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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 | FAIR Science for Social Machines: Let’s Share Metadata Knowlets in the Internet of FAIR Data and Services显示文摘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 anxiety.Some 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 developments.Many of these concerns are associated with mind-machine interaction and the critical role that computers are now playing in our day to day scientific practice.Here we address a number of these concerns and provide some possible solutions.FAIR(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 Science.Here we first define the term FAIR science as opposed to Open Science.In 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 security.Although Open Science is a definition for a way of working rather than explicitly requesting for all data to be available in full Open Access, the connotation of openness of the data involved in Open Science is very strong. In FAIR science, data and the associated services to run all processes in the data stewardship cycle from design of experiment to capture to curation, processing, linking and analytics all have minimally FAIR metadata, which specify the conditions under which the actual underlying research objects are reusable, first for machines and then also for humans. This effectively means that-properly conducted- Open Science is part of FAIR science. However, FAIR science can also be done with partly closed, sensitive and proprietary data. As has been emphasized before, FAIR is not identical to “open”. In FAIR/Open Science, data should be as open as possible and as closed as necessary. Where data are generated using public funding, the default will usually be that for the FAIR data resulting from the study the accessibility will be as high as possible, and that more restrictive access and licensing policies on these data will have to be explicitly justified and described. In all cases, however, even if the reuse is restricted, data and related services should be findable for their major uses, machines, which will make them also much better findable for human users. With a tendency to make good data stewardship the norm, a very significant new market for distributed data analytics and learning is opening and a plethora of tools and reusable data objects are being developed and released. These all need FAIR metadata to be routed to each other and to be effective. | Barend Mons | 2019 | Data Intelligence2019，1，1： | 8 |
| 3 | 实时经支气管超声引导针吸活检在肺癌分期中的应用显示文摘线性经支气管超声引导针吸活检(endobronchial ultrasound-guided transbronchial needle aspiration,EBUS-TBNA)是新引进的技术,它是实时超声下可视淋巴结的针吸活检。尽管有研究显示,其为肺癌纵隔分期的有效方法,但全世界多数机构并未应用该技术。本报道旨在分享我们应用EBUS-TBNA的经验,并对相关文献做一简要概述。我们对有关该技术的已有文献进行综述,并特别介绍了我们应用该技术方面的经验。EBUS-TBNA用以探查肺癌患者的转移性纵隔淋巴结和/或肺门淋巴结是有效且安全的。在其它病理状态下,其亦为有效的诊断方法。 | Ignasi GARCIA-OLIVé José SANZ-SANTOS Felipe ANDREO Eduard MONSó 南娟 丁燕 | 2010 | 中国肺癌杂志2010，，5： | 7 |
| 4 | Statements from the Taormina expert meeting on occult hepatitis B virus infection显示文摘 | Giovanni Raimondo Jean-Pierre Allain Maurizia R. Brunetto Marie-Annick Buendia Ding-Shinn Chen Massimo Colombo Antonio Craxì Francesco Donato Carlo Ferrari Giovanni B. Gaeta Wolfram H. Gerlich Massimo Levrero Stephen Locarnini Thomas Michalak Mario U. Mon | 2008 | Journal of Hepatology2008，，4： | 5 |
| 5 | 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 |
| 6 | 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 |
