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| 1 | FAIR Principles:Interpretations and Implementation Considerations显示文摘The FAIR principles have been widely cited,endorsed and adopted by a broad range of stakeholders since their publication in 2016.By intention,the 15 FAIR guiding principles do not dictate specific technological implementations,but provide guidance for improving Findability,Accessibility,Interoperability and Reusability of digital resources.This has likely contributed to the broad adoption of the FAIR principles,because individual stakeholder communities can implement their own FAIR solutions.However,it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations.Thus,while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways,for true interoperability we need to support convergence in implementation choices that are widely accessible and(re)-usable.We introduce the concept of FAIR implementation considerations to assist accelerated global participation and convergence towards accessible,robust,widespread and consistent FAIR implementations.Any self-identified stakeholder community may either choose to reuse solutions from existing implementations,or when they spot a gap,accept the challenge to create the needed solution,which,ideally,can be used again by other communities in the future.Here,we provide interpretations and implementation considerations(choices and challenges)for each FAIR principle. | Annika Jacobsen Ricardo de Miranda Azevedo Nick Juty Dominique Batista Simon Coles Ronald Cornet Melanie Courtot Merce Crosas Michel Dumontier Chris T.Evelo Carole Goble Giancarlo Guizzardi Karsten Kryger Hansen Ali Hasnain Kristina Hettne Jaap Heringa Rob W.W.Hooft Melanie Imming Keith G.Jeffery Rajaram Kaliyaperumal Martijn GKersloot Christine R.Kirkpatrick Tobias Kuhn Ignasi Labastida Barbara Magagna PeterMcQuilton Natalie Meyers Annalisa Montesanti Mirjam van Reisen Philippe Rocca-Serra Robert Pergl Susanna-Assunta Sansone Luiz Olavo Bonino da Silva Santos Juliane Schneider George Strawn Mark Thompson Andra Waagmeester Tobias Weigel Mark D.Wilkinson Egon L.Willighagen Peter Wittenburg Marco Roos Barend Mons Erik Schultes | 2020 | Data Intelligence2020，2，1： | 26 |
| 2 | BRIEF INTRODUCTION TO SYNERGIZED STANDARD OPERATING PROCEDURES FOR COASTAL MULTI-HAZARDS EARLY WARNING SYSTEM显示文摘The most countries surrounding the Indian Ocean as well as Southeast Asian countries do not have operational experience in handling a combination of tsunami and other coastal hazard early warning systems.The challenge faced by warning providers,media,disaster managers,and coastal communities is in understanding the similarities and differences among different coastal hazards and the characteristics of the early warnings that are issued.There is a strong need to create synergies among different types of coastal hazard early warnings by reviewing the relevant existing standard operating procedures.These synergies can be achieved through identifying specific gaps and needs for making the existing early warning systems fully operational for the use in multi-hazards context.The project of Synergized Standard Operating Procedures for Coastal Multi-Hazards Early Warning System(SSOP) was proposed by Typhoon Committee Secretariat with the objectives of developing the SSOP Manual/Handbook and establishing the cooperation mechanism on coastal multi-hazard early warning among the target countries.The project will mainly focus on the meteorological and hydrological services for affected areas which become more vulnerable to natural disasters after tsunami and other costal disasters.The synergized standard operating procedure should be easier understandable and interpretable for decision makers,forecasters and dwellers. | OLAVO RASQUINHO DEREK LEONG JINPING LIU | 2012 | Tropical Cyclone Research and Review2012，1，4： | 5 |
| 3 | A Generic Workflow for the Data FAIRification Process显示文摘The FAIR guiding principles aim to enhance the Findability,Accessibility,Interoperability and Reusability of digital resources such as data,for both humans and machines.The process of making data FAIR(“FAIRification”)can be described in multiple steps.In this paper,we describe a generic step-by-step FAIRification workflow to be performed in a multidisciplinary team guided by FAIR data stewards.The 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 resources.The 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 data.For 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. | Annika Jacobsen Rajaram Kaliyaperumal Luiz Olavo Bonino da Silva Santos Barend Mons Erik Schultes Marco Roos Mark Thompson | 2020 | Data Intelligence2020，2，1： | 5 |
