Advancements in computing, data storage, and network infrastructure are helping researchers to make sense of data on a previously unthinkable scale.
Some have called these computational possibilities a new "paradigm" in research. The terms eScience and "cyberinfrastructure" are often used to describe these new capabilities.
Several fields of research have embraced the research benefits of making data more discoverable to other scientists and open for re-use. Large scale examples of intensive data sharing include:
At the conclusion of a research project, researchers often report findings in journal articles, book chapters, conference papers, or other forms of scholarly communication. They many not thinking about the ongoing usefulness of their data.
Preserving data for long-term use and referral serves several purposes (as noted by the Digital Curation Centre):
Johns Hopkins has a simple diagram showing the stages of data management both during and after a project is completed.
Whether a researcher intends to share their data broadly or not, there are several things that he or she can do to make sure that data is well prepared for long-term storage. Some data practices researchers can explore:
[INCOMPLETE: LIST IS STILL BEING DEVELOPED]
This list contains data repositories with a brief description, including the related discipline(s). Some of these repositories accept research dataset submissions from all researchers, while others require institutional affiliation for archiving your data.