Translational Cancer Research Data Quality – The Context Factor
2017-08
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
Translational Cancer Research Data Quality – The Context Factor
Authors
Published Date
2017-08
Publisher
Type
Thesis or Dissertation
Abstract
Cronbach’s alpha indicates that as the count of items in a set increases, so does the level of relationship between them. Translational cancer research (TCR) data is an example of increasing items within a set. As a national priority, TRC is well-funded contributing to continued increase in data organizations produce, the number of organizations producing data, and the amount of sharing in which each organization participates. However, rather than leveraging the data relationships – a contextual approach – intrinsic measures such as accuracy and completeness remain referenced most often in data quality (DQ) articles and conceptual frameworks. The purpose of this set of studies is to expand our knowledge of TCR data quality (DQ) by examining context-sensitive DQ methods. The knowledge gained could be incorporated into future TCR DQ efforts, leading to more informative and actionable data, and quicker development of better clinical treatments.
Description
University of Minnesota Ph.D. dissertation. August 2017. Major: Health Informatics. Advisor: Stuart Speedie. 1 computer file (PDF); vi, 80 pages.
Related to
Replaces
License
Collections
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Other identifiers
Suggested citation
Orreggio, Giordi. (2017). Translational Cancer Research Data Quality – The Context Factor. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/191477.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.