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Table 6 Lesson learned when connecting, enriching, and linking “big data” with survey data

From: Connecting and linking neurocognitive, digital phenotyping, physiologic, psychophysical, neuroimaging, genomic, & sensor data with survey data

Research challenge Solution(s) or idea(s)
Regulatory requirements • Involve legal, contracts, and procurements staff early in the process
• Be prepared to adjust system architecture and computing center environmental specifications
• Take advantage of U.S. funder (NIH) policies such as single IRB and Certificates of Confidentiality
• Adjust quality control processes and procedures for monitoring, reporting, and auditing
• Be prepared to limit data storage to select partners and data warehouses per DUAs
• Negotiate onerous terms and conditions that do not adhere to study design and Prime contractual requirements
Protocol complexities • Create an IMS that
Is data-driven
Is web-based
Enables adaptive sampling
Uses multiple linking identification schemas
Uses an agile approach that ensures participants and staff find the IMS user-friendly
Allows tailored event, incentive, reporting, and delivery routines and functionality
Is scalable and flexible enough to accommodate protocol modifications
Adheres to security, privacy, and compliance requirements
Multiple technology partners and/or platforms • Plan for differential DUAs and accompanying limitations and understand the implications for the protocol and architecture (e.g., monitoring, security reviews, level of access)
• Negotiate system boundaries by partner and platform; adjust if (and level of) system interconnections necessary to accomplish re linkage and data capture, status reporting, and delivery
• Budget appropriately to account for software, platform, and technological enhancements (e.g., new versions, downtimes, security changes) and how e-linkages between systems are affected (scalability and flexibility are key constructs)
• Ensure specific hardware/sensors, manufacturing and production schedules can achieve main protocol recruitment timelines, sharing/distribution of sensors, and implications on chain of custody and analysis
• Plan that participating laboratories often have existing LIMS with unique data linking requirements and may be outdated and separate from laboratory-to-laboratory
  1. Key research challenges and solutions and ideas we found useful when building such complex information management systems.