another location.
  • All damaged media containing sensitive data will be physically destroyed.
  • All servers will be located in a datacentre with restricted access. The datacentre is based in [country] (preferably data are stored at EPFL/ETH Zurich).
  • No data will be stored on a public cloud / cloud hosted outside Switzerland.
  • No sensitive/personal data will be stored in cloud service external to EPFL/ETH Zurich. “Sensitive data can be for example data related to individuals, data under a non-disclosure agreement, data injuring third-parties rights or legal expertise).
  • All computers storing or computing sensitive data will not be connected to the Internet.
  • All computers storing or computing sensitive data will have a hardened configuration (disk encryption, restricted access to privileged accounts to a small, controlled group of users, restricted or disabled remote access using privileged accounts, disabled guest or default accounts, local firewall, automatic screen lock with password protection, disabled remote out-of-band management (IPMI, Active Management Technology (AMT), etc.), disabled USB ports, removable privacy filter on screens, automatic updates via “Windows Update”, Apple’s “Software Update” or Linux “yum auto-update”, anti-virus software, Adobe’s “Flashplayer” and “Java” runtime).

 


Please note

In May 2018, the EU General Data Protection Regulation (GDPR, Regulation (EU) 2016/679) will come into force. This already now influences future cooperation with any EU-based partners and will be implemented in Swiss law, as well.
GDPR introduces an approach of “Privacy by Design” for parties working with personal or other sensitive data, requiring projects to define their data protection measures from the beginning.

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Info
iconfalse
titleExample 6 (template if you̕re using openBIS)

All data generated in the project will be stored in our open- BIS ELN-LIMS. This operates in a client-server model, which is installed and maintained by the ETH Zurich IT services on ETH Zurich infrastructure. Researchers can access openBIS via any of the most common web browsers. openBIS requires user authentication with ETH Zurich credentials and it provides user right management, so that different users can have different access to all or different parts of the system, as required. Below is a description of the default openBIS roles, which can be modified upon request:

  1. Instance admin. Has full admin powers. Can customize settings, create, modify and delete entities, assign user roles, create data spaces.
  2. Instance observers. Has read-only access to everything in openBIS.
  3. Space admin. Can create, modify, delete entities and assign roles only within a given data space.
  4. Space power user. Can create, modify and delete entities only within a given data space.
  5. Space user. Can create and modify entities only within a given data space.
  6. Space observer. Has read-only access limited to a given data space.

openBIS does not offer any specific option for sensitive data, but the data will be encrypted prior to upload to openBIS. Furthermore, all operations on the system (incl. which users log in and when) are logged, so that it is fully transparent who did what to the data and when.

The data stored in openBIS is physically located on a NAS (network attached storage) provided by the ETH Zurich IT Services. The access to the share’s data is governed by the latest security best practices and only a limited number of employees of the ETH Zurich IT services have access to that share.

 


References
Guidelines for Research Integrity
https://doi.org/10.3929/ethz-b-000179298 
The ETH Zurich Compliance Guide
https://rechtssammlung.sp.ethz.ch/Dokumente/133en.pdf

 

Contact for assistance – ETH Zurich

...

Scientific IT Services
https://sis.id.ethz.ch/

 

 



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2.3 How will you handle copyright and Intellectual Property Rights issues?

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Info
iconfalse
titleExample 4 (EAWAG example)

The source code for analysis will most likely utilize the GNU Scientific Library (GSL), which is licensed under the GNU General Public License (GPL). Therefore we will make our analysis software available under the GPL as well.

 

 



References
Guidelines for Research Integrity
https://doi.org/10.3929/ethz-b-000179298 
The ETH Zurich Compliance Guide
https://rechtssammlung.sp.ethz.ch/Dokumente/133en.pdf

 

Contact for assistance – ETH Zurich

...

 ETH transfer (e.g. for research contracts) 
https://www.ethz.ch/en/industry-and-society/tto.html

 

Anchor
3. Data storage and preservation
3. Data storage and preservation

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Please specify your back-up procedure (frequency of updates, responsibilities, automatic/manual process, security measures, etc.)

 


Recommendations

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Institutional storage solutions:

For ETH Zurich, see storage options here
https://www.ethz.ch/services/en/it-services/catalogue/storage.html
and consult the IT Support Group of your Department
https://www.ethz.ch/services/en/it-services/service-desk/contacts-departments.html.

 

Examples of answer to be adapted to your research application

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Info
iconfalse
titleExample 6 (template* if you̕re using openBIS)

by the ETH Zurich IT Services. openBIS uses a postgres database that stores all metadata. This database is backed up (“pg_dump”) every night with a 7 days retention of the dumps and fully backed-up twice a week with a backup retention of 20 days. The full backup procedure includes a point-in-time recovery that allows a finer granularity (up to minutes) of data recovery in case of a disaster. The database backup is stored on the NAS (network attached storage) provided by the ETH Zurich IT services. The same NAS is used to store the data uploaded to openBIS. This network attached storage is snapshot every night with a 7 days retention, and data is backed up on a proprietary tape library with a retention of 90 days.

