The FAIR data principles (Wilkinson et al. (Meta)data are associated with detailed provenance, R1.3. Following the lead of the European Commission and Horizon 2020, Irish funders, including the Health Research Board (HRB) … For instance, principle F4 defines that both metadata and data are registered or indexed in a searchable resource (the infrastructure component). The ultimate goal of FAIR is to optimise the reuse of data. For example, publically available data may lack sufficient documentation to meet the FAIR principles, such as licensing for clear reuse. In diesem Beitrag erläutern wir die jeweiligen Anforderungen und geben Beispiele. Gemäß der FAIR-Prinzipien sollen Daten " F indable, A ccessible, I nteroperable, and R e-usable" sein. For example, publically available data may lack sufficient documentation to meet the FAIR principles… Het vraagt immers om een herziening van het huidige datamanagement. En wanneer u zelf gebruik maakt van andermans data, hoe weet u dan dat alles klopt? In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing. The term FAIR was launched at a Lorentz workshop in 2014, the resulting FAIR principles were published in 2016. FAIR data are data which meet principles of findability, accessibility, interoperability, and reusability. Other international organisations active in the research data ecosystem, such as CODATA or Research Data Alliance (RDA) also support FAIR implementations by their communities. This is what the FAIR principles are all about. The guidelines are timely as we see unprecedented volume, complexity, and … [2], At the 2016 G20 Hangzhou summit, the G20 leaders issued a statement endorsing the application of FAIR principles to research. (Meta)data are registered or indexed in a searchable resource[2]. The FAIR principles are designed to support knowledge discovery and innovation both by humans and machines, support data and knowledge integration, promote sharing and reuse of data, be applied across multiple disciplines and help data and metadata to be ‘machine readable’, support new discoveries through the harvest and analysis of multiple datasets and outputs. Metadata clearly and explicitly include the identifier of the data they describe, F4. This is an initiative of the stakeholders in the research process including academics, industry, funders and scholarly publishers to design and implement a set of principles that are called the FAIR Data Principles. On this website, we explain the principles (based on the DTLS website) and translate them into practical information for Radboud University researchers. The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. FAIR Principles. Why use the FAIR principles for your research data? The principles have since received worldwide recognition by various organisations including FORCE11 , National Institutes of Health (NIH) and the European Commission as a useful framework for thinking about sharing data in a way that will enable maximum … This includes working on policy, developing what FAIR means for specific disciplines, data and output types, supporting developers when developing code that enables FAIR outputs and building skills for research support staff and researchers. 1. (Meta)data meet domain-relevant community standards. For the most part, these efforts are being led by research librarians, who have the unique skills and expertise needed to help their institutions become FAIR compliant. Principle 1: Creating Opportunities for Economically Disadvantaged Producers Poverty reduction by making producers economically independent. Data are described with rich metadata (defined by R1 below), F3. In 2017 Germany, Netherlands and France agreed to establish[6] an international office to support the FAIR initiative, the GO FAIR International Support and Coordination Office. The CARE Principles for Indigenous Data Governance were developed by the Global Indigenous Data Alliance (GIDA) in 2019 to complement the FAIR principles and other movements towards Open Data. This involves data stewardship which is about proper collection, annotation and archiving of data but also preservation into the future of valuable digital assets. The Principles define characteristics that contemporary data resources, tools, vocabularies and infrastructures should exhibit to assist discovery and reuse by third-parties. Reusing existing data sets for new research purposes is becoming more common across all research disciplines.. Research funders and publishers are asking researchers to make data sets produced in their projects available to others. FAIR: findable, accessible, interoperable, reusable) primarily focus on characteristics of data that will facilitate increased data sharing among entities while ignoring power differentials and historical contexts. I2. Accessible Once the user finds the required data, she/he needs to know how can they be accessed, possibly including authentication and authorisation. Sci Data 3, 160018 (2016) doi:10.1038/sdata.2016.18) and are now a standard framework for the storage and sharing of scientific information. Researchers need to consider data management and stewardship throughout the grant procedure and their research project. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings. [3][4], In 2016 a group of Australian organisations developed a Statement on FAIR Access to Australia's Research Outputs, which aimed to extend the principles to research outputs more generally.[5]. Adopting the FAIR data principles requires institutions to strengthen their policies around the sharing and management of research data. Anders herum gilt: Wenn Open Data gut dokumentiert und maschinenlesbar sind, eine offene Lizenz haben, herstellerunabhängige Formate und offene Standards verwendet, entsprechen sie auch dem FAIR-Konzept. The General Data Protection Regulation … Metadata are accessible, even when the data are no longer available. These guidelines are based on the FAIR Principles for scholarly output (FAIR data principles [2014]), taking into account a number of other recent initiatives for making data findable, accessible, interoperable and reusable. (Meta)data use vocabularies that follow FAIR principles, I3. The FAIR Data principles act as an international guideline for high quality data stewardship. Most of the requirements for findability and accessibility can be achieved at the metadata level. GDPR Compliance. The context FAIR DATA – The role of scientists FAIR Repository – The role of the repository Each dataset is assigned a globally unique and persistent identifier (PID), e.g. [14], Data compliant with the terms of the FAIR Data Principles, Acceptance and implementation of FAIR data principles, Sandra Collins; Françoise Genova; Natalie Harrower; Simon Hodson; Sarah Jones; Leif Laaksonen; Daniel Mietchen; Rūta Petrauskaité; Peter Wittenburg (7 June 2018), "Turning FAIR data into reality: interim report from the European Commission Expert Group on FAIR data", Zenodo, doi:10.5281/ZENODO.1285272, GO FAIR International Support and Coordination Office, Association of European Research Libraries, "The FAIR Guiding Principles for scientific data management and stewardship", Creative Commons Attribution 4.0 International License, "G20 Leaders' Communique Hangzhou Summit", "European Commission embraces the FAIR principles - Dutch Techcentre for Life Sciences", "Progress towards the European Open Science Cloud - GO FAIR - News item - Government.nl", "Open Consultation on FAIR Data Action Plan - LIBER", "Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud", "Funding research data management and related infrastructures", "CARE Principles of Indigenous Data Governance", "FAIR Principles: Interpretations and Implementation Considerations", https://en.wikipedia.org/w/index.php?title=FAIR_data&oldid=994054954, Creative Commons Attribution-ShareAlike License, This page was last edited on 13 December 2020, at 21:54. 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