NNLM webinar teaches basic spreadsheet setup and simple charting; points to NIH data-management resources

Justin Dela Cruz, associate director of the National Center for Data Services, and Sarah Gonzalez, a data librarian at Northwestern University's Galter Health Sciences Library and Learning Center, led a Network of the National Library of Medicine (NNLM) webinar titled "Data for Everyone: an introduction to spreadsheets." The session combined short definitions of data terms, a hands-on demonstration in Google Sheets and Excel, and pointers to training resources.

The presenters opened by framing the class around three goals: define common health-data terms, prepare a spreadsheet for analysis, and create a simple visualization. "My name is Justin Dela Cruz," Justin said in his introduction, and Sarah explained, "The NNLM is the network of the National Library of Medicine," noting NNLM is an outreach program of the National Library of Medicine (an institute of NIH).

The webinar covered practical steps for beginners: choose clear column headers as variable names, keep a consistent data type per column (text, number, or date), and format cells early so spreadsheet software does not misinterpret values. Using a simple example—an invoice-style spreadsheet with product name, quantity, unit price, total price and a gift/personal flag—the presenters showed how column choices drive analytic questions (for example, "How much is spent on gifts in a given month?").

Justin demonstrated creating a linked chart from selected cells in Google Sheets, switching the automatic pie chart to a bar chart, and using sort-by-counts so the chart displays categories from smallest to largest for easier comparison. He emphasized that charts remain linked to source data so updates are reflected automatically. On formatting, presenters advised setting the numeric format for count fields (integers without decimal places) and using built-in table and filter tools to clean and explore data.

During a live Q&A, presenters said Google Sheets and Excel share many features; Excel desktop retains offline capability while cloud variants differ slightly. They also pointed attendees to more advanced training—Python or R for larger datasets, Carpentries lessons for programming, and NNLM on-demand courses covering research data management, data sharing, open science and data ethics.

The presenters highlighted resources where materials and recordings will be posted: an NNLM Zenodo repository that will host class slides and recordings and an NNLM YouTube playlist. They also referenced the NIH Data Management and Sharing policy, noting it went into effect in January 2023 and is driving demand for documented data management plans among NIH grantees; NNLM offers materials to help researchers and librarians navigate those requirements.

The session closed with a request that attendees complete a short survey (also used to claim continuing-education credit), an invitation to submit topic suggestions for future classes (formulas, macros, deeper spreadsheet training), and contact information for follow-up. Presenters said registrants will receive email links to handouts and recordings.