Suchergebnisse

The Research Data Alliance (ambassador poster) With over 9000 members from 137 countries, RDA provides neutral space where its members can come together to work towards Research Data Sharing without barriers. The Research Data Alliance (RDA) was launched as a community-driven initiative in 2013 by the European Commission, the United States Government's National Science Foundation and National Institute of Standards and Technology, and the Australian Government's Department of Innovation with the goal of building the social and technical infrastructure to enable open sharing and re-use of data. RDA has a grass-roots, inclusive approach covering all data lifecycle stages in all science domains, engaging data producers, users and stewards, addressing data exchange, processing, and storage. It has succeeded in creating the neutral social platform where international research data experts meet to exchange views and to agree on topics including social hurdles on data sharing, education and training challenges, data management plans and certification of data repositories, disciplinary and interdisciplinary interoperability, as well as technological aspects. ; Text mainly from RDA website. www.rd-alliance.org/about-rda

In order to increase all aspects of data discovery, accessibility and reusability, FAIRplus is launching a unique Fellowship Programme. By pooling PhD and/or postdoc students from Life Sciences departments of affiliated academic institutions with expert partners from SMEs, the programme provides an opportunity for researchers to build FAIRdata research groups in the field of FAIR data management. The programme is designed by the FRAUNHOFER INSTITUT FIT and implemented by selected FAIRplus partners. The purpose of this Fellowship Programme is to intensively train eligible PhD and/or postdoc students together with industry partners (from the EFPIA and SME network) in FAIR data management procedures. An increased knowledge transfer for FAIR data transformations will naturally lead to a wider sharing of best practices, greater opportunities for innovation, and more insights that can benefit the whole of society. The Fellowship Programme is - until further notice - scheduled to be active until the end of 2021. The following report provides an overview of the FAIR Fellowship Application Process, eligibility, preliminary application deadlines, information about the evaluation process as well as the evaluation criteria of both candidates and the selection of suitable project data sets. ; This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 802750. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation and EFPIA companies.

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 ineffective Enhance 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 ...

International audience ; 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 ...

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 ineffective Enhance 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 ...