Assessing Data Quality: An Approach and An Application

2021 ◽  
pp. 1-24
Author(s):  
Kelly McMann ◽  
Daniel Pemstein ◽  
Brigitte Seim ◽  
Jan Teorell ◽  
Staffan Lindberg
Keyword(s):  
Data Quality ◽  
Quality Assessment ◽  
Convergent Validity ◽  
Assessment Tools ◽  
Generation Process ◽  
Data Generation ◽  
Validity And Reliability ◽  
Advantages And Disadvantages ◽  
Data Quality Assessment ◽  
Assessment Approach

Abstract Political scientists routinely face the challenge of assessing the quality (validity and reliability) of measures in order to use them in substantive research. While stand-alone assessment tools exist, researchers rarely combine them comprehensively. Further, while a large literature informs data producers, data consumers lack guidance on how to assess existing measures for use in substantive research. We delineate a three-component practical approach to data quality assessment that integrates complementary multimethod tools to assess: (1) content validity; (2) the validity and reliability of the data generation process; and (3) convergent validity. We apply our quality assessment approach to the corruption measures from the Varieties of Democracy (V-Dem) project, both illustrating our rubric and unearthing several quality advantages and disadvantages of the V-Dem measures, compared to other existing measures of corruption.

scholarly journals An integrated system for data quality and conditions assessment for the ATLAS Tile Calorimeter

2019 ◽  
Vol 214 ◽  
pp. 01030
Author(s):  
Juraj Smiesko
Keyword(s):  
Data Quality ◽  
Quality Assessment ◽  
Virtual Machine ◽  
Web Applications ◽  
Web Server ◽  
Integrated System ◽  
Assessment Tools ◽  
Web Interface ◽  
Data Quality Assessment ◽  
Quality Tools

An integrated system for data quality and conditions assessment for the ATLAS Tile Calorimeter is known amongst the ATLAS Tile Calorimeter as the Tile-in-One. It is a platform for combining all of the ATLAS Tile Calorimeter offline data quality tools in one unified web interface. It achieves this by using simple main web server to serve as central hub and group of small web applications called plugins, which provide the data quality assessment tools. Every plugin runs in its own virtual machine in order to prevent interference between the plugins and also to increase stability of the platform.

Acoustic data quality assessment tools and findings for ocean observing systems

2016 ◽  
Vol 140 (4) ◽  
pp. 3410-3410 ◽  
Author(s):  
Thomas Dakin ◽  
John Dorocicz ◽  
Ben Biffard ◽  
Nathan D. Merchant ◽  
David Hannay ◽  
...  
Keyword(s):  
Data Quality ◽  
Quality Assessment ◽  
Assessment Tools ◽  
Acoustic Data ◽  
Data Quality Assessment ◽  
Ocean Observing ◽  
Ocean Observing Systems ◽  
Observing Systems

Applying Domain Knowledge for Data Quality Assessment in Dermatology

2017 ◽  
pp. 147-156
Author(s):  
Nemanja Igić ◽  
Branko Terzić ◽  
Milan Matić ◽  
Vladimir Ivančević ◽  
Ivan Luković
Keyword(s):  
Data Quality ◽  
Quality Assessment ◽  
Domain Knowledge ◽  
Data Quality Assessment

scholarly journals Evaluation of a staff training programme to reimplement a comprehensive health assessment

2018 ◽  
Vol 7 (4) ◽  
pp. e000353 ◽  
Author(s):  
Luke A Turcotte ◽  
Jake Tran ◽  
Joshua Moralejo ◽  
Nancy Curtin-Telegdi ◽  
Leslie Eckel ◽  
...  
Keyword(s):  
Data Quality ◽  
Quality Assessment ◽  
Health Information ◽  
Health Assessment ◽  
Training Programme ◽  
Care Planning ◽  
Assessment Framework ◽  
High Quality ◽  
Data Quality Assessment ◽  
Comprehensive Health

BackgroundHealth information systems with applications in patient care planning and decision support depend on high-quality data. A postacute care hospital in Ontario, Canada, conducted data quality assessment and focus group interviews to guide the development of a cross-disciplinary training programme to reimplement the Resident Assessment Instrument–Minimum Data Set (RAI-MDS) 2.0 comprehensive health assessment into the hospital’s clinical workflows.MethodsA hospital-level data quality assessment framework based on time series comparisons against an aggregate of Ontario postacute care hospitals was used to identify areas of concern. Focus groups were used to evaluate assessment practices and the use of health information in care planning and clinical decision support. The data quality assessment and focus groups were repeated to evaluate the effectiveness of the training programme.ResultsInitial data quality assessment and focus group indicated that knowledge, practice and cultural barriers prevented both the collection and use of high-quality clinical data. Following the implementation of the training, there was an improvement in both data quality and the culture surrounding the RAI-MDS 2.0 assessment.ConclusionsIt is important for facilities to evaluate the quality of their health information to ensure that it is suitable for decision-making purposes. This study demonstrates the use of a data quality assessment framework that can be applied for quality improvement planning.

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