|Title||Body||Technical Expertise Required||Cost||Additional Information|
|Decide what data to preserve|
The process of science generates a variety of products that are worthy of preservation. Researchers should consider all elements of the scientific process in deciding what to preserve:
When deciding on what data products to preserve, researchers should consider the costs of preserving data:
Researchers should consider the following goals and benefits of preservation:
|Identify data with long-term value|
As part of the data life cycle, research data will be contributed to a repository to support preservation and discovery. A research project may generate many different iterations of the same dataset - for example, the raw data from the instruments, as well as datasets which already include computational transformations of the data.
In order to focus resources and attention on these core datasets, the project team should define these core data assets as early in the process as possible, preferably at the conceptual stage and in the data management plan. It may be helpful to speak with your local data archivist or librarian in order to determine which datasets (or iterations of datasets) should be considered core, and which datasets should be discarded. These core datasets will be the basis for publications, and require thorough documentation and description.
Given the amount of data produced by scientific research, keeping everything is neither practical nor economically feasible.
|Store data with appropriate precision|
Data should not be entered with higher precision than they were collected in (e.g if a device collects data to 2dp, an Excel file should not present it to 5 dp). If the system stores data in higher precision, care needs to be taken when exporting to ASCII. E.g. calculation in excel will be done to the highest possible precision of the system, which is not related to the precision of the original data.