| 7 | Towards the Tipping Point for FAIR Implementation显示文摘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 reusable.The 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 reuse.Accordingly,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 presented.The investigation also includes an analysis of the domains in the IFDS Implementation Networks(INs).Its uptake has been mainly in the Western hemisphere.The investigation found that implementation of FAIR Guiding Principles has taken firm hold in the domain of bio and natural sciences.To achieve a tipping point for FAIR implementation,it is now time to ensure the inclusion of non-European ascendants and of other scientific domains.Apart 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 boundaries.The 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 IFDS.It is further concluded that policy entrepreneurs and the GO FAIR INs may contribute to making the FAIR Guiding Principles more flexible in including different research epistemologies,especially through its GO CHANGE pillar. | Mirjam van Reisen Mia Stokmans Mariam Basajja Antony Otieno Ong’ayo Christine Kirkpatrick Barend Mons | 2020 | Data Intelligence2020，2，1： | 3 |
| 8 | Actinobacteria-enhanced plant growth, nutrient acquisition, and crop protection:Advances in soil, plant, and microbial multifactorial interactions显示文摘Agricultural areas of land are deteriorating every day owing to population increase, rapid urbanization, and industrialization. To feed today’s huge populations, increased crop production is required from smaller areas, which warrants the continuous application of high doses of inorganic fertilizers to agricultural land. These cause damage to soil health and, therefore, nutrient imbalance conditions in arable soils. Under these conditions, the benefits of microbial inoculants (such as Actinobacteria) as replacements for harmful chemicals and promoting ecofriendly sustainable farming practices have been made clear through recent technological advances. There are multifunctional traits involved in the production of different types of bioactive compounds responsible for plant growth promotion, and the biocontrol of phytopathogens has reduced the use of chemical fertilizers and pesticides. There are some well-known groups of nitrogen-fixing Actinobacteria, such as Frankia, which undergo mutualism with plants and offer enhanced symbiotic trade-offs.In addition to nitrogen fixation, increasing availability of major plant nutrients in soil due to the solubilization of immobilized forms of phosphorus and potassium compounds, production of phytohormones, such as indole-3-acetic acid, indole-3-pyruvic acid, gibberellins, and cytokinins, improving organic matter decomposition by releasing cellulases, xylanase, glucanases, lipases, and proteases, and suppression of soil-borne pathogens by the production of siderophores, ammonia, hydrogen cyanide, and chitinase are important features of Actinobacteria useful for combating biotic and abiotic stresses in plants.The positive influence of Actinobacteria on soil fertility and plant health has motivated us to compile this review of important findings associated with sustaining plant productivity in the long run. | Debasis MITRA Rittick MONDAL Bahman KHOSHRU Ansuman SENAPATI T.K.RADHA Bhaswatimayee MAHAKUR Navendra UNIYAL Ei Mon MYO Hanane BOUTAJ Beatriz Elena GUERRA SIERRA Periyasamy PANNEERSELVAM Arakalagud Nanjundaiah GANESHAMURTHY Snežana ANÐELKOVIĆ Tanja VASIĆ Anju RANI Subhadeep DUTTA Pradeep K.DAS MOHAPATRA | 2022 | Pedosphere2022，32，1： | 3 |
