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Data sharing and long-term preservation

5a - How and when will data be shared? Are there possible restrictions to data sharing or embargo reasons?

Science Europe DMP Guidance License: CC BY 4.0 - annotated

5a.1
Explain how the data will be discoverable and shared (for example by deposit in a trustworthy data repository, indexed in a catalogue, use of a secure data service, direct handling of data requests, or use of another mechanism)

Sharing should be read as publishing data in a repository (openly or with controlled access). Unpublished data requires a preservation plan.

5a.2
Outline the plan for data preservation and give information on how long the data will be retained.

In many cases this information should be provided by the data repository. Relevant certification schemes are e.g. CoreTrustSeal, DIN31644, ISO163638.

5a.3
Explain when the data will be made available. Indicate the expected timely release. Explain whether exclusive use of the data will be claimed and if so, why and for how long. Indicate whether data sharing will be postponed or restricted for example to publish, protect intellectual property, or seek patents.

See also questions on IPR under 4 - Legal and ethical requirements.

5a.4
Indicate who will be able to use the data. If it is necessary to restrict access to certain communities or to apply a data sharing agreement, explain how and why. Explain what action will be taken to overcome or to minimise restrictions.

See also 4 - Legal and ethical requirements.

There are different ways of restricting data access: publishing in controlled access repositories or applying reuse limitations (restrictive licenses or tags/ontologies specifying allowed reuse).
Examples of controlled access repositories in Norway: SIKT archive, Federated EGA Norway node
Examples of restrictive licenses: CLARIN ACA (‘academic use’) and CLARIN RES (‘restricted use’) licenses
Examples of defining reuse permissions by ontologies/frameworks: Data Use Ontology (DUO), Data Use Conditions (DUC)

It is crucial to be aware of necessity of access restriction and possibilities to overcome restrictions early in the project, as this is often impossible to implement in retrospect.

Science Europe DMP Evaluation Rubric: sufficiently addressed

  • Clearly describes how the data and/or metadata will be made discoverable and shared.
  • Specifies when data will be shared and under which licence.
  • Includes the name of the repository, data catalogue, or registry where data will or could be shared.
  • Includes information on how long the data will be retained and gives precision on its timely release.
  • Clearly explains, if applicable, why data sharing is limited or not possible, and who can access the data under which conditions (for example, only members of certain communities or via a sharing agreement).
  • Explains, where possible, what actions will be taken to overcome or to minimise data sharing restrictions.

Coverage in RDA Common Standard for maDMP License: Unlicense

[Properties in dmp]

[Properties in dataset]

[Properties in distribution]

Missing:

  • Measures to overcome sharing restrictions
  • Detailed information on restricted access

Other DMP guidance

Guidance from NFR

[Data sharing and reuse]

  • How should the data be findable and how should it be shared? Examples may be that they are made available in a certified data repository, are indexed in a catalogue, that you use a secure data service, direct handling of data requests, etc.
  • When should the data be shared? If, for example, an exclusive right of control granted by legal law is made that affects the time of sharing and, why and for how long? Examples may be that you wait until a scientific publication is available or that you want to protect intellectual property rights, such as patent law, until you have applied for a patent.

Horizon Europe DMP Template

[2.2 Making data accssible - Repository]

  • Have you explored appropriate arrangements with the identified repository where your data will be deposited [2.2 Making data accssible - Data]
  • Will all data be made openly available? If certain datasets cannot be shared (or need to be shared under restricted access conditions), explain why, clearly separating legal and contractual reasons from intentional restrictions. Note that in multi-beneficiary projects it is also possible for specific beneficiaries to keep their data closed if opening their data goes against their legitimate interests or other constraints as per the Grant Agreement.
  • If an embargo is applied to give time to publish or seek protection of the intellectual property (e.g. patents), specify why and how long this will apply, bearing in mind that research data should be made available as soon as possible.
  • Will the data be accessible through a free and standardized access protocol?
  • If there are restrictions on use, how will access be provided to the data, both during and after the end of the project? [2.4 Increase data re-use]
  • Will your data be made freely available in the public domain to permit the widest re-use possible? Will your data be licensed using standard reuse licenses, in line with the obligations set out in the Grant Agreement?
  • Will the data produced in the project be useable by third parties, in particular after the end of the project?
  • Will the provenance of the data be thoroughly documented using the appropriate standards?

