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Building Expertise on FAIR Through Evolving Bring Your Own data(BYOD) Workshops: Describing the data, Software, and Management-focused Approaches and Their Evolution

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data Intelligence 2024年第2期6卷 429-456页

作者： César H.Bernabé Lieze Thielemans Rajaram Kaliyaperumal Claudio Carta Shuxin Zhang Celia W.G.van Gelder Nirupama Benis luiz olavo bonino da silva santos Ronald Cornet Bruna dos santos Vieira Nawel Lalout Ines Henriques Alberto Camara Ballesteros Kees Burger Martijn G.Kersloot Friederike Ehrhart Esther van Enckevort Chris T.Evelo Alasdair J.G.Gray Marc Hanauer Kristina Hettne Joep de Ligt Arnaldo Pereira Nuria Queralt-Rosinach Erik Schultes Domenica Taruscio Andra Waagmeester Mark D.Wilkinson Egon L.Willighagen Mascha Jansen Barend Mons Marco Roos Annika Jacobsen Biosemantics Group Department of Human GeneticsLeiden University Medical CentreLeidenThe Netherlands NIHR Academic Fellow in General Practice University College London and The Royal Free NHS Foundation Trust National Centre for Rare Diseases Istituto Superiore di SanitaRomeItaly Department of Medical Informatics Amsterdam UMC location University of AmsterdamMeibergdreef 9AmsterdamThe Netherlands Amsterdam Public Health Methodology&Digital HealthAmsterdamThe Netherlands Health-Rl UtrechtThe Netherlands Semantics Services and Cybersecurity groupUniversity of TwenteEnschedeThe Netherlands Department of Medical Imaging Radboud Institute for Health SciencesRadboud University Medical CenterNijmegenThe Netherlands Department of Medical BioSciences Radboud University Medical CenterNijmegenThe Netherlands The Duchenne Parent Project VeneendaalThe Netherlands Departamento de Biotecnologia-Biologia Vegetal Escuela Tecnica Superior de Ingenieria AgronomicaAlimentaria y de BiosistemasCentro de Biotecnologia y Genomica de PlantasUniversidad Politecnica de Madrid(UPM)-Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria-CSIC(INIA-CSIC).Campus MontegancedoPozuelo de Alarcon(Madrid)Spain Castor AmsterdamThe Netherlands Department of Bioinformatics-BiGCaT Maastricht UniversityMaastrichtThe Netherlands University Medical Center Groningen University of GroningenGroningenThe Netherlands Maastricht Centre for Systems Biology(MaCSBio) Maastricht UniversityMaastrichtThe Netherlands Department of Computer Science Heriot-Watt UniversityEdinburghUK INSERM US14-OrphanetPlateforme Maladies RaresParisFrance Centre for Digital Scholarship Leiden University LibrariesThe Netherlands Center for Molecular Medicine Cancer Genomics NetherlandsDepartment of GeneticsUniversity Medical Center UtrechtUniversity UtrechtThe Netherlands University of Aveiro DETI/IEETAAveiroPortugal GO FAIR Foundation LeidenThe Netherlands The Leiden Academic Center for Drug Research LeidenThe Netherlands Micel

Since 2014,"Bring Your Own data"workshops(BYODs)have been organised to inform people about the process and benefits of making resources Findable,Accessible,Interoperable,and Reusable(FAIR,and the FAIRification process).The BYOD workshops'content and format differ depending on their goal,context,and the background and needs of ***-focused BYODs educate domain experts on how to make their data FAIR to find new answers to research ***-focused BYODs promote the benefits of making data FAIR and instruct project managers and policy-makers on the characteristics of FAIRification ***-focused BYODs gather software developers and experts on FAIR to implement or improve software resources that are used to support ***,these BYODs intend to foster collaboration between different types of stakeholders involved in data management,curation,and reuse(*** experts,trainers,developers,data owners,data analysts,FAIR experts).The BYODs also serve as an opportunity to learn what kind of support for FAIRification is needed from different communities and to develop teaching materials based on practical examples and *** this paper,we detail the three different structures of the BYODs and describe examples of early BYODs related to plant breeding data,and rare disease registries and biobanks,which have shaped the structure of the *** discuss the latest insights into making BYODs more productive by leveraging our almost ten years of training experience in these workshops,including successes and encountered ***,we examine how the participants'feedback has motivated the research on FAIR,including the development of workflows and software.

