In 2020, more researchers than ever found themselves teleworking. With standard tools, not being in the lab might sharply limit the type of analytical work they can do. Flywheel, a modern cloud-based research data platform, supports remote workflows with secure access to data and cloud computation. Flywheel helps researchers perform remote analyses, write papers, and plan future experiments. Our modern approach to data and computational management helps our customers carry out essential research efficiently even when working remotely.
“Now more than ever, when our in-person research is interrupted and we are collaborating remotely, our ability to quickly access a shared set of data in Flywheel is a huge benefit to our research community. Flywheel provides us with a platform so we can continue to support our researchers across the university and they can remain highly productive in driving important research studies forward,”
— Dr. Jonas Kaplan, Co-Director of the Dornsife Neuroimaging Center
Shared Remote Access
Flywheel is a cloud-based research data platform that makes study data and clinical data easily accessible to all contributors. Users may build automated pre-processing pipelines and set custom de-identification rules that run once data is collected, protecting privacy and making all data analysis-ready.
Before the enormous advances in cloud computing, researchers might have to log in to a remote computer system and make a local copy of the data. It would be complex to preserve the full value of the curated Flywheel data and metadata on a local copy, including organized tags and measurement parameters. If two or more people are working on the project together, each with their own local copy, differences and errors will creep in that will limit the reproducibility of the analyses. To work on shared datasets in Flywheel, users simply log in to the secure web interface with their institutional credentials. Flywheel gives users a HIPAA and IRB compliant tool that allows them to work with the complete data and metadata collaboratively and reproducibly with colleagues who are also working remotely.
Backing up data on home systems also presents a security concern. Sensitive medical data must be carefully stored by healthcare professionals to reduce the risk of data leaks. As a SOC 2 certified organization, Flywheel provides remote access to a secure system that ensures data privacy, confidentiality and processing integrity.
Exploratory Development and Analysis
Flywheel’s computational management allows researchers to securely use conventional algorithms or develop original algorithms while working remotely.
Researchers can perform analyses on the cloud, including over 70 plug-in algorithms (called Gears) in the Flywheel Gear Exchange or privately-shared Gears on a user’s instance of Flywheel. Gears may be run on-demand for a given dataset or in batch mode for a selected collection of datasets. Flywheel’s comprehensive provenance captures all analytical derivative information to support the consistency and reproducibility of your project. If you are developing your own algorithms, you can use the Python SDK, MATLAB SDK, or command-line interface to read and analyze data and metadata from Flywheel and store your analyses in the Flywheel system.
Flywheel’s built-in image viewers also support remote work, making it possible to see the results of different analyses either as images or through quantitative graphical plotting methods. The results of the remote analyses can be downloaded and inserted in reports and publications.
To learn more about Flywheel’s research data management platform and how it supports working remotely, please click to schedule a demo.