FAIRsFAIR FAIR-Aware Additional Guidance License: CC BY 4.0

  • With respect to licensing: Clearly and explicitly license your data, no matter which access level the data has. Find a suitable license (either standard such as CreativeCommons, or bespoke) and find a repository that supports it on Re3data. Preferably use a standard, machine-readable licence. Include the license information in the metadata.
  • With respect to access: Consider and define the access levels of your data early on (public, restricted, embargo, closed, or a combination). Include this information in your metadata, including possible related conditions for reuse.
  • With respect to discoverability and preservation planning: Deposit your data in a trustworthy data repository.
  • For guidance on trustworthy repositories, see 6a.

Knowledge for support staff

  • Embargo policies and funder guidelines
  • Controlled access repositories
  • Ways of limiting data reuse: reuse tags, licenses
  • Trustworthy repositories
  • Certification schemes: CoreTrustSeal, DIN31644, ISO163638

Knowledge for users

  • sharing as in archiving != sharing with collaborators in the active phase (storage = section 3, consortia agreements in section 4)
  • Embargo policies and funder guidelines
  • Valid and invalid reasons of access restritions and how to do this in practice
  • Identifying repositories, re3data, FairSharing
  • Trusted repositories
  • Licensing

Existing sources that can be reused

NTNU - DMP Guidance

NTNU encourages Open Science and open data (see Policy for Open Science at NTNU), but this does not mean that all data should be shared openly. Datasets containing personal information are examples of data that should not be shared without careful considerations. Still, in many cases, it is possible to publish selections of data or to anonymise the data. Another option is to obtain consent for archiving personal data with access restrictions. Note that NSD Data Archive provides options for archiving data with access restrictions. They do not, however, accept anonymised qualitative data due to the efforts required to verify anonymity. Qualitative data with indirect personal identifiers can only be archived with consent from informants.

For more NTNU-relevant information regarding data sharing, see next question.

UiT - DMP guidance

What kind of methods or software are needed to get access to the data? Are the methods/software openly available?

When will the data be made available, and how long will they be stored? (According to section 4.5 in the UiT guidelines, research data shall be made openly accessible as early as possible. For data that form the basis of scientific publications, this means no later than the date of publication. For other data that may be of interest for other research, this will normally be at the end of the project and no later than three years after the project has ended.)

Are there other conditions, restrictions or embargo on the use of the data?

SIKT DMP License: CC BY 4.0

According to the National strategy on access to and sharing of research data and the Research Council’s Policy for Open Access to Research Data, all research data must be made available to all relevant users under equal conditions, so long as there are no legal, ethical or security reasons not to do so. Research data can be made available in secure archives for research data, either centrally at your own institution, in national archives, or in subject-specific archives.

Research data should be shared as open as possible and closed as necessary. See National Strategy for Accessing and Sharing Research Data.

EasyDMP License: CC0-1.0

Data sharing and long-term preservation – covers what steps you will take to ensure your data are accessible and reusable by interested groups.

Describe how and when you will share your data including data you intend to preserve - you should describe how you plan to make the data discoverable (e.g. by depositing the data into a trustworthy data repository).

You should describe when the data will be made available and any access restrictions. You should cover the criteria you will use to identify preservable data. You should also describe how you will ensure the data remain usable during the data’s lifetime (e.g. by providing access to supported tools, documentation on data use and support resources).

SND - Checklist DMP License: CC BY 4.0

[How do you plan to preserve the research material? Find out what rules your university/organization has for preservation and destruction of research records and decide who in the research team is responsible for making sure that the official records from the project are archived. What data will be preserved and/or made accessible, and how do you make that selection? Are there any local regulations? If it is possible to make the data accessible: when, where, and to whom? Will the data be made accessible in a data repository, a subject-specific database, at the university, or by the research group?] Why is this important? Digital data materials need to be actively administered over time, to make sure that they remain accessible and usable. Research materials that are created at a university/public agency must be archived there, in accordance with the Swedish Archives Act (SFS 1990:782). As a rule, official documents at universities and other higher education institutions shall be archived and it is, in principle, unlawful to destroy official documents unless specifically allowed by law, i.e. if there is a right to dispose of records. Raw data files, ethical approvals, research data documentation, and published results must be archived. If you have questions regarding archiving or destruction of documents, please consult with your organization’s archive.

DMP Tuuli License: CC BY 4.0

What part of the data can be made openly available or published? Where and when will the data, or its metadata, be made available?