关键词： FAIR FAIRification FAIR expertise Bring Your Own data Workshop BYOD

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Making FAIR Easy with FAIR Tools:From Creolization to Convergence

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data Intelligence 2020年第1期2卷 87-95,305页

作者： Mark Thompson Kees Burger Rajaram Kaliyaperumal Marco Roos luiz olavo bonino da silva santos Leiden University Medical Center Leiden2333 ZAThe Netherlands GO FAIR international Support&Coordination Office(GFISCO) LeidenThe Netherlands

Since their publication in 2016 we have seen a rapid adoption of the FAIR principles in many scientific disciplines where the inherent value of research data and,therefore,the importance of good data management and data stewardship,is *** has led to many communities asking“What is FAIR?”and“How FAIR are we currently?”,questions which were addressed respectively by a publication revisiting the principles and the emergence of FAIR ***,early adopters of the FAIR principles have already run into the next question:“How can we become(more)FAIR?”This question is more difficult to answer,as the principles do not prescribe any specific standard or ***,there does not yet exist a mature ecosystem of tools,platforms and standards to support human and machine agents to manage,produce,publish and consume FAIR data in a user-friendly and efficient(i.e.,“easy”)*** this paper we will show,however,that there are already many emerging examples of FAIR tools under *** paper puts forward the position that we are likely already in a creolization phase where FAIR tools and technologies are merging and combining,before converging in a subsequent phase to solutions that make FAIR feasible in daily practice.

关键词： FAIR data FAIR in practice FAIR tools FAIR application support creolization and convergence

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FAIR data Point:A FAIR-Oriented Approach for Metadata Publication

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data Intelligence 2023年第1期5卷 163-183页

作者： luiz olavo bonino da silva santos Kees Burger Rajaram Kaliyaperumal Mark D.Wilkinson Services and Cybersecurity group Faculty of Electrical EngineeringMathematics and Computer ScienceUniversity of Twente-Enschede7513GBthe Netherlands Biosemantics group Department of Human GeneticsLeiden University Medical Center-LeidenNL 2333 ZCthe Netherlands Escuela Técnica Superior de Ingenieria Agronomica Alimentaria y de BiosistemasCentro de Biotecnologia y Genomica de Plantas UPM-INIAUniversidad Politecnica de Madrid(UPM)-Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria(INIA)MadridES 28223Spain

Metadata,data about other digital objects,play an important role in FAIR with a direct relation to all FAIR *** this paper we present and discuss the FAIR data Point(FDP),a software architecture aiming to define a common approach to publish semantically-rich and machine-actionable metadata according to the FAIR *** present the core components and features of the FDP,its approach to metadata provision,the criteria to evaluate whether an application adheres to the FDP specifications and the service to register,index and allow users to search for metadata content of available FDPs.

关键词： FAIR FAIR data point FAIR principles Metadata Interoperability Linked data Semantic interoperability

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daMS:A Distributed Analytics Metadata Schema

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data Intelligence 2021年第4期3卷 528-547页

作者： Sascha Welten Laurenz Neumann Yeliz Ucer Yediel luiz olavo bonino da silva santos Stefan Decker Oya Beyan Chair Informatik 5 RWTH Aachen University52056 AachenGermany Fraunhofer Institute for Applied Information Techniques(FIT) 53757 Sankt AugustinGermany Faculty of Electrical Engineering Mathematics and Computer ScienceUniversity of Twente7500AE EnschedeThe Netherlands Department of Human Genetics Leiden University Medical CentreLeiden 2333 ZAThe Netherlands Institute of Medical Information Faculty of Medicine&University Hospital CologneUniversity of Cologne50674 CologneGermany

