Data Management

What is research data?

Universities have many definitions of "research data". The USC Research - Academic Policy uses the following:

Data are facts, observations, computer results, measurements or experiences upon which an argument, theory or research publications is based.
Data may be numerical, descriptive, visual, raw, analysed, experimental or observational.
Data includes assays, test results, transcripts, laboratory and field notes and data recorded in any media which can be used to produce research outputs.

Research data may also include provenance information about the data, such as how, when or where it was collected, and with what (for example, instrument). It may also include the software code used to generate, annotate or analyse the data.

Why should research data be managed?

Planning for your data management needs at the start of your project will save you time and resources in the long run.

Preserve your data: Damaged drives, new operating systems and upgraded software can render your data useless, while you still need it.
Increase your research efficiency: Have you ever had a hard time understanding the data that you or your colleagues have collected? Documenting your data throughout its life cycle saves time because it ensures that in the future you and others will be able to understand and use it.
Document and explain your data: Managing and documenting your data throughout its life cycle ensures that the integrity and proper description of your data are maintained.
Meet grant requirements: Many funding agencies and journal publishers now require that researchers retain and properly archive data which they collect as part of a research project. Some also require that the data is made accessible externally.

Consider the following

Before, during and after your project, you should be thinking about your data and how you are storing it, the format you are storing it in, and any long term preservation implications...

Before you start your project:

Does someone already have the data that you want?
Where will you store the material you find in your environmental scan/literature review?
What volume of data will you be generating?
What form will the data be in?
Is there a particular format or tool that needs to be used?
Is there any data storage charges?
Does the data need to be securely stored for confidentiality?
Will the data need to be shared - either within USC or externally?
What are you going to do with the data in the future?
If you wish to share your data, do you need to get the appropriate ethics clearances before you begin?
In a cooperative activity, is an agreement about the future of the research data required?

During the project:

Your data should be backed up regularly, with one backup stored at a separate location.
How can you migrate your data to new software versions if you upgrade?
How will you manage version control in your data?
Do you have consistent file naming protocols?
Do you have metadata and descriptors for your data files?
Is a key for coding required?
Does the data need to be password protected for security and privacy issues?

After your project completion:

What is the retention period for your data as specified by your grant, sponsor or funding body?
Are there any data requirements for potential publication?
Is there an agreed archiving practice if the project was a joint cooperative?
Who "owns" the research data?
Are there any ethics agreements that relate to privacy or sharing of the data?
Are there any intellectual property or licensing agreements that relate to the sharing of the data?
What are the long-term storage implications?
Can you maintain appropriate versioning for progressive software upgrades?
Who manages the dataset?
Who has access to the data when you leave USC?
What disposal and destruction strategy is in place for your data?

Data Sharing and Management

A data management horror story by Karen Hanson, Alisa Surkis and Karen Yacobucci. This is what shouldn't happen when a researcher makes a data sharing request! Topics include storage, documentation, and file formats.

Further Resources for Data Management

ANDS: Australian National Data Service

The Australian National Data Service (ANDS) has a Data Management Planning guide, that will be of particular interest to researchers and research administrators who are charged with preparing a data management plan for a research project.

ANDS Data Management Planning

MANTRA: Research Data Management Training

Research Data MANTRA is a free online course designed for PhD students and others who are planning a research project using digital data. Designed by the University of Edinburgh, it covers all aspects of data management from plans, file formats, documentation, storage, and preservation.

Research Data MANTRA Online Course