Using Spreadsheets for Organizing Data 

Join today
  • Instructor: Meghan Landry 
  • Level: Beginner
  • Duration: 3 hours
  • Helpers: TBD
  • Date:  January 28, 2026 | 1:00 - 4:00 pm (Atlantic)
  • Prerequisite: None
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COURSE DESCRIPTION

Good data organization is the foundation of any research project. Most researchers have data in spreadsheets, so it’s the starting place for many research projects. To use tools that make computation and analysis more efficient, such as programming languages like R or Python, we need to structure our data the way that computers need the data. This workshop aims to teach researchers basic concepts, skills, and tools for working with data to get more done quickly and with less pain. In this lesson, you will learn good data entry practices, how to avoid common formatting mistakes, approaches for handling dates in spreadsheets, basic quality control and data manipulation, and exporting data from spreadsheets. 

SETUP REQUIREMENTS
  • To interact with spreadsheets, you can use LibreOffice, Microsoft Excel, Google Sheets, or other programs. For this lesson, if you don’t have a spreadsheet program already, you can install LibreOffice. It’s a free, open source spreadsheet program.

Meet our team!

Meghan Landry

Instructor 

Humanities & Social Sciences Research Specialist
Meghan Landry is the Humanities & Social Sciences (HSS) Research Specialist with ACENET, and one of the Alliance HSS National Team Leads. She possesses an MLIS from McGill University and a BA in English Literature from UPEI. She joined ACENET from St. Francis Xavier University where she was the Scholarly Communications Librarian. Meghan specializes in working with sensitive data, digital humanities, and research data management. She is still based at StFX University, but serves all of Atlantic Canada and is active in national and regional humanities & social sciences initiatives.

Tannia Chevez

Host

Digital Training Specialist
BSc Computational Chemistry, Memorial University

Tannia joined ACENET in 2023 and is based in St. John’s. She has held positions as a research assistant in various departments, with responsibilities ranging from developing algorithms for an online animal sound repository, to crafting chemical composite films. Proficient in Python, Java, and JavaScript, she has focused on spectral data analysis, SEM image-based nanoparticle detection, and software development for data analysis. Tannia contributed significantly to the publication of a research paper by analyzing potential environmental toxicants, generating millions of chemical structure IDs, and conducting data extraction and analysis using Python, R, and JavaScript, as well as enhancing algorithms for simulating potential environmental toxicants’ behavior in water, soil, and air environments. Tannia’s teaching experience includes a Leader Instructor at Brilliant Labs where she taught a range of digital topics, and a Digital Literacy Instructor for the Association for New Canadians.

Ross Dickson

Helper

Lead Research Consultant

Ph.D. Computational Chemistry, Queen’s University

ITIL Foundation Certificate

Based at Dalhousie University, Ross joined ACENET in 2007 as a Research Consultant. His responsibilities span education, documentation, and client support, and he manages job scheduling policies on ACENET’s high-performance computing clusters. He has worked with users across many disciplines including chemistry, physics, biology, oceanography, neuroscience, several engineering disciplines, philosophy, and management studies. Following his doctoral and postdoctoral studies in computational chemistry, Ross worked in software development for Hypercube Inc., makers of HyperChem for Windows, and for Molecular Mining Corporation where he helped specify some of the earliest software for analyzing high-throughput gene expression data.

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We are an Atlantic Canadian not-for-profit providing access to advanced digital research infrastructure, expertise, support and training to academic, industry and government researchers. Learn more about ACENET

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