Describe how you will make data available and findable for reuse. If your data or parts of the data cannot be opened, explain why you publish only metadata. In the case of sensitive data, which cannot be opened, describe the opening of its metadata. Describe the secured preservation procedure of sensitive data in Section 5.2. The openness of research data promotes its reuse.

Tips for best practices

  • You can publish a description (i.e., the metadata) of your data without making the data itself openly available, which enables you to restrict access to the data. Publish your data in a data repository or a data journal.
  • Check re3data.org (https://www.re3data.org/) to find a repository for your data.
  • Prefer repositories or publishers, which provide persistent identifiers (PID) to enable access and citation to the data via a persistent link (e.g. DOI, URN).
  • Remember to check the funder, institutional, disciplinary or national recommendations for data repositories.
  • It is recommended to make all of the research data, code and software created within a research project available for reuse, for example, under a Creative Commons (https://creativecommons.org/choose/), GNU (https://www.gnu.org/licenses/gpl-3.0.en.html) or MIT license (https://opensource.org/licenses/MIT), or under another relevant license.

5b - How will data for preservation be selected, and where will data be preserved long-term (for example a data repository or archive)?

Science Europe DMP Guidance License: CC BY 4.0 - annotated

5b.1
Indicate what data must be retained or destroyed for contractual, legal, or regulatory purposes.

See also 4 - Legal and ethical requirements. Health data would be a typical example where legal obligations for retaining/destroying data exist.

Institutions and funders may set requirements to retain data for a given period. For example, the Research Council of Norway ‘has stipulated as a requirement that research data must be stored in a safe and secure manner for a minimum of 10 years’ (Policy for Open Science, 2020).

5b.2
Indicate how it will be decided what data to keep. Describe the data to be preserved long-term.

5b.3
Explain the foreseeable research uses (and/or users) for the data. Indicate where the data will be deposited. If no established repository is proposed, demonstrate in the DMP that the data can be curated effectively beyond the lifetime of the grant. It is recommended to demonstrate that the repositories policies and procedures (including any metadata standards, and costs involved) have been checked.

There may be several rounds of selecting data for preservation in a project. Criteria to consider: quality of the data (e.g. discarding failed experiments), how difficult would it be to re-create the data, technical feasibility/storage costs for retaining large amounts of raw data (e.g. instead keeping only processed data), limited reuse value (e.g. raw data to transparently document the research process with little reuse value). Particulary if large data volumes are deleted, this should be described in the DMP.

It is desirable to publish all central datasets in research data repositories by end of the project. Criteria for selection for trustworthy repositories should be applied and it should briefly be lined out how the criteria are met. If there is unpublished data remaining at the end of the project, a preservation plan needs to line out who is responsible for the data, and where and how long the data will be kept.

Science Europe DMP Evaluation Rubric: sufficiently addressed

  • Provides details of what data collected or created in the project will be preserved in the long term and clearly indicates for how long. This should be in alignment with funder, institutional, or national policies and/or legislation, or community standards.
  • Provides details of which (versions of) data and accompanying documentation will be retained or destroyed, and explains the rationale (for example contractual, legal requirements, or regulatory purposes).
  • Provides details of how the selection is made, and what possible interest there would be for re-use (or not).
  • Provides details on how the data, accompanying documentation, and any other required technology such as copies of software in specific versions will be archived in the long term.
  • Explains how data will be managed in a sustainable way beyond the lifetime of the grant.
  • Provides the name of the archive or trustworthy repository – or the way to curate and preserve data – that will be used to make data available for re-use.

Coverage in RDA Common Standard for maDMP License: Unlicense

[Properties in dmp]

[Properties in dataset]

[Properties in distribution]

  • #license_table: license_ref [uri], start_date
  • #host_tree: nested, see below e.g. availability, backup_frequency, backup_type, certified_with, description, geo_location, pid_system, storage_type, support_versioning, title, url

[Properties in host]

Missing:

  • Preservation considerations
  • Deleted data
  • Controlled access specifications (e.g. need for data access committee)
  • Dataset logic only partially suited for unpublished datasets

Other DMP guidance

Guidance from NFR

[Data sharing and reuse]

  • How should the data be findable and how should it be shared? Examples may be that they are made available in a certified data repository, are indexed in a catalogue, that you use a secure data service, direct handling of data requests, etc.
  • When should the data be shared? If, for example, an exclusive right of control granted by legal law is made that affects the time of sharing and, why and for how long? Examples may be that you wait until a scientific publication is available or that you want to protect intellectual property rights, such as patent law, until you have applied for a patent.

