Feb
01
Posted by Carolann Curry on February 1st, 2024
Posted in: Data Science
Tags: Love Data Week
International Love Data Week is a five-day annual event aimed at raising awareness and promoting responsible data practices among researchers, students, librarians, and other stakeholders. Love Data Week inspires a deeper understanding of the value of data and encourages the adoption of research data management and sharing best practices. This event serves as a platform to promote awareness and appreciation for the role data plays in advancing knowledge across various disciplines. Join NNLM as we celebrate Love Data Week and recognize the power of data in driving research forward and shaping a more informed and interconnected world.
Tuesday, Feb. 13th
Artificial Intelligence & Healthcare: An Overview for the Curious (sponsored by Region 1)
11:00 a.m. – 12:00 p.m. PT/12:00 p.m. – 1:00 p.m. MT/1:00 p.m. – 2:00 p.m. CT/2:00 p.m. – 3:00 p.m. ET
AI is widely utilized in healthcare. This presentation provides a friendly introduction to the topic for librarians, health professionals, and anyone with an interest in the topic. Attendees will come away informed about the field’s history, conversant with definitions of important concepts, an understanding of how AI can become biased (and what that means for patients), and familiar with some of the many ways that AI is currently being used in healthcare. This class is eligible for 1 MLA CE credit.
An Overview of the All of Us Researcher Workbench and the Role of the Library (sponsored by the All of Us Program Center)
12:00 p.m. – 1:00 p.m. PT/1:00 p.m. – 2:00 p.m. MT/2:00 p.m. – 3:00 p.m. CT/3:00 p.m. – 4:00 p.m. ET
Campus libraries are well situated to respond to the needs of academic institutions for data-driven research; provide access to a diverse, longitudinal dataset; utilize training materials to assist campus communities. The All of Us Researcher Hub houses one of the largest, most diverse, and most broadly accessible datasets ever assembled. Built in partnership with participants spanning different ages, races, ethnicities, and regions of the country, it currently includes physical measurements, surveys, wearables, electronic health records, and genomics. Join us as we learn about the participants, explore the data offered, learn how to become a registered user, and discover why this data is of value to your academic libraries and campus communities. This class is eligible for 1 credit of MLA CE and DSS Level 1.
Wednesday, Feb. 14th
All’s FAIR in Love and…Software: Operationalizing FAIR in Research Software (sponsored by Region 5 and the National Center for Data Services)
11:00 a.m. – 12:00 p.m. PT/12:00 p.m. – 1:00 p.m. MT/1:00 p.m. – 2:00 p.m. CT/2:00 p.m. – 3:00 p.m. ET
Biomedical research software come in various formats such as Python scripts, desktop software, or web applications, and are developed for various purposes such as data visualization, computational modeling, or artificial intelligence (AI) development. They have become an essential part of biomedical research, especially with the advent of cloud computing and AI. Making biomedical research software reusable is therefore critical to enable the reproducibility of research results, prevent duplicate efforts, and ultimately increase the pace of discoveries. In this talk, we discuss the importance of biomedical research software, why they should be made reusable, and how this can be achieved by developers and managers of biomedical research software. We particularly cover the FAIR Principles for Research Software (FAIR4RS Principles), which are adaptations of the FAIR Principles tailored specially for making research software reusable. We also present the FAIR Biomedical Research Software (FAIR-BioRS) guidelines, which are a set of minimal, actionable, step-by-step instructions we have established for developers to easily make their biomedical research software reusable in compliance with the FAIR4RS Principles. This class is eligible for 1 credit of MLA CE.
Thursday, Feb. 15th
NIH Data Management and Sharing Policy Overview (sponsored by the National Center for Data Services)
9:00 a.m. – 10:30 p.m. PT/10:00 a.m. – 11:30 a.m. MT/11:00 a.m. – 12:30 p.m. CT/12:00 p.m. ET – 1:30 p.m. ET
The NIH Data Management and Sharing Policy requires funded researchers to submit a plan outlining how scientific data from their research will be managed and shared. This session is intended for information professionals who are unfamiliar with this policy and it will review the policy components and how you can prepare to address the policy at your institution. Topics to be covered include the context for the policy, the scope, the various components of the policy, institutional considerations for working with the policy in place, and tools and resources already available to help. This class is eligible DSS Level 1 and 1.5 credits of MLA CE.
Learn more about the MLA’s Data Services Specialization (DSS) here, including instructions on how to request that NNLM sponsor your application fees!