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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: David, Romain; Bouveret, Laurent; Coché, Lorraine; Corrêa, Pedro Pizzigatti; +21 Authors

    We are now facing profound changes (biodiversity, climate, pandemic, etc.). Human impacts and their mitigation will depend on our ability to mobilize research at the global level. The sustainable development of the society will largely depend on the sustainable development of global science and scientific research tools, outputs, and research ecosystems. This globalization of research requires interoperating our observation and experimentation systems in order to better understand these changes, to better simulate their effects. The Covid-19 pandemic is now raging around the world. The reproducibility of research and results across regions in different contexts should accelerate human responses. Data sharing and the development of Synthesis Research with data aggregation at large scale is critical to enable such processes. The use of common knowledge, vocabularies, standards and procedures at a large scale is necessary. The objective of this poster is to report on the challenges met while building data dictionaries in three global projects related to biodiversity and/or disease research: PARSEC, Kakila, ERINHA-Advance. The Kakila database centralizes and harmonizes marine mammal observation data for the AGOA sanctuary around the French archipelago of Guadeloupe, French Antilles. The PARSEC Project is building new tools for data sharing and reuse through a transnational investigation of the socioeconomic impact of protected areas. The ERINHA-Advance project aims to support the operations of the ERINHA research infrastructure which is designed to generate data from transnational access research activities on highly pathogenic agents. In these 3 global case-studies, similar challenges have arisen: to aggregate and interoperate pre-existing heterogeneous data at the global scale, and to share common tools to monitor, maintain quality, scan scale and cope with uncertainty. This poster proposes a draft common methodology, a data dictionary cookbook, which will provide a roadmap towards the building of large scale - data dictionaries. Topics proposed to be covered in such a cookbook include: how to search for existing and appropriate data dictionaries, controlled vocabularies or other semantic resources (before building a new one), the first steps for data dictionary building, data dictionary literacy (and why it is a mandatory work), how to define all scientific objects, aspects (or use existing one) and agree on the definitions with the whole community, building / proposing variables / indicators with ontology models, schemas, variables naming rules and context awareness, and finally addressing dimension issues considering each context. The common experience of our three projects showed that we need to proceed step by step as simply as possible and to ensure that each step is understandable for the whole community. It is necessary to improve access and re-use of all existing semantic materials and not trying to build a cathedral with a little spoon. {"references": ["David, R., Mabile, L., Specht, A., Stryeck, S., Thomsen, M., Yahia, M., Jonquet, C., Doll\u00e9, L., Jacob, D., Bailo, D., Bravo, E., Gachet, S., Gunderman, H., Hollebecq, J.-E., Ioannidis, V., Le Bras, Y., Lerigoleur, E., Cambon-Thomsen, A. and Research Data Alliance \u2013 SHAring Reward and Credit (SHARC) Interest Group, T.R.D., 2020. FAIRness Literacy: The Achilles' Heel of Applying FAIR Principles. Data Science Journal, 19(1), p.32. DOI: http://doi.org/10.5334/dsj-2020-032", "Coch\u00e9, L., Arnaud E., Bouveret L., David R., Foulquier E., Gandilhon N., Jeannesson E., Le Bras Y., Lerigoleur E., Lopez P., Madon B., Sananikone J., S\u00e8be M., Le Berre I., Jung J-L., 2021. Kakila database: Towards a FAIR community approved database of cetacean presence in the waters of the Guadeloupe archipelago based on citizen science. Biodiversity Data Journal: Data paper. submitted Dataset: https://doi.org/10.48502/cg6n-1103"]} PARSEC is funded by the Belmont Forum through the National Science Foundation (NSF), The São Paulo Research Foundation (FAPESP), the French National Research Agency (ANR), and the Japan Science and Technology Agency (JST). ERINHA Advance is funded by ERINHA-Advance european program under grant agreement Nº824061. Kakila database is funded by the LabEx DRIIHM French program "Investissements d'Avenir" (ANR-11-LABX-0010) and supported by the SO-DRIIHM project (ANR-19-DATA-0022). This work is partially funded by the EOSC-Life European program (grant agreement No. 824087)