In recent years,implementations enabling Distributed Analytics(da)have gained considerable attention due to their ability to perform complex analysis tasks on decentralised data by bringing the analysis to the *** concepts propose privacy-enhancing alternatives to data centralisation approaches,which have restricted applicability in case of sensitive data due to ethical,legal or social ***,the immanent problem of da-enabling architectures is the black-box-alike behaviour of the highly distributed components originating from the lack of semantically enriched descriptions,particularly the absence of basic metadata for data sets or analysis *** approach the mentioned problems,we propose a metadata schema for da infrastructures,which provides a vocabulary to enrich the involved entities with descriptive *** initially perform a requirement analysis with domain experts to reveal necessary metadata items,which represents the foundation of our ***,we transform the obtained domain expert knowledge into user stories and derive the most significant semantic *** the final step,we enable machine-readability via RDF(S)and SHACL *** deploy our schema in a proof-of-concept monitoring dashboard to validate its contribution to the transparency of da ***,we evaluate the schema’s compliance with the FAIR *** evaluation shows that the schema succeeds in increasing transparency while being compliant with most of the FAIR *** a common metadata model is critical for enhancing the compatibility between multiple da infrastructures,our work lowers data access and analysis *** represents an initial and infrastructure-independent foundation for the FAIRification of da and the underlying scientific data management.

关键词： Distributed analytics Federated analytics Personal Health Train Metadata schema RDF(S) SHACL FAIR

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A Generic Workflow for the data FAIRification Process

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data Intelligence 2020年第1期2卷 56-65页

作者： Annika Jacobsen Rajaram Kaliyaperumal luiz olavo bonino da silva santos Barend Mons Erik Schultes Marco Roos Mark Thompson Leiden University Medical Center Leiden2333 ZAThe Netherlands GO FAIR International Support&Coordination Office(GFISCO) LeidenThe Netherlands

The FAIR guiding principles aim to enhance the Findability,Accessibility,Interoperability and Reusability of digital resources such as data,for both humans and *** process of making data FAIR(“FAIRification”)can be described in multiple *** this paper,we describe a generic step-by-step FAIRification workflow to be performed in a multidisciplinary team guided by FAIR data *** FAIRification workflow should be applicable to any type of data and has been developed and used for“Bring Your Own data”(BYOD)workshops,as well as for the FAIRification of e.g.,rare diseases *** steps are:1)identify the FAIRification objective,2)analyze data,3)analyze metadata,4)define semantic model for data(4a)and metadata(4b),5)make data(5a)and metadata(5b)linkable,6)host FAIR data,and 7)assess FAIR *** each step we describe how the data are processed,what expertise is required,which procedures and tools can be used,and which FAIR principles they relate to.

关键词： FAIR data FAIRification workflow FAIR data stewardship Hands-on FAIRification FAIR dissemination

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The“A”of FAIR-As Open as Possible,as Closed as Necessary

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data Intelligence 2020年第1期2卷 47-55,303,304页

作者： Annalisa Landi Mark Thompson Viviana Giannuzzi Fedele Bonifazi Ignasi Labastida luiz olavo bonino da silva santos Marco Roos Fondazione per la Ricerca Farmacologica Gianni Benzi Onlus 30-70010 Valenzano(BA)Italy Leiden University Medical Center Leiden2333 ZAThe Netherlands Learning and Research Resources Centre(CRAI) Universitat de BarcelonaCatalunya 08007Spain GO FAIR International Support&Coordination Office(GFISCO) LeidenThe Netherlands

In order to provide responsible access to health data by reconciling benefits of data sharing with privacy rights and ethical and regulatory requirements,Findable,Accessible,Interoperable and Reusable(FAIR)metadata should be *** to the H2020 Program Guidelines on FAIR data,data should be"as open as possible and as closed as necessary","open"in order to foster the reusability and to accelerate research,but at the same time they should be"closed"to safeguard the privacy of the *** provisions on the protection of natural persons with regard to the processing of personal data have been endorsed by the European General data Protection Regulation(GDPR),Reg(EU)2016/679,that came into force in May *** work aims to solve accessibility problems related to the protection of personal data in the digital era and to achieve a responsible access to and responsible use of health *** strongly suggest associating each data set with FAIR metadata describing both the type of data collected and the accessibility conditions by considering data protection obligations and ethical and regulatory ***,an existing FAIR infrastructure component has been used as an example to explain how FAIR metadata could facilitate data sharing while ensuring protection of individuals.

