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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

FAIR Science for Social Machines: Let’s Share Metadata Knowlets in the Internet of FAIR Data and Services

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Data Intelligence 2019年第1期1卷 22-42页

作者： barend.mons Leiden University Medical Centre The Netherlands Poortgebouw N-01Rijnsburgerweg 102333 AA LeidenThe Netherlands

In a world awash with fragmented data and tools,the notion of Open Science has been gaining a lot of momentum,but simultaneously,it caused a great deal of *** of the anxiety may be related to crumbling kingdoms,but there are also very legitimate concerns,especially about the relative role of machines and algorithms as compared to humans and the combination of both(i.e.,social machines).There are also grave concerns about the connotations of the term“open”,but also regarding the unwanted side effects as well as the scalability of the approaches advocated by early adopters of new methodological *** of these concerns are associated with mind-machine interaction and the critical role that computers are now playing in our day to day scientific *** we address a number of these concerns and provide some possible ***(machine-actionable)data and services are obviously at the core of Open Science(or rather FAIR science).The scalable and transparent routing of data,tools and compute(to run the tools on)is a key central feature of the envisioned Internet of FAIR Data and Services(IFDS).Both the European Commission in its Declaration on the European Open Science Cloud,the G7,and the USA data commons have identified the need to ensure a solid and sustainable infrastructure for Open *** we first define the term FAIR science as opposed to Open *** FAIR science,data and the associated tools are all Findable,Accessible under well defined conditions,Interoperable and Reusable,but not necessarily“open”;without restrictions and certainly not always“gratis”.The ambiguous term“open”has already caused considerable confusion and also opt-out reactions from researchers and other data-intensive professionals who cannot make their data open for very good reasons,such as patient privacy or national *** Open Science is a definition for a way of working rather than explicitly requesting for all data to be available in full

关键词： FAIR science Semantic publication Metadata Knowlets FAIR principles

A Journal for Human and Machine

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Data Intelligence 2019年第1期1卷 1-5页

作者： James Hendler Ying Ding barend.mons Rensselaer Institute for Data Exploration and Applications Rensselaer Polytechnic InstituteTroyNY12180USA School of Informatics Computingand EngineeringIndiana UniversityBloomingtonIN 47408USA Leiden University Medical Centre The NetherlandsPoortgebouw N-01Rijnsburgerweg 102333 AA LeidenThe Netherlands

It is with great pride to bring you this new journal of Data *** journal has at least two major purposes that we hope ***,it will embrace the traditional role of a journal in helping to facilitate the communication of research and best practices in scientific data sharing,especially across disciplines,an area that is continually growing in importance for the modern practice of ***,we will be experimenting with new methods of enhancing the sharing of this communication,and examples of the field,by utilizing the increasing power of intelligent computing systems to further facilitate the growth of the *** journal’s title,combining“data,”the field we will support,and“intelligence,”a means to that end,is meant to connote this growing interaction.

关键词： interaction. journal utilizing

The FAIR Principles:First Generation Implementation Choices and Challenges

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Data Intelligence 2020年第1期2卷 1-9,293页

作者： barend.mons Erik Schultes Fenghong Liu Annika Jacobsen Leiden University Medical Center Leiden2333 ZAThe Netherlands GO FAIR International Support&Coordination Office(GFISCO) LeidenThe Netherlands National Science Library Chinese Academy of SciencesBeijing 100093China School of Economics and Management University of Chinese Academy of SciencesBeijing 100084China School of Information Management Nanjing UniversityNanjing 210023China

“FAIR enough”?...A question asked on a daily basis in the rapidly evolving field of open science and the underpinning data stewardship *** the publication of the FAIR principles in 2016,they have sparked theoretical debates,but some communities have already begun to implement FAIR-guided data and ***-one really argues against the idea that data,as well as the accompanying workflows and services should be findable,accessible under well-defined conditions,interoperable without data munging,and thus optimally *** FAIR is not a goal in itself;FAIR Data and Services are needed to enable data intensive research and innovation and(thus)have to be“AI-ready”(=future proof for machines to optimally assist us).However,the fact that science and innovation becomes increasingly“machine-assisted”and hence the central role of machines,is still overlooked in some cases when people claim to implement FAIR.

关键词： hence enable enough

Towards the Tipping Point for FAIR Implementation

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Data Intelligence 2020年第1期2卷 264-275页

作者： Mirjam van Reisen Mia Stokmans Mariam Basajja Antony Otieno Ong’ayo Christine Kirkpatrick barend.mons Liacs Institute of Advanced Computer Science Leiden UniversityLeidenThe Netherlands Tilburg School of Humanities and Digital Sciences Tilburg University901535000 LE TilburgThe Netherlands International Institute of Social Studies Erasmus University297762502 LT The HagueThe Netherlands San Diego Supercomputer Center University of California San DiegoSan Diego CA 92093USA Leiden University Medical Center Leiden2333 ZAThe Netherlands