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    Conference object . 2021
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      Other literature type . Article . 2021
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Altincekic, Nadide; Korn, Sophie Marianne; Qureshi, Nusrat Shahin; Dujardin, Marie; +126 Authors

    This work was supported by Goethe University (Corona funds), the DFG-funded CRC: “Molecular Principles of RNA-Based Regulation,” DFG infrastructure funds (project numbers: 277478796, 277479031, 392682309, 452632086, 70653611), the state of Hesse (BMRZ), the Fondazione CR Firenze (CERM), and the IWB-EFRE-program 20007375. This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 871037. AS is supported by DFG Grant SCHL 2062/2-1 and by the JQYA at Goethe through project number 2019/AS01. Work in the lab of KV was supported by a CoRE grant from the University of New Hampshire. The FLI is a member of the Leibniz Association (WGL) and financially supported by the Federal Government of Germany and the State of Thuringia. Work in the lab of RM was supported by NIH (2R01EY021514) and NSF (DMR-2002837). BN-B was supported by theNSF GRFP.MCwas supported byNIH (R25 GM055246 MBRS IMSD), and MS-P was supported by the HHMI Gilliam Fellowship. Work in the labs of KJ and KT was supported by Latvian Council of Science Grant No. VPP-COVID 2020/1-0014. Work in the UPAT’s lab was supported by the INSPIRED (MIS 5002550) project, which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure,” funded by the Operational Program “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and cofinanced by Greece and the EU (European Regional Development Fund) and the FP7 REGPOT CT-2011- 285950–“SEE-DRUG” project (purchase of UPAT’s 700MHz NMR equipment). Work in the CM-G lab was supported by the Helmholtz society. Work in the lab of ABö was supported by the CNRS, the French National Research Agency (ANR, NMRSCoV2- ORF8), the Fondation de la Recherche Médicale (FRM, NMR-SCoV2-ORF8), and the IR-RMN-THC Fr3050 CNRS. Work in the lab of BM was supported by the Swiss National Science Foundation (Grant number 200020_188711), the Günthard Stiftung für Physikalische Chemie, and the ETH Zurich. Work in the labs of ABö and BM was supported by a common grant from SNF (grant 31CA30_196256). This work was supported by the ETHZurich, the grant ETH40 18 1, and the grant Krebsliga KFS 4903 08 2019. Work in the lab of the IBS Grenoble was supported by the Agence Nationale de Recherche (France) RA-COVID SARS2NUCLEOPROTEIN and European Research Council Advanced Grant DynamicAssemblies. Work in the CA lab was supported by Patto per il Sud della Regione Siciliana–CheMISt grant (CUP G77B17000110001). Part of this work used the platforms of the Grenoble Instruct-ERIC center (ISBG; UMS 3518 CNRS-CEA-UGA-EMBL) within the Grenoble Partnership for Structural Biology (PSB), supported by FRISBI (ANR-10-INBS-05-02) and GRAL, financed within the University Grenoble Alpes graduate school (Ecoles Universitaires de Recherche) CBH-EUR-GS (ANR-17-EURE- 0003). Work at the UW-Madison was supported by grant numbers NSF MCB2031269 and NIH/NIAID AI123498. MM is a Ramón y Cajal Fellow of the Spanish AEI-Ministry of Science and Innovation (RYC2019-026574-I), and a “La Caixa” Foundation (ID 100010434) Junior Leader Fellow (LCR/BQ/PR19/11700003). Funded by project COV20/00764 fromthe Carlos III Institute of Health and the SpanishMinistry of Science and Innovation to MMand DVL. VDJ was supported by the Boehringer Ingelheim Fonds. Part of this work used the resources of the Italian Center of Instruct-ERIC at the CERM/ CIRMMP infrastructure, supported by the Italian Ministry for University and Research (FOE funding). CF was supported by the Stiftung Polytechnische Gesellschaft. Work in the lab of JH was supported by NSF (RAPID 2030601) and NIH (R01GM123249). The highly infectious disease COVID-19 caused by the Betacoronavirus SARS-CoV-2 poses a severe threat to humanity and demands the redirection of scientific efforts and criteria to organized research projects. The international COVID19-NMR consortium seeks to provide such new approaches by gathering scientific expertise worldwide. In particular, making available viral proteins and RNAs will pave the way to understanding the SARS-CoV-2 molecular components in detail. The research in COVID19-NMR and the resources provided through the consortium are fully disclosed to accelerate access and exploitation. NMR investigations of the viral molecular components are designated to provide the essential basis for further work, including macromolecular interaction studies and high-throughput drug screening. Here, we present the extensive catalog of a holistic SARS-CoV-2 protein preparation approach based on the consortium’s collective efforts. We provide protocols for the large-scale production of more than 80% of all SARS-CoV-2 proteins or essential parts of them. Several of the proteins were produced in more than one laboratory, demonstrating the high interoperability between NMR groups worldwide. For the majority of proteins, we can produce isotope-labeled samples of HSQC-grade. Together with several NMR chemical shift assignments made publicly available on covid19-nmr.com, we here provide highly valuable resources for the production of SARS-CoV-2 proteins in isotope-labeled form. Peer reviewed