关键词： Accessibility of health data FAIR metadata GDPR data sharing ELSI

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GO FAIR Brazil:A Challenge for Brazilian data Science

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data Intelligence 2020年第1期2卷 238-245,316,317页

作者： Luana Sales Patricia Henning Viviane Veiga Maira Murrieta Costa Luis Fernando Sayao luiz olavo bonino da silva santos Luis Ferreira Pires Instituto Brasileiro em Informacao em Ciencia e Tecnologia Rio de Janeiro-RJ22290-160Brazil Universidade Federal do Estado do Rio de Janeiro Rio de Janeiro-RJ22290-240Brazil Fundacao Oswaldo Cruz Rio de Janeiro-RJ21040-900Brazil Ministerio da Ciencia TecnologiaInovacoes e ComunicacoesEsplanada dos MinisteriosBloco R-BrasiliaDFCEP 70067-900Brazil Comissao Nacional de Energia Nuclear Rua Gal.Severianon 90 Bairro:BotafogoCEP 22290-901-Rio de JaneiroBrazil GO FAIR International Support&Coordination Office(GFISCO) Leiden 2333 AAThe Netherlands University of Twente Enschede 7522 NHThe Netherlands

The FAIR principles,an acronym for Findable,Accessible,Interoperable and Reusable,are recognised worldwide as key elements for good practice in all data management *** understand how the Brazilian scientific community is adhering to these principles,this article reports Brazilian adherence to the GO FAIR initiative through the creation of the GO FAIR Brazil Office and the manner in which they create their implementation *** contextualise this understanding,we provide a brief presentation of open data policies in Brazilian research and government,and finally,we describe a model that has been adopted for the GO FAIR Brazil implementation *** Brazilian Institute of Information in Science and Technology is responsible for the GO FAIR Brazil Office,which operates in all fields of knowledge and supports thematic implementation ***,GO FAIR Brazil-Health is the first active implementation network in operation,which works in all health domains,serving as a model for other fields like agriculture,nuclear energy,and digital humanities,which are in the process of adherence *** report demonstrates the strong interest and effort from the Brazilian scientific communities in implementing the FAIR principles in their research data management practices.

关键词： FAIR principles GO FAIR GO FAIR Brazil Open Science Research data

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The FAIR data Point:Interfaces and Tooling

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data Intelligence 2023年第1期5卷 184-201页

作者： Oussama Mohammed Benhamed Kees Burger Rajaram Kaliyaperumal luiz olavo bonino da silva santos Marek Suchánek Jan Slifka Mark D.Wilkinsoni Departamento de Biotecnologia-Biologia Vegetal Escuela Tecnica Superior de Ingenieria AgronomicaAlimentaria y de BiosistemasCentro de Biotecnologia y Genomica de Plantas UPM-INIAUniversidad Politecnica de Madrid(UPM)-Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria(INIA)MadridES 28223Spain Leiden University Medical Center Leiden2333 ZCthe Netherlands University of Twente Enschede7513 GBthe Netherlands Czech Technical University in Prague PragueCZ 15000Czech Republic

While the FAIR Principles do not specify a technical solution for'FAIRness',it was clear from the outset of the FAIR initiative that it would be useful to have commodity software and tooling that would simplify the creation of FAIR-compliant *** FAIR data Point is a metadata repository that follows the DCAT(2)schema,and utilizes the Linked data Platform to manage the hierarchical metadata layers as LDP *** has been a recent flurry of development activity around the FAIR data Point that has significantly improved its power and *** we describe five specific tools—an installer,a loader,two Webbased interfaces,and an indexer-aimed at maximizing the uptake and utility of the FAIR data Point.