Data which is no longer actively needed is moved to the long term storage (i.e. tapes). The tape library where openBIS moves the data has a read-only replica in a different geographical location in order to minimize any data loss.

*For data linked to openBIS with the BigDataLink tool, please provide details of the data location and back-up.

 


Contact for assistance
Digital Curation Office
data-archive@library.ethz.ch
Scientific IT Services
https://sis.id.ethz.ch/

 

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3.2 What is your data preservation plan?

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In particular, comment on the choice of file formats and the use of community standards.

 


Recommendations

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Describe the procedure, (appraisal methods, selection criteria …) used to select data to be preserved.  Note that preservation does not necessarily mean publication (e.g. personal sensitive data may be preserved but never published), but publication means generally preservation. 

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Other criteria from the Digital Curation Center (UK). In addition, select appropriated preservation formats (see section 1.1) and data description or metadata (see section 1.3).

 


Examples of answer to be adapted to your research application

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Info
iconfalse
titleExample 4

Data will be stored on ETH servers and will be preserved for the long term at the ETH Data Archive.

 


Contact for assistance – ETH Zurich
Digital Curation Office
data-archive@library.ethz.ch
 IT Support Groups in the Departments
https://www.ethz.ch/services/en/it-services/service-desk/contacts-departments.html

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  • each data packet and publication has a DOI (or similar persistent identifier) assigned,

  • they are deposited Open Access in a repository harvested by the main data services (e.g.: OpenAire, EUDAT,…).


Examples of answer to be adapted to your research application

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Info
iconfalse
titleExample 3

For this project, the National Geoscience Data Centre (NGDC) (see http://www.bgs.ac.uk/services/ngdc/home.html) is the most suited repository. As it is adapted to geodata, it facilitates storage and allows interactive geographical search. In addition, many other researchers in our field are familiar with it.

This repository requires the deposition under Open Governement Licence (see : http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/), which demands attribution when the data is reused (our dataset must by cited, similarly to the CC BY license).

 


References
SNSF’s criteria for non-commercial respositories
http://www.snf.ch/en/theSNSF/research-policies/open_
research_data/Pages/data-management-plan-dmp-guidelinesfor-
researchers.aspx

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Digital Curation Office
data-archive@library.ethz.ch
Research Collection
https://www.research-collection.ethz.ch/

 


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4.2 Are there any necessary limitations to protect sensitive data?

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This relates to the FAIR Data Principles A1 & R1.1
http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf.

 

Recommendations

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You may mention specifically the conditions under which the data will be made available:

  • there are no sensitive data

  • the data are not available at the time of publication

  • the data are not available before publication

  • the data are available after the embargo of …

  • the data are not available because of the patent of … for a period of…

 


Examples of answer to be adapted to your research application

...

Info
iconfalse
titleExample 4 (Eawag example)

The extensive household survey about water-born diseases poses severe challenges with regard to anonymization, since simple pseudonymization might not be sufficient to guard against the identification of individual households by an inference attack that uses other available information.

Therefore we will be only able to publish summary statistics together with the associated article. If a sufficiently anonymized dataset turns out to still hold scientific value, we will publish it no later than one year after completion of the project.

 


References
Guidelines for Research Integrity
https://doi.org/10.3929/ethz-b-000179298 
 The ETH Zurich Compliance Guide
https://rechtssammlung.sp.ethz.ch/Dokumente/133en.pdf

 

Contact for assistance – ETH Zurich
Digital Curation office
data-archive@library.ethz.ch
Ethics Commission
https://www.ethz.ch/services/en/organisation/boards-university-groups-commissions/ethics-commission.html
Contact: raffael.iturrizaga@sl.ethz.ch

 


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4.3 All digital repositories I will choose are conform to the FAIR Data Principles 

 


[CHECK BOX]

 


Recommendations

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The SNSF requires that repositories used for data sharing are conformed to the FAIR Data Principles. For more information, please refer to the SNSF’s explanation of the FAIR Data Principles.

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4.4 I will choose digital repositories maintained by a non-profit organisation

[RADIO BUTTON yes/no]

 

 



Recommendations

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If you do not choose a repository maintained by a non-profit organization, you have to provide reasons for that.

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Please note that the SNSF supports the use of non-commercial repositories for data sharing. Costs related to data upload are only covered for non-commercial repositories. Check the SNSF’s criteria for non-commercial repositories (http://www.snf.ch/en/theSNSF/research-policies/open_research_data/Pages/data-management-plan-dmp-guidelines-for-researchers.aspx, section 5.2).

 

 



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External useful resources

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