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Dictionary terms
20 resultsFAIR4RS Software Citation Principles
An extension of the FAIR Guiding Principles to research software, articulating that software should be Findable, Accessible, Interoperable, and Reusable, with the precise interpretations adapted to software's distinctive properties (executability, versioning, dependencies).
FAIRsharing (concept)
A curated, community-driven registry of databases, standards (metadata, identifiers, formats, terminologies), and data policies relevant to research data, maintained at the University of Oxford with linkage to funders, journals, and standards organisations.
AI fairness
A property of an AI system whereby its outputs satisfy a defined criterion of equitable treatment across specified groups — common criteria include demographic parity, equalised odds, equal opportunity, and calibration parity — recognising that these criteria are often mutually incompatible.
Archive phase
The post-closeout lifecycle phase during which project records, datasets, code, and documentation are deposited in appropriate repositories for long-term preservation, access, and possible re-use.
SDG 9 (Industry Innovation)
The ninth Sustainable Development Goal: build resilient infrastructure, promote inclusive and sustainable industrialisation and foster innovation.
Patient partner
A patient, service user, carer or member of the public who is actively involved in shaping and conducting research as a recognised partner, typically with named role, compensation and decision-making influence.
Author fee equity
The principle that author-side publication charges (APCs, page charges, submission fees) should not act as a barrier to publication, with equitable access ensured through waivers, transformative agreements, diamond OA alternatives or funder support.
African Open Science Platform (concept)
A continental initiative coordinated by the African Academy of Sciences, NRF South Africa and partners, working to develop open-science infrastructure, policies and capacity across African research institutions.
GIDA (Global Indigenous Data Alliance)
An international network of Indigenous-led organisations and individuals advancing Indigenous Data Sovereignty and Indigenous Data Governance globally, and the source of the CARE Principles for Indigenous Data Governance.
CARE Principles
A set of principles for Indigenous data governance articulated by the Global Indigenous Data Alliance in 2019, encompassing Collective Benefit, Authority to Control, Responsibility, and Ethics, intended to complement the FAIR data principles with people- and purpose-oriented obligations.
GDPR (General Data Protection Regulation)
The European Union regulation that governs the processing of personal data of individuals in the EU, requiring a lawful basis for processing, transparency to data subjects, data-minimisation, security, and accountability, with extraterritorial application where data subjects in the EU are targeted or monitored.
Singapore Statement on Research Integrity (2010)
A short framework statement of four principles and fourteen responsibilities for the responsible conduct of research, adopted at the 2nd World Conference on Research Integrity in Singapore in 2010. It is referenced as a foundational global statement rather than a regulatory instrument.
Research integrity
The adherence to professional values and practices (honesty, rigour, transparency, accountability, fairness) such that research can be trusted by other researchers and by society. A practice exhibits research integrity if it could be openly described to peers without embarrassment or sanction.
Trustworthy AI
AI systems exhibiting properties (lawful, ethical, technically robust) that warrant the trust of users, affected parties, and society, as articulated in the EU High-Level Expert Group's framework and adopted in subsequent regulation.
Responsible AI
An umbrella term covering the design, development, deployment, and governance practices intended to ensure AI systems are ethical, fair, transparent, accountable, robust, secure, and respectful of privacy.
Bias audit (model)
An audit specifically focused on disparate model performance across demographic, geographic, or contextual sub-groups, including testing for direct, proxy, and intersectional disparities.
Open data
The practice of making research data freely available for any user to access, use, modify, and share, subject only to attribution requirements, typically through deposit in a public repository under an open licence.
Preservation commitment (in DMP)
A statement in a DMP specifying which datasets will be preserved beyond project end, in which repository, for how long, and under what conditions.
DMP assessment
The structured rating of a DMP against a published rubric to produce a comparable score across plans, used in funder evaluation, institutional benchmarking, and capacity-building.
DMP template
A funder-, institution-, or community-specific structured set of questions and guidance used to elicit the content of a Data Management Plan from researchers.
Dictionary domains
1 resultNews & perspectives
10 resultsNews · 2026-06-27
The FAIR Digital Object (FDO) Framework: Structuring Machine-Actionable Science
1. Introduction to the Role of FAIR Digital Objects in Scholarly Infrastructure In the contemporary landscape of global science, open research practices, and institutional data governance, establishing robust standards is crucial. The integration of FAIR Digital Objects represents a landmark advancement in addressing long-standing hurdles in scholarly communication, administrative reporting, and metadata curation. This extensive […]
News · 2026-06-25
FAIR4RS Principles in Practice: Applying FAIR Data Concepts to Research Software
1. Introduction to the Role of FAIR4RS Principles in Scholarly Infrastructure In the contemporary landscape of global science, open research practices, and institutional data governance, establishing robust standards is crucial. The integration of FAIR4RS Principles represents a landmark advancement in addressing long-standing hurdles in scholarly communication, administrative reporting, and metadata curation. This extensive guide provides […]
News · 2026-06-18
FAIR Principles for Research Data Explained
The FAIR principles make research data Findable, Accessible, Interoperable and Reusable. Published by Wilkinson et al. in 2016, they emphasise persistent identifiers and rich metadata. This explainer defines each principle and clarifies how FAIR differs from open data.
News · 2026-06-15
FAIR data in practice: making research data findable and reusable
FAIR is widely cited and often misunderstood. What Findable, Accessible, Interoperable and Reusable actually require in practice, why FAIR is not the same as open, and the concrete steps that move a dataset from a hard drive to a genuinely reusable output.
News · 2026-06-15
Software Citation in Scholarly Publishing: Implementing the FAIR4RS Principles
Introduction to Software Citation in Scholarly Spaces Research software is a vital component of modern scientific discovery. However, software has historically been treated as supplementary material rather than a citeable, first-class scholarly output, leading to reproducibility gaps and a lack of academic credit for developers. The FAIR4RS Principles Explained The FAIR Principles for Research Software […]
News · 2026-06-13
FAIR Data Principles in Action: A Practical Implementation Guide for Researchers
Introduction The FAIR Data Principles, published in 2016, provide a guideline for improving the Findability, Accessibility, Interoperability, and Reusability of digital assets. They emphasize machine-actionability—the capacity of computational systems to find, access, interoperate, and reuse data with minimal or no human intervention—because humans increasingly rely on computational support to deal with data at scale and […]
News · 2026-06-11
Sensitive and controlled-access data: FAIR for data that cannot be fully open
Not all research data can be made open. Health records, personal data and other sensitive material must be protected, yet they can still be made findable and reusable under controlled access. How FAIR principles, data-access committees and synthetic data reconcile openness with confidentiality.
News · 2026-06-11
Computational reproducibility: containers, workflows and FAIR4RS
A result you cannot re-run is a claim, not a finding. How containers, workflow languages, Software Heritage and the FAIR4RS principles turn computational work into something others can actually reproduce.
News · 2026-06-10
The SCOPE framework for responsible research evaluation: a practical model for designing fair evaluations
Declarations like DORA tell us what to stop doing in research assessment. The INORMS SCOPE framework offers something different: a step-by-step process for designing an evaluation that is fair, fit for purpose and grounded in what an organisation actually values.
News · 2026-06-10
CARE alongside FAIR: Indigenous data governance and the TK Labels
FAIR makes data open by default; CARE asks whose data it is and who governs it. The CARE Principles, Indigenous data sovereignty and the TK Labels set out a people-and-purpose framework that sits alongside FAIR, not against it.
