Webinar – Securing bibliographic data Training Home Our news Webinars Webinar – Securing bibliographic data 16/06/2021 Purpose of the webinar In a health context where telecommuting is becoming the norm, outsourcing bibliographic data is a real issue for private and public research organizations. The storage and security of these data become the central pivot of a fluid and accessible work process. Join our Webinar on securing bibliographic data and learn how to keep the scientific production value chain on a stable and secure infrastructure. Date and duration Thursday, May 6, 2021 at 11:00 a.m. – duration 45mn Terms of participation Free and online, a zoom link will be distributed to registrants by May 6. The webinar will be delivered in French. The topics covered during the webinar We will explore together: How your bibliographic data can be a treasure trove for the competition if not locked awayHow to make your data accessible while protecting its confidentiality and ensuring partitioned access for both your internal and external usersHow to collaborate on your research projects via a simple and secure toolThe different types of storage and access offered as well as their specificities The speaker Maxime DE COURVILLE From a Computer Systems Administration background, Maxime joined RITME in 2018 to support research centers on their projects of integration and implementation of bibliographic management tools offered by RITME. He has been helping R&D engineers and information professionals for several years around topics related to bibliographic technique, knowledge organization and centralization of scientific data. I register Also read 17/06/2021 Ritme Innovation Leaders using Intel® oneAPI Cross-architecture Tools OneAPI is driving a new era of accelerated computing across XPU architectures (CPU, GPU, FPGA, other accelerators). Read more Read more 22/05/2021 Webinars MIPAR Webinar – Metal characterization using deep learning image analysis In this webinar, you will learn how to use MIPAR for image segmentation analysis in metals using Deep Learning. Read more Read more