Defining Big Data for Generalist Repositories

This white paper defines Big Data and its key characteristics, including volume, variety, velocity, and veracity. It explains that Generalist Repositories (GRs) are suitable for handling Big Data due to their data-agnostic nature and ability to store large, heterogeneous datasets. The document highlights the increasing importance of Big Data in research and the efforts of the NIH-funded Generalist Repository Ecosystem Initiative (GREI) to support its sharing and reuse. The document outlines specific features and challenges related to Big Data in GRs, such as storage size, file number, data updates, access methods, and interoperability with cloud platforms. It also addresses data packaging, metadata creation, moderated access, curation support, retention periods, and associated costs. The document provides links to additional GREI resources for repository comparisons and selection. It acknowledges the sources used to develop the definition of Big Data and the NIH funding support for this initiative.