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doi: 10.5281/zenodo.32500
REDI-Dropper: 0.0.3b Transferring data among disparate organizations can be a difficult challenge in clinical research. Adding to this difficulty the requirements of securing patient data yields an environment ripe for development of tools to assist investigators in conducting research. Open-source development using highly available languages such as Python can result in solutions tailored to meet the security demands while providing usability to the researcher. REDI-Dropper is a new, open source utility written using Python, Javascript and SQL which allows secure transfer of data among research entities. The data generated at an organization can often be of such a size as to restrict transfer over the internet and in some cases result in transfer via encrypted disks through physical mail. Although this method can work, it adds delays to the processing of data and results in such issues as encrypted data being spread across multiple file systems. Other proven technology such as secure file transfer protocol (SFTP) or RSYNC can accomplish reliable transfer of data of various sizes but it does not automatically create links to subjects and study data, nor does it enforce a naming standard among all parties for storing files. REDI-Dropper provides digital connections between research entities for large or small dataset transfer. REDI-Dropper is customizable to restrict access to relevant study investigators. It provides a secure web interface that is most often accessible even in restrictive hospital settings. REDI-Dropper is configurable to utilize study data stored in systems such as REDCap to create links between a study participant and their relevant research data. REDI-Dropper assists in the storage of subject research data by applying a defined method to add metadata to name subject files that is consistent and relevant. In this poster, we will describe the REDI-Dropper software, how it can be utilized, how it links study participants to their research data and how it is used to store files which are retrievable for further study processing.
https://www.flsenate.gov/Committees/BillSummaries/2014/html/838
Clinical Research, MRI, Python, Flask, File Storage
Clinical Research, MRI, Python, Flask, File Storage
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