Glossary¶
This page provides explanations of key terms used on the DataverseNO Information Website.
- Authorship identifies the people who have made substantial intellectual contributions to creating, collecting, producing, or preparing a dataset. In DataverseNO, authors are credited in the dataset metadata and dataset citation.
- Citation
- A citation provides the information needed to identify, locate, and acknowledge a dataset or data file. In DataverseNO, citations are automatically generated and can be copied directly from dataset and file landing pages. Dataset citations normally include the authors, title, publication year, repository, version, and DOI.
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- Collection
- A collection is an area within a repository used to organize and manage related datasets. In DataverseNO, most collections represent partner institutions. Some collections represent projects, research groups, research infrastructures, or other organizational units.
- CoreTrustSeal
- CoreTrustSeal is a certification that demonstrates that a repository meets recognized requirements for the trustworthy management, preservation, and provision of digital resources. DataverseNO obtained CoreTrustSeal certification for the first time in 2020 and is currently renewing its certification.
- Curation
- In DataverseNO, curation is the process of reviewing a dataset and providing guidance on metadata, documentation, file formats, licensing, and other aspects that support data sharing and reuse. Datasets are curated before publication to help align them with DataverseNO policies, deposit guidelines, and recognized good practices for research data management, in particular the FAIR Principles.
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- Curation Label
- A curation label is used by DataverseNO curators to track and communicate the progress of a dataset through the curation workflow.
- Curator
- A curator is a member of research support staff who reviews datasets and provides guidance to depositors. Curators help ensure that datasets comply with DataverseNO policies, deposit guidelines, and recognized good practices for research data management. Information about the curators at DataverseNO partner institutions is available on the People page.
- Data requiring protection
- Data requiring protection are research data that cannot be shared openly in their raw or current form. This may be because of legal, ethical, institutional, or security-related constraints. In DataverseNO, this includes: - **Personal and health data:** Data that can be linked to identifiable persons or medical records. - **Indigenous data:** Data that are subject to cultural oversight, traditional ownership, or specific governance protocols. - **Intellectual property:** Copyrighted material or commercially sensitive data. - **Environmental risks:** Sensitive biodiversity data, such as locations of endangered species. - **Safety risks:** Data involving geopolitical or security-related concerns. - **Rights restrictions:** Data for which the researcher does not have the necessary rights and permissions. Such data must be handled before they can be shared openly. This may include preparatory steps such as anonymization. If the data cannot be prepared for open sharing, they should be directed to a suitable alternative repository instead of being deposited directly in DataverseNO.
Further reading:
- DataverseNO Data Privacy Guide
- Dataset
- A dataset consists of one or more files together with metadata and documentation describing them. In DataverseNO, datasets are the primary units that are archived, curated, published, cited, and preserved.
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- DataverseNO Deposit Agreement
- The DataverseNO Deposit Agreement defines the rights and responsibilities of depositors and DataverseNO when datasets are submitted to the repository. The agreement forms part of the DataverseNO Policy Framework and applies to all datasets deposited in DataverseNO.
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- DataverseNO Deposit Guidelines
- The DataverseNO Deposit Guidelines describe how datasets should be organized, documented, described, licensed, uploaded, and submitted for review and publication in DataverseNO. The guidelines help depositors align their datasets with DataverseNO requirements and recognized good practices for research data management. The guidelines are available on the Deposit Guidelines page.
- DataverseNO Organizational Agreement
- The DataverseNO Organizational Agreement describes the governance, roles, responsibilities, competencies, and funding arrangements of the DataverseNO consortium and its partner institutions.
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- DataverseNO Policy Framework
- The DataverseNO Policy Framework consists of the policies, plans, and related documents that define how the repository is governed, managed, preserved, and used. An overview of the framework and its constituent documents is available on the DataverseNO Policy Framework page.
- Deposit
- A deposit is the submission of a dataset, including files, metadata, and documentation, to a repository for review, publication, and preservation.
- Depositor
- A depositor is a person who creates or manages a dataset submission and submits it for review and publication in DataverseNO.
- Designated Community
- A Designated Community is the group of users that a repository expects to access and reuse preserved data. DataverseNO aims to ensure that published datasets remain understandable to their intended research communities.
- Digital Object Identifier (DOI)
- A Digital Object Identifier (DOI) is a globally unique and persistent identifier that provides a stable reference to a digital resource. In DataverseNO, datasets and individual files within datasets are assigned DOIs that support citation, discovery, and long-term access.
- Double-Blind Peer Review
- Double-blind peer review is a review process intended to reduce bias by keeping both authors and reviewers anonymous during manuscript evaluation.
