BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20260808T214327Z UID:0ca3e5c5-c1fb-45b6-b475-64fa15fe0733 DTSTART:20241023T000000Z DTEND:20241024T000000Z DESCRIPTION:# Overview\nThe exponential growth of data has urged the scient ific community to consider developing efficient FAIR Research Data Managem ent (RDM) strategies with an “Open Data” philosophy and implementing r obust Data Management Plans (DMP) for research projects.\nAdopting best RD M practices including FAIR principles (Findable\, Accessible\, Implementab le\, Reusable)**1** not only enhances the value of your data by boosting v isibility\, reproducibility\, and reuse\, but also increases confidence in your findings**2-4** and opens up opportunities for new collaborations.\n These practices are mandated by funding agencies such as the Swiss Nation al Science Foundation (SNFS) and Horizon Europe\, as well as by leading pu blishing platforms.\n\n\nThis course\, given by researchers and profession als involved in Research Data Management and in Data Management Plan prepa ration at ELIXIR-CH\, SIB/Vital-IT and DSBU/FBM-UNIL/CHUV\, will provide y ou with the knowledge and the tools **5** to generate robust data and exce llent quality studies that follow the FAIR principles. This course will al so provide you with effective support to build high quality DMP complying with the guidelines established by funding agencies. \n\n*Sources of infor mation*\n\n**1** Wilkinson\, M.\, Dumontier\, M.\, Aalbersberg\, I. et al. The FAIR Guiding Principles for scientific data management and stewardshi p. Sci Data 3\, 160018 (2016). DOI: [https://doi.org/10.1038/sdata.2016.18 ](https://doi.org/10.1038/sdata.2016.18)\n\n**2** Baker\, M. 1\,500 scient ists lift the lid on reproducibility. Nature 533\, 452–454 (2016). DOI: [https://doi.org/10.1038/533452a](https://doi.org/10.1038/533452a)\n\n**3* * Begley\, C G\, and Ioannidis\, J. PA. “Reproducibility in science impr oving the standard for basic and preclinical research.” Circulation rese arch. 2015\; 116.1: 116-126. DOI: [10.1161/CIRCRESAHA.114.303819](https:// doi.org/10.1161/circresaha.114.303819) \n\n**4** Asher Mullard\, “Precl inical cancer research suffers another reproducibility blow” Nature Revi ews Drug Discovery 21\, 89 (2022). DOI: [https://doi.org/10.1038/d41573-02 2-00012-6](https://doi.org/10.1038/d41573-022-00012-6)\n\n**5** RDMkit: RD Mkit The ELIXIR Research Data Management Kit.2022. [https://rdmkit.elixir- europe.org/index.html](https://rdmkit.elixir-europe.org/index.html). \n\n # Schedule\n**First day- 09:00-17:00 CET**\n\nAt first\, participants will be introduced to the notion of research reproducibility and to the need f or a Data Management Plan (DMP) preparation\, an evolving document reporti ng how the research data will be managed during and after a research proje ct. You will learn best practices in FAIR Research Data Management (RDM) w ith a focus on data collection and data documentation. \nDuring the exerci ses\, participants will directly apply what they have learned. \n\n \n\nIn the afternoon\, you will learn additional steps of the RDM cycle concerni ng ethics\, legal\, security issues\, data preservation and data sharing\, as well as an overview of the FAIR principles. During the exercises you w ill learn how to share your data on suitable repositories\, such as [Zeno do](https://zenodo.org/). \n\n**Second day- 09:00-17:00 CET**\n\nOn the se cond day\, participants will gain hands-on experience creating Data Manage ment Plans (DMPs) tailored to their research using the effective and colla borative [Data Stewardship Wizard (DSW)](https://ds-wizard.org/) tool. The y will also have the opportunity to share and receive feedback on their dr aft DMPs through group discussions. \n\n# Audience\nThe course is address ed to PhD students\, postdocs and researchers involved in life sciences a nd clinical research.\n\n# Learning objectives\nAt the end of the course y ou will be able to:\n* Manage the main steps of your research rata using b est practices and guidelines (RDM) \n* Understand the FAIR guiding princip les and Open Data foundations \n* Understand the requirements of a Data Ma nagement Plan (DMP) \n* Use the [DSW](https://ds-wizard.org/) tool to comp lete your own DMP \n\n# Prerequisites\n##### ***Knowledge / competencies** *\nTo be involved in Life Sciences or clinical research.\n\n##### ***Techn ical***\nYou will need a laptop with a web browser installed. \n\n\n# Trai ners\n* Cécile Lebrand - Head of the Data Stewardship Biomed Unit (DSBU) at FBM UNIL- CHUV \n\n* Vassilios Ioannidis - Lead Computational Biologist - FAIR specialist at SIB/Vital-IT and DSBU/FBM UNIL-CHUV\n\n* Grégoire Rossier - Training Manager at SIB Training &\; Project Manager at SIB/V ital-IT\n\n# Application\n\n\n\n\n\n\nWhile participants are registered on a first come\, first served basis\, exceptions may be made to ensure dive rsity and equity\, which may increase the time before your registration is confirmed.\n\nDeadline for cancellation is set to **09/10/2024**.\n\nYou will be informed by email of your registration confirmation. \n\n # Venue and time\n\n\nThis course will ONLY be held in person at the University of Lausanne (Metro M1 line\, Sorge station). **No online streaming will be o ffered.**\n\nIt will start at 9:00 and end around 17:00 on each day.\n\nPr ecise information will be provided to the participants before the course.\ n\n# Additional information\nCoordination: Valeria Di Cola\, SIB Training Group\n\nYou are welcome to register to the SIB courses mailing list to b e informed of all future courses and workshops\, as well as all important deadlines using the form [here](https://lists.sib.swiss/postorius/lists/co urses.lists.sib.swiss/).\n\nPlease note that participation in SIB courses is subject to our [general conditions](https://www.sib.swiss/training/term s-and-conditions).\n\nSIB abides by the [ELIXIR Code of Conduct](https://e lixir-europe.org/events/code-of-conduct). Participants of SIB courses are also required to abide by the same code.\nFor more information\, please co ntact [training@sib.swiss](mailto://training@sib.swiss). SUMMARY:Open and reusable research: boost the value of your data URL;VALUE=URI:https://www.sib.swiss/training/course/20241023_ORRBV END:VEVENT END:VCALENDAR