Horizon Europe DMP Template

[2.2 Making data accssible - Repository]

  • Will the data be deposited in a trusted repository?

[2.2 Making data accssible - Metadata]

  • How long will the data remain available and findable? Will metadata be guaranteed to remain available after data is no longer available?

[4. Allocation of resources]

  • How will long term preservation be ensured? Discuss the necessary resources to accomplish this (costs and potential value, who decides and how, what data will be kept and for how long)? (see also section 6_responsibilities_resources)

[5. Data security]

  • Will the data be safely stored in trusted repositories for long term preservation and curation? (see also section 3_storage_backup)

FAIRsFAIR FAIR-Aware Additional Guidance License: CC BY 4.0

  • With respect to data destruction: Figure out early on by conferring with research data management and ethics specialists if (parts of) your data need to be destroyed (e.g., after a certain amount of time). If this is the case, include general statements about data destruction in the consent forms you use during your study. Make sure that the repository you deposit your data in can handle such destruction and will continue to maintain your metadata afterwards.
  • For guidance on trustworthy repositories, see 6a - Who (for example role, position, and institution) will be responsible for data management (i.e. the data steward)?

Knowledge for support staff

  • Preservation selection best practice.
  • Legal requirements, e.g. health data.
  • Selecting repositories, archive catalogues, definition trusted repositories

Knowledge for users

  • Preservation selection best practice.
  • Consider when preservation decisions will be taken. Might be too early to concretize at planning stage but institutional guidance and requirements should be taken into account.
  • Selecting a trusted repository.
  • Why is it important that metadata are preserved even if data is deleted

Existing sources that can be reused

NTNU - DMP Guidance

Are there any relevant community specific repositories/archives for your type of data? You can search for data repositories/archives at www.re3data.org. Data can also be published through generic repositories like Zenodo, or NTNU’s institutional archive NTNU Open Research Data. This archive is part of DataverseNO, a Core Trust-certified data archive which provides access to the data for at least 10 years after deposition. Archiving data through NTNU Open Research Data/DataverseNO facilitates FAIR data by providing a DOI, following the Dublin Core metadata standard and by providing a license for reuse of data (CC0 is the standard). For more information about specific details regarding the archive, see DataverseNO: About DataverseNO. See also the wiki Research Data Repository.

For principles when choosing licenses for data and other research results, see part 3.1 of the Guidelines for Open Science.

UiT - DMP guidance

Which data will be preserved, and which will be destroyed at the end of the project?

Will (a selection of) the data be long-term preserved, and how is this decided? (According to section 4.2 in the UiT guidelines, researchers have to assess the long-term value of their data, and describe how they will be managed.)

Where will data, metadata, documentation and code associated with the data be archived? (UiT’s archive for open research data, UiT Open Research Data, provides researchers with a safe service for archiving, sharing and publishing open research data.)

SIKT DMP License: CC BY 4.0

Data that forms the basis of scientific articles should be deposited at a relevant archive and made available as early as possible, and usually never later than at the time of publication. Other data that may be of interest to other researchers should also be made available within a reasonable time, and usually never later than three years after the completion of a project, cf. the Research Council’s Policy on Open Access to Research Data (PDF in Norwegian).

SND - Checklist DMP License: CC BY 4.0

[Before you preserve the data material and make it accessible, you may want to prepare the material. What file formats are suitable for long-term preservation? What documentation should be included with the data material after the project has ended? Are there any ethical and legal restrictions on the material, which mean that the data need to be processed (e.g. de-identified) before they can be made accessible? Where do you plan to archive and/or make the data accessible? Contact them in good time for assistance in how to prepare the material.] Why is this important? Digital file formats run the risk of becoming obsolete. If this should happen, future software may not be able to read and present the information in the files correctly, and valuable research data could be lost. Therefore, you should choose file formats that are more likely to remain usable in the future, i.e. formats that are commonly used, non-proprietary, and have an open technical specification. Another benefit of choosing those formats is that you won’t have to convert the file formats at the end of the project. It isn’t always possible to choose a format that meets all criteria, as specific instruments, analysis tools, or developed software can affect the choice of data formats. If that’s the case, it’s important to plan for how to guarantee that the data material can be preserved.