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    https://doi.org/10.5445/ir/100...
    Article . 2021
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    https://doi.org/10.26083/tupri...
    Article . 2022
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: David, Romain; Richard, Audrey; Stepanyann, Diana; Versteeg, Krista; +4 Authors

    Reducing the risk of misuse of data is particularly crucial in the context of research on highly pathogenic agents. But as demonstrated during the COVID19 crisis, sharing data of high quality is a sine qua non condition to compare research results at a large scale.Our actual challenge is to ensure compliance with the FAIR principles while taking into account the dangers and pitfalls concerning dual use type data and samples (because there are often some good reasons to not share).Dual Use Research of Concern (DURC) is defined by the United States Government Policy for Oversight of Life Sciences as ”Life sciences research that, based on current understanding, can be reasonably anticipated to provide knowledge, information, products, or technologies that could be directly misapplied to pose a significant threat, with broad potential consequences, to public health and safety, agricultural crops and other plants, animals, the environment, materiel, or national security.” Many countries or regions have adopted laws to regulate exchanges concerning DURC. As an example, in the European Union, dual use biological materials are listed in Council Regulation (EC) No 428/2009" [https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32009R0428]. How can we take these aspects into account so that the respect of the FAIR principles is done while respecting these legislations? How to increase the possibilities of sharing dual use data, to reduce overlap, encourage collaboration on DURC while securing their uses? How to reward and credit back good practices?For example, what data should be prohibited to share? Who should be prohibited from sharing or accessing data which may be classified as DURC?DURC data typically falls into one or more of these categories:Demonstrate how to render a vaccine ineffectiveEnhance the harmful consequences of a pathogen or toxin or render a non-pathogen virulent Increase the transmissibility of a pathogen Alter the host range of a pathogen or toxin Enable evasion of diagnostic or detection modalities Enhance the susceptibility of a host population to a pathogen or toxin Generate or reconstitute certain eradicated or extinct pathogens or toxins Enable weaponization of a biological agent or toxin. This poster aims to present the landscape of DURC data in Europe, the main actors and their responsibilities. It underlines that pre-approved data sharing agreements is probably one major possible recommendation with highly secured repositories. Additionally, a consideration of DURC in actual Data stewardship should be developed. Conversely, another pitfall would be to be too careful and to classify all data in dual uses, and to prevent re-use despite public health issues. Indeed, reducing duplication of effort and improving trial design concerning Dual Use research is a challenge, at least inside a country or a community of countries (e.g. Europe) that need to identify actors and organize their interactions. We also recommend that for this dual use data sharing information and authorized metadata should be available centrally on an intergovernmental web page with explicit authority contact and / or be applied considering officials sharing conventions. International audience

