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Psychology: Managing your research data

Data repositories

You can search for subject-specific repositories on the Registry of Research Data Repositories

Those listed below are the most popular.

Data management tools

Research Data Oxford tools, services, and-training

Here you will find a list of useful tools for data management from both Oxford and external providers.

What is data management?

What is Research Data Management?

All research projects will generate data in one form or another. Good data management practices will help you organise, store and retrieve data for use during your project and after it is completed. You can find out more about the principles behind data management on the Research Data Management website.

Working with data

There are a number of practical activities and considerations involved in day-to-day management of research data. You can find out more about the different aspects of working with data using the links below:

 

Preservation

Storing your data in suitable formats and under suitable conditions helps ensure that it can be viewed and built upon by future generations of researchers. Find out more about preserving your research data here.

 

Sharing data

There are various legal and ethical issues you might need to think about before sharing your research data with others. Also, it's important to get credit for your data by having it cited correctly. You can find out more information about sharing data on the links below:

 

Tools, services and training

There are a variety of tools and services which can support you with different aspects of managing your research data, from developing your data management plan to storing you data in an online repository. The University also offers a range of training to help you manage your data effectively. You can find more information here.

Citing data

As datasets become more widely shared and recognised as an important part of research output, there is more of a need to ensure that data can be reliably cited in publications. This ensures that:

  1. Datasets referred to in a publication can be identified easily and unambiguously
  2. Creators of data are properly acknowledged and credited for their work

A dataset can be cited in a similar way to how you would cite any other kind of source in a bibliography, although it may need to include extra details such as the version of a dataset you are referring to or what portion of data you are referencing from a larger dataset.

The Digital Curation Centre provides an excellent guide to citing datasets.

Case studies

Examples of how data management principles have been applied to research in psychological science.

Background reading for data management

 

      Additional information can be found on the companion website.

Training

 

Contacts

If you have any enquiries about data management at Oxford University, e-mail the data management team.

Alternatively, you can contact your Subject Librarian for assistance.