Towards a content agnostic computable knowledge repository for data quality assessment.

BACKGROUND AND OBJECTIVE: In recent years, several data quality conceptual frameworks have been proposed across the Data Quality and Information Quality domains towards assessment of quality of data. These frameworks are diverse, varying from simple lists of concepts to complex ontological and taxonomical representations of data quality concepts. The goal of this study is to design, develop and implement a platform agnostic computable data quality knowledge repository for data quality assessments. METHODS: We identified computable data quality concepts by performing a comprehensive literature review of articles indexed in three major bibliographic data sources. From this corpus, we extracted data quality concepts, their definitions, applicable measures, their computability and identified conceptual relationships. We used these relationships to design and develop a data quality meta-model and implemented it in a quality knowledge repository. RESULTS: We identified three primitives for programmatically performing data quality assessments: data quality concept, its definition, its measure or rule for data quality assessment, and their associations. We modeled a computable data quality meta-data repository and extended this framework to adapt, store, retrieve and automate assessment of other existing data quality assessment models. CONCLUSION: We identified research gaps in data quality literature towards automating data quality assessments methods. In this process, we designed, developed and implemented a computable data quality knowledge repository for assessing quality and characterizing data in health data repositories. We leverage this knowledge repository in a service-oriented architecture to perform scalable and reproducible framework for data quality assessments in disparate biomedical data sources.

Patterns and Perceptions of Asynchronous Video Discussion in a Graduate Health Sciences Course.

BACKGROUND: Studies of graduate online education indicate a need for increased interaction among students and faculty. However, it can be challenging to foster a high level of scholarly interaction and engagement in fully online courses. The objective of this study was to evaluate student perceptions and participation patterns related to online, asynchronous video discussion in a graduate health sciences course. METHOD: An asynchronous video discussion was piloted in a 2014 interprofessional informatics course and students were subsequently surveyed to determine their perceptions of this approach. Participation patterns were analyzed using descriptive statistics and social network analysis. RESULTS: The results indicate broad and inclusive interaction among students and faculty, with discussion characteristics perceived as equivalent to, or better than, traditional classroom discussion. The quality of student participation was high, and students spent additional time researching and preparing their contributions. CONCLUSION: This format for a seminar-style discussion holds good potential for effective teaching and learning in online graduate-level health courses and supports the development of students' critical thinking and scholarly communication skills. [J Nurs Educ. 2016;55(12):706-710.].