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: David, Romain; Bouveret, Laurent; Coché, Lorraine; Corrêa, Pedro Pizzigatti; +21 Authors

    We are now facing profound changes (biodiversity, climate, pandemic, etc.). Human impacts and their mitigation will depend on our ability to mobilize research at the global level. The sustainable development of the society will largely depend on the sustainable development of global science and scientific research tools, outputs, and research ecosystems. This globalization of research requires interoperating our observation and experimentation systems in order to better understand these changes, to better simulate their effects. The Covid-19 pandemic is now raging around the world. The reproducibility of research and results across regions in different contexts should accelerate human responses. Data sharing and the development of Synthesis Research with data aggregation at large scale is critical to enable such processes. The use of common knowledge, vocabularies, standards and procedures at a large scale is necessary. The objective of this poster is to report on the challenges met while building data dictionaries in three global projects related to biodiversity and/or disease research: PARSEC, Kakila, ERINHA-Advance. The Kakila database centralizes and harmonizes marine mammal observation data for the AGOA sanctuary around the French archipelago of Guadeloupe, French Antilles. The PARSEC Project is building new tools for data sharing and reuse through a transnational investigation of the socioeconomic impact of protected areas. The ERINHA-Advance project aims to support the operations of the ERINHA research infrastructure which is designed to generate data from transnational access research activities on highly pathogenic agents. In these 3 global case-studies, similar challenges have arisen: to aggregate and interoperate pre-existing heterogeneous data at the global scale, and to share common tools to monitor, maintain quality, scan scale and cope with uncertainty. This poster proposes a draft common methodology, a data dictionary cookbook, which will provide a roadmap towards the building of large scale - data dictionaries. Topics proposed to be covered in such a cookbook include: how to search for existing and appropriate data dictionaries, controlled vocabularies or other semantic resources (before building a new one), the first steps for data dictionary building, data dictionary literacy (and why it is a mandatory work), how to define all scientific objects, aspects (or use existing one) and agree on the definitions with the whole community, building / proposing variables / indicators with ontology models, schemas, variables naming rules and context awareness, and finally addressing dimension issues considering each context. The common experience of our three projects showed that we need to proceed step by step as simply as possible and to ensure that each step is understandable for the whole community. It is necessary to improve access and re-use of all existing semantic materials and not trying to build a cathedral with a little spoon. {"references": ["David, R., Mabile, L., Specht, A., Stryeck, S., Thomsen, M., Yahia, M., Jonquet, C., Doll\u00e9, L., Jacob, D., Bailo, D., Bravo, E., Gachet, S., Gunderman, H., Hollebecq, J.-E., Ioannidis, V., Le Bras, Y., Lerigoleur, E., Cambon-Thomsen, A. and Research Data Alliance \u2013 SHAring Reward and Credit (SHARC) Interest Group, T.R.D., 2020. FAIRness Literacy: The Achilles' Heel of Applying FAIR Principles. Data Science Journal, 19(1), p.32. DOI: http://doi.org/10.5334/dsj-2020-032", "Coch\u00e9, L., Arnaud E., Bouveret L., David R., Foulquier E., Gandilhon N., Jeannesson E., Le Bras Y., Lerigoleur E., Lopez P., Madon B., Sananikone J., S\u00e8be M., Le Berre I., Jung J-L., 2021. Kakila database: Towards a FAIR community approved database of cetacean presence in the waters of the Guadeloupe archipelago based on citizen science. Biodiversity Data Journal: Data paper. submitted Dataset: https://doi.org/10.48502/cg6n-1103"]} PARSEC is funded by the Belmont Forum through the National Science Foundation (NSF), The São Paulo Research Foundation (FAPESP), the French National Research Agency (ANR), and the Japan Science and Technology Agency (JST). ERINHA Advance is funded by ERINHA-Advance european program under grant agreement Nº824061. Kakila database is funded by the LabEx DRIIHM French program "Investissements d'Avenir" (ANR-11-LABX-0010) and supported by the SO-DRIIHM project (ANR-19-DATA-0022). This work is partially funded by the EOSC-Life European program (grant agreement No. 824087)

