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LORIS: API development and documentation

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Status:
Completed
Contributor/Mentors

Simon Pelletier 
Christine Rogers

About

“LORIS (Longitudinal Online Research and Imaging System), a web-based data and project management software for neuroimaging research studies”

( https://mcin.ca/technology/loris/ ). It is a very convenient tool for researchers conducting neuroimaging research studies, or any clinical studies that involves multiple costly measurements (especially longitudinal studies), are often statistically underpowered because of the difficulty to get data from enough subjects ( e.g. because of the difficulty to recruit subjects, the measurements are very time consuming or subjects are dropping from the study). The obvious solution to increase the datasets’ size is to collect data from multiple sites, but using data with multiple sources needs a very high level of care to make the data collected compatible. Subjects in clinical studies can have a high degree of variability, so every detail must be tracked with caution in an effort to explain this variability. Additionally, multi-center studies involve a high number of people, which alsoincreases variability.

Another major contribution of LORIS is to make data available to researchers that wish to conduct neuroimaging research downstream of data collection. Indeed, neuroscience is very interdisciplinary ( e.g. psychology, medicine, biology, bioinformatics, statistics, machine learning) and not all researchers involved in the process should have to collect their own data to do what they do best. As a computer scientist and neurobiologist, I have been on both sides of this research cycle. From my experience, it is common for researchers to collect their own data to answer a very specific question, when the data from other studies might have been adequate to answer the question if it had it open sourced data. Thus, LORIS should help to reduce useless redundancy of studies, or at least put them together to make better studies.

The REST API is an easy way to securely access, retrieve and manipulate the sensitive data about the subjects stored in LORIS. This data contained in Loris should be easily accessible to the researchers allowed to use it, but such information is very personal to the subjects, so the security of these actions on Loris’ database is of foremost importance for ensuring the subjects confidentiality. The REST API is already a work in progress, so I will be implementing endpoints for the modules not already accessible via the API.

Deliverables

Implement endpoints for LORIS modules not already accessible via the REST API to make data available to researchers while protecting the privacy of subjects