Objective(s): Data sharing has enormous potential to accelerate and improve the accuracy of research, strengthen collaborations, and restore trust in the clinical research enterprise. Nevertheless, there remains reluctancy to openly share raw data sets, in part due to concerns regarding research participant confidentiality and privacy. We provide an instructional video to describe a standardized de-identification framework that can be adapted and refined based on specific context and risks.
Data Description: Training video, presentation slides.
Related Resources: The data de-identification algorithm, dataset, and data dictionary that correspond with this training video are available through the Smart Triage sub-Dataverse. NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days.
Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on this page under "collaborate with the pediatric sepsis colab."
Note: Up to 1000 features for each file are displayed
Citation
APA Citation:
Mawji, A., Longstaff, H., Trawin, J., Komugisha, C., Novakowski, S. K., Wiens, M., Akech, S., Tagoola, A., Kissoon, N., & Ansermino, M. J. (2023). Open Data Training Video: A proposed data de-identification framework for clinical research [Data set]. UBC Dataverse. https://doi.org/10.5683/SP3/7XYZVC