When the project is finished and the data material shall be made accessible, it may, due to ethical and legal restrictions, be important to guarantee that the individuals in the study cannot be re-identified (i.e. identified through indirect identifiers in the data material).

DMP Tuuli License: CC BY 4.0

Where will data with long-term value be archived, and for how long? (5.2) Briefly describe what part of your data you will preserve, where it is preserved, and for how long. Long term preservation means that data is preserved for as long as necessary, for several decades or even centuries.

You can categorise your data sets according to the anticipated preservation period: A) Data to be destroyed upon the ending of the project B) Data to be archived for a verification period, which varies across disciplines, e.g., 5–15 years C) Data to be archived for potential re-use, e.g., for 25 years D) Data with long-term value to be archived by a curated facility for future generations for tens or hundreds of years

You will need to decide which of your research data to preserve and dispose of. Data that is unique or difficult to replicate might have long-term value and be fit for preservation. Special long term data repositories should be used for digital preservation.

Tips for best practices

  • Decisions about preserving data should begin during the data management planning stage, and should take into account e.g. institutional guidance and requirements.
  • Use data repositories with a commitment to long-term curation, e.g. Fairdata Digital Preservation Service is dedicated for research datasets that have significant value to the organization or on a national level currently and especially also in the future. Contact your home organisation for further information.

5c - What methods or software tools will be needed to access and use the data?

Science Europe DMP Guidance License: CC BY 4.0 - annotated

5c.1
Indicate whether potential users need specific tools to access and (re-)use the data. Consider the sustainability of software needed for accessing the data.

Access protocols for controlled access should be described (see FAIR principles A1.2).

Preferance to open formats should be specified in 1b - What data (for example the kind, formats, and volumes) will be collected or produced?.
Software/computer code generated in the project should be managed as research output.

5c.2
Indicate whether data will be shared via a repository, requests handled directly, or whether another mechanism will be used?

There is few reasons to share data outside of data repositories after completion of the project.

Science Europe DMP Evaluation Rubric: sufficiently addressed

  • Clearly indicates which specific tools or software (for example specific scripts, codes, or algorithms developed during the project, version of the software) potential users may need to access, interpret, and (re-)use the data.
  • Provides information, if relevant, on any protocol to access the data (for example if authentication is needed or if there is a data access request procedure).

Coverage in RDA Common Standard for maDMP License: Unlicense

[Properties in dmp]

[Properties in dataset]

[Properties in distribution]

  • #host_tree: nested, e.g. availability, backup_frequency, backup_type, certified_with, description, geo_location, pid_system, storage_type, support_versioning, title, url

Missing:

  • specification of e.g. software needed to access data

Other DMP guidance

Guidance from NFR

[Data sharing and reuse]

  • Do potential users need specific tools, such as software, to access and (re)use the data? The sustainability of the software for future access to the data should be considered.

FAIRsFAIR FAIR-Aware Additional Guidance License: CC BY 4.0

  • Include the tools and/or code needed to reuse your data in the metadata of your dataset, as well as meaningful and explicit links to other kinds of research output (e.g., previous versions, other relevant datasets, related publications, data sources, data creators, data collectors, funding organizations, host institutions) to increase potential for reuse.
  • For guidance on access, see 5a.

Knowledge for support staff

  • Data provenance
  • Persistent file formats
  • Dependencies for software code.
  • Controlled access systems, some technical understanding of authentification methods.

Knowledge for users

  • Data provenance
  • Persistent file formats
  • Dependencies for software code
  • Controlled access archives

Existing sources that can be reused

NTNU - DMP Guidance

NTNU recommends the use of open source and open formats where possible. If the data is only available in proprietary formats requiring specific software or tools, consider the possibility of providing an additional copy in an open format even if that entails data loss. If specific code, scripts or algorithms are developed during the project, they can be published using the GitHub/Zenodo-integration. See also the wiki Open source. For principles when choosing licenses, see part 3.1 of the Guidelines for Open Science.

UiT - DMP guidance

What kind of methods or software are needed to get access to the data? Are the methods/software openly available?

Is special software for reading/interpreting the data necessary?

SND - Checklist DMP License: CC BY 4.0

[Will a specific software or tool be required to use the data material? If it is: is it possible to add the software or tool to the data material, and if so, what documentation is required for someone to be able to use it? If it isn’t possible to add the software/tool, what is required to be able to use the data material?]

Why is this important?

