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Data Management: Sharing Data

Resources and strategies for managing research data

Why Share Data?

Sharing data increases citation counts

Sharing data improves reproducibility

Shared data opens up the possibility of new collaborations

Data sharing is required by your funder, journal, etc.

Unicorn Data Sharing Video

Data Sharing Guidelines

A UWM guide on complying with data sharing mandates is available here.

Select list of funders with data sharing policies:

Select list of journals with data sharing policies:

How to Share Data

The best practice is to share data by placing it into a repository because you don't have to do any work after submission! Most repositories also have built-in methods for data citation and providing data permanence.

Here are some suggested repositories:

You can find other repositories listed by discipline at:

Also consider sharing your research code via Github or Google Code.

Preparing Data for Sharing

Plan to perform quality control and add documentation to your data prior to sharing either for a collaboration or publicly. These steps make it easier for someone to understand and use your data.

For tabular data, consider using OpenRefine for data clean up.

I recommended using README.txt's and data dictionaries to document shared datasets. You may also need to use a metadata schema, depending on where you share the data.

See also: Nine simple ways to make it easier to (re)use your data

More Information

The Data Services librarian position is currently vacant. You may direct your questions to the Scholarly Communication team at 

The content of this guide is available under a CC-BY license with attribution to UWM Libraries.