Translational research data are generated in multiple research domains from the bedside to experimental laboratories. These data are typically stored in heterogeneous databases, held by segregated research domains, and described with inconsistent terminologies. Such inconsistency and fragmentation of data significantly impedes the efficiency of tracking and analyzing human-centered records. To address this problem, we have developed a data repository and management system named TraM (http://tram.uchicago.edu), based on a domain ontology integrated entity relationship model. The TraM system has the flexibility to recruit dynamically evolving domain concepts and the ability to support data integration for a broad range of translational research. The web-based application interfaces of TraM allow curators to improve data quality and provide robust and user-friendly cross-domain query functions. In its current stage, TraM relies on a semi-automated mechanism to standardize and restructure source data for data integration and thus does not support real-time data application.