To make it possible to continue using the data material, it’s important to enter information about what software or tools that are needed, as non-proprietary software isn’t always sufficient. Some tools may also be based on a certain software and, if possible, it’s of great help to include the software with the material, e.g. by open source code.

5d - How will the application of a unique and persistent identifier (such as a Digital Object Identifier (DOI)) to each data set be ensured?

Science Europe DMP Guidance License: CC BY 4.0 - annotated

5d.1
Explain how the data might be re-used in other contexts. Persistent identifiers (PIDs) should be applied so that data can be reliably and efficiently located and referred to. PIDs also help to track citations and re-use.

5d.2
Indicate whether a PID for the data will be pursued. Typically, a trustworthy, long-term repository will provide a persistent identifier.

At what granularity are PIDs provided? (collection, dataset, each item in a dataset?)

Science Europe DMP Evaluation Rubric: sufficiently addressed

  • Specifies how the data can be re-used in other contexts.
  • Clearly indicates if and which PIDs are provided for all datasets, individual datasets, data collections, or subsets. If PIDs will not be used, it explains why.
  • Clearly presents the approach, and the choice of identifiers is justified and refers to international standards.

Coverage in RDA Common Standard for maDMP License: Unlicense

[Properties in dmp]

[Properties in dataset]

  • #distribution_tree: nested, see below e.g. access_url, available_until, byte_size, data_access, description, download_url, format, host, license, title

[Properties in distribution]

  • #host_tree: nested, e.g. availability, backup_frequency, backup_type, certified_with, description, geo_location, pid_system, storage_type, support_versioning, title, url

[Properties in host]

  • #host_pid_system_tree: ark, arxiv, bibcode, doi, ean13, eissn, handle, igsn, isbn, issn, istc, lissn, lsid, pmid, purl, upc, url, urn, other [controlled]

Missing:

  • possibility to specify other PID?

Other DMP guidance

Guidance from NFR

[Data sharing and reuse]

  • Will a persistent identifier (DOI) for the datasets be used? Persistent identifiers should be applied to metadata and datasets so that they can be findable and referenced in a reliable and efficient manner. Using DOI also ensures that citations and reuse can be tracked. A certified data repository will often provide this to (meta)data deposited there.

Horizon Europe DMP Template

[2.2 Making data accessible - Repository]

  • Does the repository ensure that the data is assigned an identifier? Will the repository resolve the identifier to a digital object

FAIRsFAIR FAIR-Aware Additional Guidance License: CC BY 4.0

  • Choose a data repository to deposit your data in that assigns your desired persistent identifiers (e.g., a DOI, Handle, or ARK for the data, or an ORCID for the researchers). Use Re3data or FAIRsharing to find a suitable repository.

Knowledge for support staff

  • Types of PIDs
  • Research catalogues

Knowledge for users

  • The archives decides for you, types of PIDs

Existing sources that can be reused

NTNU - DMP Guidance

Persistent identifiers like DOIs are usually issued by data repositories (e.g., Zenodo, NTNU Open Research Data etc.). In most cases, your choice of repository will therefore determine the use of persistent identifiers.

SIKT DMP License: CC BY 4.0

Research data that are going to be shared and published should be equipped with international standard licenses that have as few restrictions as possible on access and reuse purpose.

The licenses that are marked with “Open Definition Recommended” are licenses that are conformant with the principles of open knowledge, as defined by the Open Knowledge Foundation.

EasyDMP License: CC0-1.0

Describe how you will assign persistent identifiers to your data

You should describe who will provide persistent identifiers. In many cases, the long-term repository will provide the identifiers. If you plan to provide the identifiers yourself, you should choose a service that is mandated to maintain the identifiers for the long-term (such as DOI issued by Bibsys).

SND - Checklist DMP License: CC BY 4.0

[Will the material receive a persistent identifier (PID), and what type of PID? Enter the PID here if you have one, or when you get one.]

Why is this important? A persistent identifier is a unique digital ID that refers to one or more objects, digital or physical. In research, it’s common practise to issue a PID to publications or research data that are preserved for a long time and made accessible through digital resources. It’s important to enter this information to show funders that you have thought about essential factors around the access to data. As there are different types of PID, depending on e.g. field of research or where the data material is preserved, you may want to explore which PID is most suited for your material. Data that are made accessible through SND receive a persistent identifier called a DOI (Digital Object Identifier).

Contributors
Jenny Ostrop Lead

University of Bergen (UiB)

Svein Høier Contributor

Norwegian University of Science and Technology (NTNU)