- Embargo
- An embargo is a temporary restriction on access to one or more files in a dataset. In DataverseNO, embargoes may be applied only to unpublished data files and normally for no longer than 2 years. During the embargo period, the embargoed files are inaccessible, while the dataset metadata and README file remain publicly available. Embargoes expire automatically on a specified date, after which the files become openly accessible. Once a dataset has been published, the embargo period cannot normally be extended or modified by the depositor. Embargoes are intended for temporary restrictions on access to files and should not be used to delay the publication of datasets associated with manuscripts under review.
- FAIR
- FAIR is a set of guiding principles for research data management and stewardship. FAIR aims to ensure that research data and metadata can be found, accessed, integrated with other data and systems, and reused by both humans and machines.
- File Format
- A file format defines how information is encoded and stored in a digital file. Some file formats are better suited for long-term preservation and reuse than others.
- Harvesting
- Harvesting is the process whereby one system collects metadata from another system. It helps make datasets discoverable through external search and discovery services.
- Institutional Collection
- An Institutional Collection is a collection within DataverseNO that is managed and curated by a partner institution and contains datasets associated with that institution.
- License
- A license specifies the permissions and conditions that apply to the reuse of a dataset. In DataverseNO, every dataset must be assigned a license or equivalent terms of use when it is deposited. Licensing information is included in the dataset metadata and helps users understand how the data may be accessed, used, and shared. DataverseNO recommends open licenses that facilitate data reuse, particularly Creative Commons CC0, while allowing depositors to specify alternative terms of use where appropriate.
- Metadata
- Metadata is structured information that describes a dataset, such as its title, authors, keywords, dates, methods, and license. Metadata helps users find, understand, cite, and reuse data.
- Open Access
- Open Access means that digital resources are made available online without price barriers or access restrictions.
- Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH)
- Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) is a protocol that allows metadata to be harvested automatically from repositories and reused in external discovery services.
- Open Researcher and Contributor ID (ORCID)
- Open Researcher and Contributor ID (ORCID) is a globally unique identifier that distinguishes researchers and helps connect them to their publications, datasets, and other research outputs.
- Open Science
- Open Science is an approach to conducting and communicating research that seeks to make research processes and outputs as open, transparent, accountable, and reusable as possible. It encourages practices such as sharing research data, publications, methods, software, and other research outputs, thereby supporting verification, collaboration, and the reuse of research results.
- Persistent Identifier (PID)
- A Persistent Identifier (PID) is a stable identifier designed to remain valid over time and provide a reliable reference to a specific entity. PIDs can be assigned to digital resources such as datasets and publications, as well as to researchers, organizations, and other entities. Examples include DOI identifiers for datasets, ORCID identifiers for researchers, and ROR identifiers for research organizations.
- Preservation
- Preservation consists of organizational and technical measures intended to keep datasets accessible, understandable, and usable over time.
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- Preview URL
- A Preview URL is a private link that provides access to an unpublished dataset without making the dataset publicly accessible. Users accessing a dataset via a Preview URL can view and download the dataset and its files, but cannot edit the dataset. In DataverseNO, Preview URLs are typically created by curators upon request and may be used, for example, to provide access to editors and reviewers during peer review of a publication manuscript related to the dataset.
- README File
- A README file is a document that provides the information needed to understand, interpret, and reuse a dataset. In DataverseNO, a README file is a mandatory component of all datasets and must be based on an approved README template or contain equivalent information. Typical contents include information about the dataset, methods, files, terms of reuse, and contact details.
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- Repository
- A repository is a service that stores, manages, preserves, and provides access to digital resources such as datasets. In addition to providing storage, repositories support activities such as discovery, citation, curation, sharing, preservation, and reuse. DataverseNO is a repository for research data.
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- Research Data
- Research data are data that are created, collected, observed, measured, or generated during research and that are used as evidence in the research process or needed to validate research findings. Research data may take many forms, including measurements, observations, survey responses, interview transcripts, images, audio recordings, software-generated data, models, and code.
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- Research Organization Registry (ROR)
- The Research Organization Registry (ROR) provides unique identifiers for research organizations and helps connect datasets, publications, researchers, and institutions.
- Terms of Use
- Terms of Use specify the permissions, restrictions, responsibilities, and conditions that apply when using a dataset. Terms of Use may take different forms, including standardized licenses and customized reuse conditions defined by the depositor. In DataverseNO, every dataset must have Terms of Use, whenever possible in the form of a standardized open license to facilitate the discovery, sharing, and reuse of research data.
- Trustworthy Digital Repository (TDR)
- A Trustworthy Digital Repository (TDR) is a repository that follows recognized standards and practices for the long-term management, preservation, and provision of access to digital resources.
- Version Control
- Version Control is the practice of recording and managing changes to a dataset and its metadata. In DataverseNO, changes made after publication result in a new dataset version while previous versions remain accessible.
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