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Enhancing Traceability in Clinical Research Data through a Metadata Framework
Background The clinical research data lifecycle, from data collection to analysis results, functions in silos that restrict traceability. Traceability is a requirement for regulated clinical research studies and an important attribute of nonregulated studies. Current clinical research software tools provide limited metadata traceability capabilities and are unable to query variables across all phases of the data lifecycle.
Objectives To develop a metadata traceability framework that can help query and visualize traceability metadata, identify traceability gaps, and validate metadata traceability to improve data lineage and reproducibility within clinical research studies.
Methods This research follows the design science research paradigm where the objective is to create and evaluate an information technology (IT) artifact that explicitly addresses an organizational problem or opportunity. The implementation and evaluation of the IT artifact demonstrate the feasibility of both the design process and the final designed product.
Results We present Trace-XML, a metadata traceability framework that extends standard clinical research metadata models and adapts graph traversal algorithms to provide clinical research study traceability queries, validation, and visualization. Trace-XML was evaluated using analytical and qualitative methods. The analytical methods show that Trace-XML accurately and completely assesses metadata traceability within a clinical research study. A qualitative study used thematic analysis of interview data to show that Trace-XML adds utility to a researcher's ability to evaluate metadata traceability within a study.
Conclusion Trace-XML benefits include features that (1) identify traceability gaps in clinical study metadata, (2) validate metadata traceability within a clinical study, and (3) query and visualize traceability metadata. The key themes that emerged from the qualitative evaluation affirm that Trace-XML adds utility to the task of creating and assessing end-to-end clinical research study traceability.
Keywordsmetadata - data quality - biomedical research - standards - clinical study report - design science research
The [Dakota State University] University Institutional Review Board, chaired by Jack H. Walters, PhD, granted expedited approval (#2016–2016–114) to conduct this research with human subjects.
Received: 27 March 2020
Accepted: 09 June 2020
07 September 2020 (online)
© 2020. Thieme. All rights reserved.
Georg Thieme Verlag KG
Stuttgart · New York
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