关键词： FAIR data Linked data Semantic Web Metadata User interfaces Tooling Semantic query

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Distributed Analytics on Sensitive Medical data:The Personal Health Train

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data Intelligence 2020年第1期2卷 96-107,305,306,307页

作者： Oya Beyan Ananya Choudhury Johan van Soest Oliver Kohlbacher Lukas Zimmermann Holger Stenzhorn Md.Rezaul Karim Michel Dumontier Stefan Decker luiz olavo bonino da silva santos Andre Dekker Fraunhofer Institute for Applied Information Technology(FIT) 53754 Sankt AugustinGermany RWTH Aachen University 52056 AachenGermany Department of Radiation Oncology(MAASTRO) GROW School for Oncology and Developmental BiologyMaastricht University Medical Center6200 MD MaastrichtThe Netherlands Institute of data Science Maastricht UniversityUniversiteitssingel 60Maastricht 6229 ERThe Netherlands Department of Computer Science University of TübingenTubingenBaden-Württemberg 72076Germany Quantitative Biology Center University of TübingenTubingenBaden-Württemberg 72076Germany Institute for Translational Bioinformatics University of TubingenTubingenBaden-Württemberg 72076Germany Center for Bioinformatics University of TübingenGermany GO FAIR International Support&Coordination Office(GFISCO) LeidenThe Netherlands

In recent years,as newer technologies have evolved around the healthcare ecosystem,more and more data have been *** analytics could power the data collected from numerous sources,both from healthcare institutions,or generated by individuals themselves via apps and devices,and lead to innovations in treatment and diagnosis of diseases;improve the care given to the patient;and empower citizens to participate in the decision-making process regarding their own health and ***,the sensitive nature of the health data prohibits healthcare organizations from sharing the *** Personal Health Train(PHT)is a novel approach,aiming to establish a distributed data analytics infrastructure enabling the(re)use of distributed healthcare data,while data owners stay in control of their own *** main principle of the PHT is that data remain in their original location,and analytical tasks visit data sources and execute the *** PHT provides a distributed,flexible approach to use data in a network of participants,incorporating the FAIR *** facilitates the responsible use of sensitive and/or personal data by adopting international principles and *** paper presents the concepts and main components of the PHT and demonstrates how it complies with FAIR principles.

关键词： Distributed analytics data reuse FAIR Health data Ethics and privacy

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The Need of Industry to Go FAIR

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data Intelligence 2020年第1期2卷 276-284,320,321,322页

作者： Herman van Vlijmen Albert Mons Arne Waalkens Wouter Franke Arie Baak Gerbrand Ruiter Christine Kirkpatrick luiz olavo bonino da silva santos Bert Meerman Renger Jellema Derk Arts Martijn Kersloot Sebastiaan Knijnenburg Scott Lusher Rudi Verbeeck Jean-Marc Neefs Janssen Pharmaceuticals Antwerpseweg 152340 BeerseBelgium Phortos Consultants The Netherlands Accenture Gustav Mahlerplein 901082 MA AmsterdamThe Netherlands Zorg Instituut Nederland Willem Dudokhof 11112 ZA DiemenThe Netherlands Euretos Yalelaan 13584 CL UtrechtThe Netherlands Mobiquity Tommaso Albinonistraat 91083 HM AmsterdamThe Netherlands UCSD and National data Service 10100 Hopkins DrLa JollaCA 92093USA GO FAIR International Support&Coordination Office(GFISCO) LeidenThe Netherlands GO FAIR Foundation Rijnsburgerweg 102333 AA LeidenThe Netherlands DSM Biotechnology Center Alexander Fleminglaan 12613 AX DelftThe Netherlands Castor Paasheuvelweg 25Vleugel 5D1105 BP AmsterdamThe Netherlands

The industry sector is a very large producer and consumer of data,and many companies traditionally focused on production or manufacturing are now relying on the analysis of large amounts of data to develop new products and *** many of the data sources needed are distributed and outside the company,FAIR data will have a major impact,both by reducing the existing internal data silos and by enabling the efficient integration with external(public and commercial)*** companies are still in the early phases of internal data”FAIRification”,providing opportunities for SMEs and academics to apply and develop their expertise on FAIR data in collaborations and public-private *** a global Internet of FAIR data&Services to thrive,also involving industry,professional tools and services are *** metrics and certifications on individuals,data,organizations,and software,must ensure that data producers and consumers have independent quality metrics on their *** this opinion article we reflect on some industry specific challenges of FAIR implementation to be dealt with when choices are made regarding”Industry GOing FAIR”.

关键词： FAIR application

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