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An intelligent linked data quality dashboard
Vaidyambath, Ramneesh; Debattista, Jeremy; Srivatsa, Neha; Brennan, Rob
This paper describes a new intelligent, data-driven dashboard for linked data quality assessment. The development goal was to assist data quality engineers to interpret data quality problems found when evaluating a dataset us-ing a metrics-based data quality assessment. This required construction of a graph linking the problematic things identified in the data, the assessment metrics and the source data. This context and supporting user interfaces help the user to un-derstand data quality problems. An analysis widget also helped the user identify the root cause multiple problems. This supported the user in identification and prioritization of the problems that need to be fixed and to improve data quality. The dashboard was shown to be useful for users to clean data. A user evaluation was performed with both expert and novice data quality engineers.
Keyword(s): Linked Data; Data Quality Analysis; Root Cause Analysis
Publication Date:
2019
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Vaidyambath, Ramneesh, Debattista, Jeremy ORCID: 0000-0002-5592-8936 <https://orcid.org/0000-0002-5592-8936>, Srivatsa, Neha and Brennan, Rob ORCID: 0000-0001-8236-362X <https://orcid.org/0000-0001-8236-362X> (2019) An intelligent linked data quality dashboard. In: AICS 27th AIAI Irish Conference on Artificial Intelligence and Cognitive Science., 5-6 Sept 2019, Galway, Ireland.
Publisher(s): CEUR-WS
File Format(s): application/pdf
Related Link(s): http://doras.dcu.ie/24121/1/AICSDashboardv02-cameraReady.pdf,
http://aics2019.datascienceinstitute.ie/papers/aics_32.pdf
First Indexed: 2020-01-11 06:05:42 Last Updated: 2020-01-11 06:05:42