Lesson: Preserve

Select a Best Practice below to learn more about the “Preserve” stage in the Data Life Cycle.

What is a Lesson?

Lessons are education materials publically available to support skillbuiliding of best data management practices. Lessons can include pdf and powerpoint slide decks, handouts, and supporting exercises and data that you can download and incorporate into your teaching materials. Materials are licensed as CC0 and you may enhance and reuse for your own purposes. In many cases slides can be previewed in the embedded slideshare viewer. We also provide one-page synopses (with space for contact information) that can be used to promote Data Management training events at your institution.

Please consider sharing your own data management teaching materials. For more information see our Frequently Asked Questions and Contributor Guidelines.

What is the “Preserve” stage?

Plan to preserve data in the short term to minimize potential losses (e.g., via accidents), and in the long term so that project stakeholders and others can access, interpret, and use the data in the future. Decide what data to preserve, where to preserve it, and what documentation needs to accompany the data. Map out the processes and resources for the entire Data Life Cycle.

More information can be found in the Best Practices Primer.

Why data management?


As rapidly changing technology enables researchers to collect large, complex datasets with relative ease, the need to effectively manage these data increases in kind. This is the first lesson in a series of education modules intended to provide a broad ... (click for more)

Tags: data management   DataONE teaching module

Data sharing


When first sharing research data, researchers often raise questions about the value, benefits, and mechanisms for sharing. Many stakeholders and interested parties, such as funding agencies, communities, other researchers, or members of the public may b... (click for more)

Tags: data management   data sharing   DataONE teaching module

Data quality control and assurance


Quality assurance and quality control are phrases used to describe activities that prevent errors from entering or staying in a data set. These activities ensure the quality of the data before it is collected, entered, or analyzed, as well as actively ... (click for more)

Tags: data management   QAQC   DataONE teaching module

Protecting your data


There are several important elements to digital preservation, including data protection, backup and archiving. In this lesson, these concepts are introduced and best practices are highlighted with case study examples of how things can go wrong. Explorin... (click for more)

Tags: data management   DataONE teaching module