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PLEASE NOTE: Throughout this page and most research data management literature, "sensitive data" is used as a blanket term to broadly apply to any data that may be sensitive, confidential, or private. This does not mean that all data under the sensitive data umbrella is truly sensitive. Please consult with the Office of Research Ethics to determine the level of sensitivity of your data if you are unsure.
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Working with Sensitive Data at the University of Waterloo
What is Sensitive Data?
Sensitive data is information that must be safeguarded against unwarranted access or disclosure. Sensitive data includes any information relating to an identified or identifiable natural person, organization or entity and may include:
- Personal information
- Personal health information
- Educational records
- Customer records
- Financial information
- Criminal information
- Geographic information
Resources for University of Waterloo Research
- Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans – TCPS 2 (2022)Comprehensive instruction for the ethical conduct of research involving humans, geared toward Canadian researchers in Canada and abroad.
- Resources and guides for Indigenous ResearchWaterloo adheres to many different principles for conducting distinctions-based research in partnership with Indigenous communities including the principles of ownership, control, access, and possession (OCAP™).
Human Participant Data
- Guideline for researchers on securing research participants' dataOutlines how to secure research data. This guideline applies to all research involving human participants conducted by or under the auspices of University of Waterloo faculty, students, other affiliated researchers (investigators).
- Guideline on retention of human participant study information and dataCovers considerations for retaining human participant information/data for a research project. This guideline applies to all research involving human participants conducted by or under the auspices of University of Waterloo faculty, students, and other affiliated researchers (investigators).
Learning Resources
- Part 1: Glossary of terms for sensitive data used for research purposesDefinitions for common terms used for discussing sensitive data management in the Canadian context.
- Part 2: Human participant research data risk matrixRisk matrix tool to help researchers determine risk level for human participant research data, and make decisions with respect to its management, deposit, and appropriate access/future. Use with glossary from Part 1 of the toolkit.
- Part 3: Research data management language for informed consentTemplate language tool that can be applied to the development of tailored, deposit-friendly language for ethics approval and informed consent documents/forms.
- De-identification Guidelines for Structured DataGuidelines for the de-identification of data from the Information and Privacy Commissioner of Ontario.
Data Anonymization & De-identification
Developed by McGill University, this online Data Anonymization Workshop Series focuses on topics related to both quantitative and qualitative data. It is presented by national and international subject matter leading experts.
Working with quantitative data
- Reducing risk: An introduction to data anonymizationSensitive data, risk of re-identification and common techniques for anonymization and de-identification with quantitative data.
- ARX - Anonymising data in theory and practiceHands-on practical workshop on Open-Source, NIST recommended and internationally recognized anonymization tool (ARX) for quantitative data.
Working with qualitative data
- Ethically sharing qualitative dataIntroduction to data de-identification best practices for qualitative data to enable ethical sharing.
- Qualitative data sharing: A roadmap and resources to facilitate responsible and ethical data sharingIntroduction to data de-identification support tool (QDS Toolkit) for qualitative data using nature language processing pipeline for de-identifying text-based research materials.