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

DNA Sequences

Chemistry

Social Sciences

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