2024/11/27 by Marla I. Hertz, Ashley S. McNeill · 5 voices · 4 citations
Computer Science · Biochemistry, Genetics and Molecular Biology · Decision Sciences · #Research Data Management Practices #Biomedical Text Mining and Ontologies #Scientific Computing and Data Management
paper · doi:10.1371/journal.pcbi.1012604
Proper handling of tabular data, i.e., spreadsheets, is an essential skill for most researchers.Well-curated tabular data has built-in quality control, is machine readable by downstream analysis applications, and ultimately saves researchers' time.The increased expectation of data sharing grounded by funder and publisher policies has made it even more crucial to format and describe tabular data properly to ensure that it is FAIR-findable, accessible, interoperable, and reusable [1].However, many researchers are not formally trained in the data management skills necessary to build strong tabular datasets.They may also struggle to anticipate the future needs and potential applications of their data.This article attempts to demystify tabular data practices and outlines 11 tips presented roughly in the order of use during a research project.While these tips feature examples using the Microsoft Excel application, chosen deliberately because it is commonly used and is often the entry point software for data analysis, they are applicable to similar spreadsheet software programs.