Find or collect data
On this page
- What is a data management plan
- Funder requirements
- Data management plan tools & examples
- Find data
- Collect data ethically
- Research with Indigenous communities
- File formats
- File naming, organization, versioning
- Document & describe
- Storage & backup
- Analyze & visualize data
- Prepare data for archiving, sharing
- Where to share data
- Data licenses
- Cite data
Collect data ethically
Confidentiality of human subjects
If your research involves human subjects, you need to comply to the Concordia Policy for the Ethical Review of Research Involving Humans (VPRGS-3). To learn more, please consult Concordia's research ethics policies and procedures.
When managing research data dealing with human subjects, the confidentiality of your respondents is paramount. Start thinking about preserving confidentiality at the outset of your research project as well how best to share your data at its conclusion.
Things to consider:
- Consent forms: Devise your consent form with data confidentiality and data sharing in mind. These need not be contradictory.
- De-identification or anonymization: Determine if you will need to de-identify or anonymize your dataset before sharing it. These procedures can be time-consuming and may necessitate an appropriate budget.
- Sharing data: Consider where (in what data repository) you will store your data at the end of your research project; this choice should be informed by the type of confidentiality review and access control options offered by that repository. For help, see the Tri-Council's Guidance on Depositing Existing Data in Public Repositories
- Human Participant Research Data Risk Matrix: helps researchers determine risk level for human participant research data, and make decisions with respect to its management, deposit, and appropriate access/future use.
Sensitive data can be ethically shared within the research community provided that adequate measures are taken. Make sure not to write your consent form in a way that would impose unnecessary limitations on how your data can be reused. It is usually very difficult or even impossible to retroactively obtain consent to share data.
Things to consider:
- Confidentiality: The consent form should explain to the participants how you will maintain the confidentiality of their records.
- Data collection: Participants should be informed of the exact type of data that will be collected and the purpose of the data collection.
- Data sharing: If you plan to share your data this should be made explicit; you should specify who will have access to the dataset and for what purpose.
- Data destruction: Do not commit to destroying your dataset unless this is deemed necessary.
- Example language for informed consent: for research involving sensitive data (Portage)
- Sample consent forms for sensitive data (Concordia's Centre for Oral History and Digital Storytelling)
- Consent for data sharing: Provides consent procedures for specific research contexts, methods, nature of the data (personal, sensitive, level of detail), data format (surveys, written, recordings) and planned data uses. (UK Data Service)
Collecting sensitive data
Consider using tools that are designed for securely collecting sensitive data. For example, REDCap is a secure web application for building and managing online surveys and databases. It can be used to collect virtually any type of data.
Learn about preparing sensitive data for sharing.