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Topic
FAIR or Fiction? Data Harmony in Biomedicine
Description
Data production in Life Sciences and Biomedicine is at an all time high. Scientists and clinicians have laboratory instruments at their disposal that can deeply explore the nature of life and disease, generating massive amounts of data quickly for relatively little money. As a result, life sciences has become among the top data generators out of all science.
Along with the massive press to advance Artificial Intelligence (AI), the sheer volume and analytics needs of the field now require a better understanding of datasets, the ability to create high-quality cohorts of data quickly, and the ability to utilize large amounts of data from other sources in single meta-analyses.
That’s where the concept of data being FAIR (Findable, Accessible, Interoperable, and Reusable) comes into play. FAIR refers to the ideal state of data management for scientific data. While the industry has been refining and trying different approaches to FAIR for the last decade, it has yet to agree on any data standards or formats, thus making FAIR fleeting. In this webinar, we’ll discuss the drivers of data analytics in biomedicine, where we stand on the journey towards FAIR, cultural considerations relevant to that journey, and the potential future of scientific discovery if we reach the goal of FAIR data.
Time
Nov 9, 2022 01:00 PM in
Eastern Time (US and Canada)
Webinar is over, you cannot register now. If you have any questions, please contact Webinar host:
BioTeam, Inc.
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Hi there, You are invited to a Zoom webinar. When: Nov 9, 2022 01:00 PM Eastern Time (US and Canada) Topic: FAIR or Fiction? Data Harmony in Biomedicine Register in advance for this webinar: https://bioteam-net.zoom.us/webinar/register/WN_VzA37nn3Twi6NWxQF7c7IA After registering, you will receive a confirmation email containing information about joining the webinar. ---------- Webinar Speakers Ari E. Berman, Ph.D. (CEO @BioTeam, Inc.) Dr. Berman is an expert in Scientific Computing specializing in high performance computing (HPC), high-performance networks, data centers, storage, cloud, general IT infrastructure, and bioinformatics and data analytics. He has been designing, building, and operating scientific computing environments for 26 years and strives to advocate for science and empower researchers to make discoveries from their complex datasets. His ultimate goal is to help create a dynamic enough abstraction of flexible infrastructure from research end-users to enable anyone to analyze and gain knowledge from very complex datasets.
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