| 4 | The Need of Industry to Go FAIR显示文摘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 services.As 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)data.Many 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 partnerships.For a global Internet of FAIR Data&Services to thrive,also involving industry,professional tools and services are essential.FAIR metrics and certifications on individuals,data,organizations,and software,must ensure that data producers and consumers have independent quality metrics on their data.In 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”. | 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 | 2020 | Data Intelligence2020，2，1： | 4 |
| 5 | The“A”of FAIR-As Open as Possible,as Closed as Necessary显示文摘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 developed.According 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 subjects.Additional 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 2018.This 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 data.We 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 requirements.Finally,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. | Annalisa Landi Mark Thompson Viviana Giannuzzi Fedele Bonifazi Ignasi Labastida Luiz Olavo Bonino da Silva Santos Marco Roos | 2020 | Data Intelligence2020，2，1： | 4 |
| 6 | ASSESSMENT ON DISASTER RISK REDUCTION OF TROPICAL STORM WA SHI显示文摘In December,2011,the world’s second most deadly disaster of the year,Tropical Storm Washi(known as Sendong in the Philippines)landed along the east coast of Mindanao,Philippines,causing 1,292 deaths,1,049 missing,2,002 injured,and total 695,195 people(110,806 families)affected.This paper introduced briefly the hydro-meteorological characteristics of Washi,and assessed its devastating impacts on society and economy,and the response and recovery taken by the Philippines government during the whole period of Washi.Based on the assessment of impact of disaster,the paper indicated the gaps and needs on aspects of DRR actions and identified the future challenges on typhoon related disaster preparedness and reduction in the Philippines.Finally,the report provided the recommendations within the framework of the activities of Typhoon Committee to improve and enhance the capacity building on typhoon related disaster reduction in the Philippines. | Olavo Rasquinho Jinping Liu Derek Leong | 2013 | Tropical Cyclone Research and Review2013，2，3： | 3 |
| 7 | GO FAIR Brazil:A Challenge for Brazilian Data Science显示文摘The FAIR principles,an acronym for Findable,Accessible,Interoperable and Reusable,are recognised worldwide as key elements for good practice in all data management processes.To 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 networks.To 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 networks.The 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 networks.Today,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 negotiation.This report demonstrates the strong interest and effort from the Brazilian scientific communities in implementing the FAIR principles in their research data management practices. | Luana Sales Patricia Henning Viviane Veiga Maira Murrieta Costa Luis Fernando Sayao Luiz Olavo Bonino da Silva Santos Luis Ferreira Pires | 2020 | Data Intelligence2020，2，1： | 3 |
| 8 | Design Optimization and Weight Reduction of 500 mL CSD PET Bottle through FEM Simulations显示文摘 | Carlos Alberto Silva De Miranda Jairo Jose Drummond Camara Olavo Pena Monken Claudio Gouvea Dos Santos | 2011 | 材料科学与工程(中英文B版)2011，1，7： | 2 |
