Ten simple rules for improving research data discovery

• Published in: PLoS computational biology Vol. 18; no. 2; p. e1009768
• Main Authors: Contaxis, Nicole, Clark, Jason, Dellureficio, Anthony, Gonzales, Sara, Mannheimer, Sara, Oxley, Peter R., Ratajeski, Melissa A., Surkis, Alisa, Yarnell, Amy M., Yee, Michelle, Holmes, Kristi
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.02.2022; Public Library of Science (PLoS)
• Subjects: Computer and Information Sciences; Computer Security; Consent; Datasets; Ecology and Environmental Sciences; Engineering and Technology; Ethics; Gene expression; General Data Protection Regulation; Genome-wide association studies; Genomes; Genotypes; Human subjects; Humans; Information professionals; Information sharing; Information Storage and Retrieval; Medicine and Health Sciences; Metadata; People and Places; Phenotypes; Professional ethics; Regulations; Values; Visibility; United States; United States > US
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1009768

Regulations provide some direction when considering ethical practices for data discovery, but ethics should be considered as an active discussion over the course of a project in order to accomplish the work in accordance with your values as well as in compliance with regulations in your country and in your field. [...]it will be beneficial to consider your own values and ethical codes when pursuing newer practices like data publishing, discovery, and reuse, which may introduce new concerns not yet represented in regulations and guidelines [21–23]. [...]the Gene Expression Omnibus (GEO) database and the database of Genotypes and Phenotypes (dbGaP) are clear choices for depositing gene expression data and genome-wide association study (GWAS) data, respectively, for high visibility. Other researchers looking for gene expression data will know to go to GEO, making it discoverable to the relevant research community.