DataFlash: Explore Routes to Learning Data Librarianship with the NNLM Data Pathways Tool

Posted by Carolann Curry on September 24th, 2024 Posted in: Blog, Data Science
Tags: Data Management, Data science, research data management

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Learning about research data management (RDM) presents unique challenges for medical librarians and information professionals, especially as the landscape of data-driven medical research grows more complex. Many librarians may lack formal training in data science or may feel overwhelmed by the technical skills required to manage, curate, and support research data. With the rapid evolution of data standards, tools, and technologies, it can be challenging for librarians to stay current and offer their users relevant guidance on data management and best practices.

Launched earlier this year, NNLM Data Pathways is a tool where library and information professionals can explore relevant NLM and NNLM courses, trainings, and webinars that strengthen their unique professional journey in data management. The resource is divided into three areas of focus so users can customize offerings based on their own interests and skill level:

• Generalist – In the Generalist path, you can see resources and training opportunities to have a broad understanding of data librarianship. This path is recommended for those who are getting started and need to offer a wide variety of data services for their institution or for those who want the ability to grow further in any area of data librarianship.
• Data Management – In the Data Management path, you can learn about trainings, resources, and other offerings for data storage, data sharing, quality control, data description, and data curation. This path is recommended for people interested in data management, data curation, or data repository and other related library roles.
• Data Science – In the Data Science path, the offerings provide training and insight into the concepts, skills, and resources around data literacy – or the ability to read, interpret, explore, and communicate data. This path is recommended for data science, social science data, data analysis, and other related library roles.

All three options incorporate data ethics, inclusion, and accessibility as primary components, and all count toward the Medical Library Association Data Services Specialization (DSS). As a reminder, NNLM offers sponsorship of DSS fees to residents of any NNLM region and U.S. citizens living outside the U.S. To learn more about the MLA DSS and NNLM’s fee sponsorship process, visit the NNLM DSS resource guide here.