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    Conference object . 2021
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Altincekic, Nadide; Korn, Sophie Marianne; Qureshi, Nusrat Shahin; Dujardin, Marie; +126 Authors

    This work was supported by Goethe University (Corona funds), the DFG-funded CRC: “Molecular Principles of RNA-Based Regulation,” DFG infrastructure funds (project numbers: 277478796, 277479031, 392682309, 452632086, 70653611), the state of Hesse (BMRZ), the Fondazione CR Firenze (CERM), and the IWB-EFRE-program 20007375. This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 871037. AS is supported by DFG Grant SCHL 2062/2-1 and by the JQYA at Goethe through project number 2019/AS01. Work in the lab of KV was supported by a CoRE grant from the University of New Hampshire. The FLI is a member of the Leibniz Association (WGL) and financially supported by the Federal Government of Germany and the State of Thuringia. Work in the lab of RM was supported by NIH (2R01EY021514) and NSF (DMR-2002837). BN-B was supported by theNSF GRFP.MCwas supported byNIH (R25 GM055246 MBRS IMSD), and MS-P was supported by the HHMI Gilliam Fellowship. Work in the labs of KJ and KT was supported by Latvian Council of Science Grant No. VPP-COVID 2020/1-0014. Work in the UPAT’s lab was supported by the INSPIRED (MIS 5002550) project, which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure,” funded by the Operational Program “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and cofinanced by Greece and the EU (European Regional Development Fund) and the FP7 REGPOT CT-2011- 285950–“SEE-DRUG” project (purchase of UPAT’s 700MHz NMR equipment). Work in the CM-G lab was supported by the Helmholtz society. Work in the lab of ABö was supported by the CNRS, the French National Research Agency (ANR, NMRSCoV2- ORF8), the Fondation de la Recherche Médicale (FRM, NMR-SCoV2-ORF8), and the IR-RMN-THC Fr3050 CNRS. Work in the lab of BM was supported by the Swiss National Science Foundation (Grant number 200020_188711), the Günthard Stiftung für Physikalische Chemie, and the ETH Zurich. Work in the labs of ABö and BM was supported by a common grant from SNF (grant 31CA30_196256). This work was supported by the ETHZurich, the grant ETH40 18 1, and the grant Krebsliga KFS 4903 08 2019. Work in the lab of the IBS Grenoble was supported by the Agence Nationale de Recherche (France) RA-COVID SARS2NUCLEOPROTEIN and European Research Council Advanced Grant DynamicAssemblies. Work in the CA lab was supported by Patto per il Sud della Regione Siciliana–CheMISt grant (CUP G77B17000110001). Part of this work used the platforms of the Grenoble Instruct-ERIC center (ISBG; UMS 3518 CNRS-CEA-UGA-EMBL) within the Grenoble Partnership for Structural Biology (PSB), supported by FRISBI (ANR-10-INBS-05-02) and GRAL, financed within the University Grenoble Alpes graduate school (Ecoles Universitaires de Recherche) CBH-EUR-GS (ANR-17-EURE- 0003). Work at the UW-Madison was supported by grant numbers NSF MCB2031269 and NIH/NIAID AI123498. MM is a Ramón y Cajal Fellow of the Spanish AEI-Ministry of Science and Innovation (RYC2019-026574-I), and a “La Caixa” Foundation (ID 100010434) Junior Leader Fellow (LCR/BQ/PR19/11700003). Funded by project COV20/00764 fromthe Carlos III Institute of Health and the SpanishMinistry of Science and Innovation to MMand DVL. VDJ was supported by the Boehringer Ingelheim Fonds. Part of this work used the resources of the Italian Center of Instruct-ERIC at the CERM/ CIRMMP infrastructure, supported by the Italian Ministry for University and Research (FOE funding). CF was supported by the Stiftung Polytechnische Gesellschaft. Work in the lab of JH was supported by NSF (RAPID 2030601) and NIH (R01GM123249). The highly infectious disease COVID-19 caused by the Betacoronavirus SARS-CoV-2 poses a severe threat to humanity and demands the redirection of scientific efforts and criteria to organized research projects. The international COVID19-NMR consortium seeks to provide such new approaches by gathering scientific expertise worldwide. In particular, making available viral proteins and RNAs will pave the way to understanding the SARS-CoV-2 molecular components in detail. The research in COVID19-NMR and the resources provided through the consortium are fully disclosed to accelerate access and exploitation. NMR investigations of the viral molecular components are designated to provide the essential basis for further work, including macromolecular interaction studies and high-throughput drug screening. Here, we present the extensive catalog of a holistic SARS-CoV-2 protein preparation approach based on the consortium’s collective efforts. We provide protocols for the large-scale production of more than 80% of all SARS-CoV-2 proteins or essential parts of them. Several of the proteins were produced in more than one laboratory, demonstrating the high interoperability between NMR groups worldwide. For the majority of proteins, we can produce isotope-labeled samples of HSQC-grade. Together with several NMR chemical shift assignments made publicly available on covid19-nmr.com, we here provide highly valuable resources for the production of SARS-CoV-2 proteins in isotope-labeled form. Peer reviewed