| 9 | The FAIR Principles:First Generation Implementation Choices and Challenges显示文摘“FAIR enough”?...A question asked on a daily basis in the rapidly evolving field of open science and the underpinning data stewardship profession.After 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 services.No-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 reusable.Being 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. | Barend Mons Erik Schultes Fenghong Liu Annika Jacobsen | 2020 | Data Intelligence2020，2，1： | 2 |
| 10 | Coexpression of Escherichia coli RNase III in silkworm cells improves the efficiency of RNA interference induced by long hairpin dsRNAs显示文摘从 chromosomal DNA 抄录的长发卡 dsRNA 能在 Bombyx mori 房间导致 RNA 干扰,尽管它的基因 silencing 效率比外长地介绍的双 stranded RNA (dsRNAs ) 的低。解决这个问题,我们监视了抄录发卡 dsRNA 的原子细胞质的 translocation 并且分析了处理效率进成熟小介入 RNA (siRNA ) 。北污点分析表明抄录发卡 dsRNAs 被拼接并且搬运进细胞质,但是有效地没被用色子赌博进 siRNAs。有趣地,有从染色体综合的红外 transgene 的发卡 dsRNAs 的 RNAi 被 Escherichia coli RNase III 的 coexpression 刺激,尽管这外长的酶似乎引起细胞的 mRNA 的 nonspecific 劈开。 | Jae Man Lee Yoshito Kojin Tsuneyuki Tatsuke Hiroaki Mon Yoshitaka Miyagawa Takahiro Kusakabe | 2013 | Insect Science2013，20，1： | 2 |
| 11 | Folic acid supplementation, MTHFR and MTRR polymorphisms, and the risk of childhood leukemia: the ESCALE study (SFCE)显示文摘 | Alicia Amigou Jérémie Rudant Laurent Orsi Stéphanie Goujon-Bellec Guy Leverger André Baruchel Yves Bertrand Brigitte Nelken Geneviève Plat Gérard Michel Stéphanie Haouy Pascal Chastagner Stéphane Ducassou Xavier Rialland Denis Hémon Jacqueline Clavel | 2012 | Cancer Causes & Control2012，，8： | 2 |
| 12 | 一种考虑损伤的沥青路面本构关系在冲击载荷作用下的应用显示文摘在经典Burgers模型的基础上,基于所有元器件均发生同一程度损伤的假设,引入了与应变和材料参数相关的损伤变量D,建立了可以描述沥青混合料损伤的Burgers模型,用于模拟沥青路面的损伤行为。修正的损伤Burgers模型经过与参考文献中的试验数据对比得到了验证。在此基础上,通过C++软件编程,完成了修正的损伤Burgers模型在FLAC3D数值计算程序中的嵌套开发和应用,计算了某种路面在冲击载荷作用下的弯沉变形和应力分布。结果表明:修正的损伤Burgers模型能够描述冲击载荷作用下沥青路面从加载变形到失稳破坏的整体阶段,计算得到的弯沉盆以及路面和基层的破坏形式与现场试验结果吻合良好,具有较高的精度;通过对计算得到的应力和应变进行后处理,可以获得损伤变量D与应变以及时间的关系曲线,对于评价沥青路面性能具有很好的指导作用;通过采用修正的损伤Burgers模型进行数值计算,在结合现场试验数据的基础上,可以得知低等级公路用于战备使用时,应充分考虑使用前的冲击载荷降压措施,以及使用后的快速修补和维护措施,在可选的情况下,应尽可能选择高等级公路,避免低等级公路段,如三级及以下的公路。 | 冯锦艳 Thant Yee Mon SAN | 2020 | 公路交通科技2020，37，4： | 2 |
| 13 | Thin water film around a cable subject to wind显示文摘 | C. Lemaitre P. Hémon E. de Langre | 2007 | Journal of Wind Engineering & Industrial Aerodynamics2007，，9： | 2 |
| 14 | Isolation ofvolatile components from a model system显示文摘 | Schultz T H Flath R A Richard Mon T | 1977 | J Agric FoodChem1977，25，3： | 1 |
| 15 | Monitoring of cryptosporidium and giardia river contamination in paris area 显示文摘 | MONS C DUMETRE A GOSSELIN S | 2009 | Wat Res2009，，43： | 1 |
| 16 | Surgical treatment of iatrogenic lesions of the proximal common bile duct 显示文摘 | Gazzaniga GM Filauro M Mon L | 2001 | World J Surg2001，25，10： | 1 |
| 17 | Screening fort twints ransfusion syndrome at 11~ 14 weeks of pregnancy:the key role of ductus venosus blood flow assessment显示文摘 | Matias A Mon tenegro N Loureiro T | | 0，，10： | 1 |
| 18 | Standard Roux-en-Y gastroieiunostomv vs. “Uncut” Roux-en-Y gastrojejunostoki: A matched cohort study显示文摘 | Rodrigo A. Mon M.D. Joseph J. Cullen M.D | 2000 | Journal of Gastrointestinal Surgery2000，，3： | 1 |
| 19 | Guillain-Barre Syndromeoutbreak associated with Zika virus infection in French Polynesia: acase-control study 显示文摘 | Cao-Lormeau VM Blake A Mons S | 2016 | Lancet2016，387，10027： | 1 |
| 20 | Standard Roux-en-Y gastrojejunostomy vs'uncut'Roux-en-Y gastrojejunostomy:a matched cohort study显示文摘 | Mon RA Cullen JJ | 2000 | J Gastrointest Surg2000，4，3： | 1 |
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