This article explores the global implementation of the FAIR Guiding Principles for scientific management and data stewardship,which provide that data should be findable,accessible,interoperable and *** implementation of these principles is designed to lead to the stewardship of data as FAIR digital objects and the establishment of the Internet of FAIR Data and Services(IFDS).If implementation reaches a tipping point,IFDS has the potential to revolutionize how data is managed by making machine and human readable data discoverable for ***,this article examines the expansion of the implementation of FAIR Guiding Principles,especially how and in which geographies(locations)and areas(topic domains)implementation is taking place.A literature review of academic articles published between 2016 and 2019 on the use of FAIR Guiding Principles is *** investigation also includes an analysis of the domains in the IFDS Implementation Networks(INs).Its uptake has been mainly in the Western *** investigation found that implementation of FAIR Guiding Principles has taken firm hold in the domain of bio and natural *** achieve a tipping point for FAIR implementation,it is now time to ensure the inclusion of non-European ascendants and of other scientific *** from equal opportunity and genuine global partnership issues,a permanent European bias poses challenges with regard to the representativeness and validity of data and could limit the potential of IFDS to reach across continental *** article concludes that,despite efforts to be inclusive,acceptance of the FAIR Guiding Principles and IFDS in different scientific communities is limited and there is a need to act now to prevent dampening of the momentum in the development and implementation of the *** is further concluded that policy entrepreneurs and the GO FAIR INs may contribute to making the FAIR Guiding Principles more flexible in including different rese

关键词： FAIR Data Health Digital Health mHealth data-driven science FAIR Implementation Networks GO-FAIR

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

Leveraging Graph Cut’s Energy Function for Context Aware Facial Recognition in Indoor Environments

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Computer Systems Science & Engineering 2021年第8期38卷 229-238页

作者： Kazeem Oyebode Shengzhi Du barend Jacobus van Wyk Pan-Atlantic University LagosNigeria Department of Electrical Engineering Tshwane University of TechnologyPretoriaSouth Africa Faculty of Engineering the Built Environment and Technology Nelson Mandela UniversitySouth Africa

Context-aware facial recognition regards the recognition of faces in association with their respective *** concept is useful for the domestic robot which interacts with humans when performing specific functions in indoor *** learning models have been relevant in solving facial and place recognition challenges;however,they require the procurement of training images for optimal ***-trained models have also been offered to reduce training time ***,for classification tasks,custom data must be acquired to ensure that learning models are developed from other pre-trained *** paper proposes a place recognition model that is inspired by the graph cut energy function,which is specifically designed for image *** objects in the considered environment are identified and thereafter they are passed over to a graph cut inspired model for indoor environment ***,faces in the considered environment are extracted and ***,the developed model can recognise a face together with its *** strength of the proposed model lies in its ability to classify indoor environments without the usual training process(es).This approach differs from what is obtained in traditional deep learning *** classification capability of the developed model was compared to state-of-theart models and exhibited promising outcomes.

关键词： Place recognition face recognition deep learning graph cut

An evaluation of mass,number concentration,chemical composition and types of particles in a cafeteria before and after the passage of an antismoking law

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Particuology 2013年第5期11卷 527-532页

作者： Jorge Pey barend L.van Drooge Anna Ripollb Teresa Moreno Joan O.Grimalt Xavier Querol Andres Alastuey Department of Epidemiology Lazio Regionvia S.Costanza5300198 RomeItaly Institute of Environmental Assessment and Water Research.ID/EA-CSIC C/Jordi Girona.18-2608034 BarcelonaSpain

This study assessed air quality indicators before and after enactment of the Spanish anti-smoking law. Mass and number concentrations and the chemical composition of particles were evaluated. Microscopy analyses were also conducted. Real time concentrations of PMlo, PM2.s, PM1 and ultrafine particles were measured under ventilated and non-ventilated conditions and PMlo samples were collected for detailed inorganic and organic chemical characterization. Before enactment of the law in 2010, tobacco smoke produced significant indoor ambient particulate matter pollution, with elevated particulate matter mass concentrations （PM10 and PM1 concentrations of 122-220 and 48-85 Dg/m3, respectively） and ultrafine particle numbers （75,000 and 48,000 cm ~ under ventilated and non-ventilated conditions, respectively）. Typical tobacco smoke tracers including iso- and anteiso-alkanes and elements including La and Ce from the ignition of lighters were abundant. Additionally, several toxic substances derived from tobacco smoke, including Cd （3.1 ng/m3） and benzo[a]pyrene （1.0 ng/m3） were present at concentrations approximately 10 times greater than those measured after enactment of the anti-smoking law. The anti-smoking law sig- nificantly reduced exposure to potentially toxic compounds by approximately 90%. This law is expected to have a positive health impact, particularly for people who spend considerable time in affected envi- ronments, such as employees.

关键词： Indoor airParticulate matterUltrafine particlesNucleationCoagulation-condensationEnvironmental tobacco smoke

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“后真相”世界中的公共关系:价值链方法

现代传播（中国传媒大学学报） 2017年第7期39卷 43-49页

作者： barend Venter 北京师范大学-香港浸会大学联合国际学院

公共关系可否在"后真相"时代拯救企业的声誉,甚至在中国亦可?这一问题是基于重新审视南非对价值链中的公共关系调整所做的研究项目而提出的,该研究发现这样的调整将有利于企业组织。本文将通过在中国进行同类型研究作出论证。

关键词：公共关系后真相价值链