| 9 | Distributed Analytics on Sensitive Medical Data:The Personal Health Train显示文摘In recent years,as newer technologies have evolved around the healthcare ecosystem,more and more data have been generated.Advanced 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 well-being.However,the sensitive nature of the health data prohibits healthcare organizations from sharing the data.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 data.The main principle of the PHT is that data remain in their original location,and analytical tasks visit data sources and execute the tasks.The PHT provides a distributed,flexible approach to use data in a network of participants,incorporating the FAIR principles.It facilitates the responsible use of sensitive and/or personal data by adopting international principles and regulations.This paper presents the concepts and main components of the PHT and demonstrates how it complies with FAIR principles. | 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 | 2020 | Data Intelligence2020，2，1： | 1 |
| 10 | Potential outcome factors in subacute combined degeneration显示文摘 | Olavo M. Vasconcelos MD Erika H. Poehm MD Robert J. McCarter ScD William W. Campbell MD Zenaide M. N. Quezado MD | 2006 | Journal of General Internal Medicine2006，，10： | 1 |
| 11 | Bactericidal activity of ethanolic extracts of propolis against Staphylococcus aureus isolated from mastitic cows显示文摘 | Henrique Freitas Santana Ana Andréa Teixeira Barbosa Sukarno Olavo Ferreira Hilário Cuquetto Mantovani | 2012 | World Journal of Microbiology and Biotechnology2012，，2： | 1 |
| 12 | Endoscopic Detection of Early Esophageal Squamous Cell Carcinoma in Patients with Achalasia: Narrow-Band Imaging versus Lugol’s Staining显示文摘 | Edson Ide Fred Olavo Arag?o Andrade Carneiro Mariana Souza Varella Fraz?o Dalton Marques Chaves Rubens Ant?nio Aissar Sallum Eduardo Guimar?es Hourneaux de Moura Paulo Sakai Ivan Cecconello Fauze Maluf-Filho Everson L. A. Artifon | 2013 | Journal of Oncology2013，，： | 1 |
| 13 | The three isoforms of nitric oxide synthase distinctively affect mouse nocifensive behavior显示文摘 | Julia Finkel Virginia Guptill Alfia Khaibullina Nicholas Spornick Olavo Vasconcelos David J. Liewehr Seth M. Steinberg Zenaide M.N. Quezado | 2011 | Nitric Oxide2011，，2： | 1 |
| 14 | Primary bone lymphoma in 24 patients treated between 1955 and 1999显示文摘 | de Camargo Olavo Pires MD PhD dos Santos Machado Telma Murias MD Croci Alberto Tesconi MD PhD | 2002 | Clin Orthop2002，397，： | 1 |
| 15 | Physical-mechanical and antimicrobial properties of nanocomposite films with pediocin and ZnO nanoparticles 显示文摘 | Vitor Rejane Andrade Batista Sukamo Olavo Ferreira | 2013 | Carbohydrate Polymers2013，94，1： | 1 |
| 16 | Measurement properties of the pressure biofeedback unit in the evaluation of transversus abdominis muscle activity:a systematic review显示文摘 | PEDRO OLAVO DE PAULA LIMA RODRIGO RIBEIRO DE OLIVEIRA LEONARDO OLIVEIRA PENA COSTA | | 0，，97： | 1 |
| 17 | Medication reconciliation in the hospital what,why,where,when,who and how显示文摘 | Olavo F Kaveh G Shojania | 2012 | Healthcare Quarterly Special Issue2012，，15： | 1 |
| 18 | Making FAIR Easy with FAIR Tools:From Creolization to Convergence显示文摘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 recognized.This 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 metrics.However,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 implementation.Moreover,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”)way.In this paper we will show,however,that there are already many emerging examples of FAIR tools under development.This 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. | Mark Thompson Kees Burger Rajaram Kaliyaperumal Marco Roos Luiz Olavo Bonino da Silva Santos | 2020 | Data Intelligence2020，2，1： | 1 |
| 19 | FAIR Data Point:A FAIR-Oriented Approach for Metadata Publication显示文摘Metadata,data about other digital objects,play an important role in FAIR with a direct relation to all FAIR principles.In 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 principles.We 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. | Luiz Olavo Bonino da Silva Santos Kees Burger Rajaram Kaliyaperumal Mark D.Wilkinson | 2023 | Data Intelligence2023，5，1： | 0 |
| 20 | The FAIR Data Point:Interfaces and Tooling显示文摘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 resources.The 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 Containers.There has been a recent flurry of development activity around the FAIR Data Point that has significantly improved its power and ease-of-use.Here 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. | Oussama Mohammed Benhamed Kees Burger Rajaram Kaliyaperumal Luiz Olavo Bonino da Silva Santos Marek Suchánek Jan Slifka Mark D.Wilkinsoni | 2023 | Data Intelligence2023，5，1： | 0 |
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