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    https://doi.org/10.5445/ir/100...
    Article . 2021
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    https://doi.org/10.26083/tupri...
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: David, Romain; Richard, Audrey; Stepanyann, Diana; Versteeg, Krista; +4 Authors

    Reducing the risk of misuse of data is particularly crucial in the context of research on highly pathogenic agents. But as demonstrated during the COVID19 crisis, sharing data of high quality is a sine qua non condition to compare research results at a large scale.Our actual challenge is to ensure compliance with the FAIR principles while taking into account the dangers and pitfalls concerning dual use type data and samples (because there are often some good reasons to not share).Dual Use Research of Concern (DURC) is defined by the United States Government Policy for Oversight of Life Sciences as ”Life sciences research that, based on current understanding, can be reasonably anticipated to provide knowledge, information, products, or technologies that could be directly misapplied to pose a significant threat, with broad potential consequences, to public health and safety, agricultural crops and other plants, animals, the environment, materiel, or national security.” Many countries or regions have adopted laws to regulate exchanges concerning DURC. As an example, in the European Union, dual use biological materials are listed in Council Regulation (EC) No 428/2009" [https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32009R0428]. How can we take these aspects into account so that the respect of the FAIR principles is done while respecting these legislations? How to increase the possibilities of sharing dual use data, to reduce overlap, encourage collaboration on DURC while securing their uses? How to reward and credit back good practices?For example, what data should be prohibited to share? Who should be prohibited from sharing or accessing data which may be classified as DURC?DURC data typically falls into one or more of these categories:Demonstrate how to render a vaccine ineffectiveEnhance the harmful consequences of a pathogen or toxin or render a non-pathogen virulent Increase the transmissibility of a pathogen Alter the host range of a pathogen or toxin Enable evasion of diagnostic or detection modalities Enhance the susceptibility of a host population to a pathogen or toxin Generate or reconstitute certain eradicated or extinct pathogens or toxins Enable weaponization of a biological agent or toxin. This poster aims to present the landscape of DURC data in Europe, the main actors and their responsibilities. It underlines that pre-approved data sharing agreements is probably one major possible recommendation with highly secured repositories. Additionally, a consideration of DURC in actual Data stewardship should be developed. Conversely, another pitfall would be to be too careful and to classify all data in dual uses, and to prevent re-use despite public health issues. Indeed, reducing duplication of effort and improving trial design concerning Dual Use research is a challenge, at least inside a country or a community of countries (e.g. Europe) that need to identify actors and organize their interactions. We also recommend that for this dual use data sharing information and authorized metadata should be available centrally on an intergovernmental web page with explicit authority contact and / or be applied considering officials sharing conventions. International audience

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