Data Management Best Practices

The following are some best practices that should be considered prior to starting a data project and provide guidance for managing data in the Research Data Lifecycle's post-active research stage.

Data Storage

To prevent data from being lost to incompatibility, store it as formats and on hardware that are open standard, not proprietary.

Type of Data	Recommended Formats	Formats Acceptable
Plain Text	txt, pdf/A xml	docx, doc, rtf
Tabular Text	csv, tsv	xlsx, xls, sav, dta
Image	tiff, JPEF2000	jpg, psd, png, gif, bmp
Audio	wave, aiff	mp3, wma, aac, ogg
Archiving	zip	rar
Video	motion jpg 2000, mov, avi	mpeg-4

Data Documentation

In your documentation, use metadata to record details about the data collection process (e.g., a study) such as:

• its context

• the dates of data collections

• data collection methods, etc.

Sharing

Sharing data makes it possible for researchers to validate research results and to reuse data for teaching and further research. Sharing is also required by an increasing number of funders and publishers. Funders seek to maximize the impact of the research they fund by encouraging or requiring data sharing.

Depositing to an established repository will help to ensure that data are consistently available and accessible, and preserved for future use. Choosing a data repository can be determined by various factors, such as discipline, accepted data format, data sharing policies and etc. You can obtain assistance from Data Services to identify a repository to publish your research data.

Subject/Discipline	Example Archive/Repository
Ecology	Dryad
DNA Sequences	GenBank
Chemistry	Cambridge Crystallographic Data Centre
Social Sciences	ICPSR