Evaluating a Conversational Agent for Open Government Data Quality Assessment

Governments have been publishing Open Government Data (OGD) on online portals to encourage the development of value-added services. The success of these services depends heavily on the quality of OGD and its metadata. Several methods have been proposed to evaluate this quality, but some rely on manual assessments, which can be time-consuming and expensive to perform. Furthermore, these methods focus on the portal rather than the data, ignore user preferences, or do not distinguish between metadata and data quality. This makes it difficult for users to identify data quality issues. This paper proposes a list of OGD quality dimensions for assessing data and metadata quality. The dimensions were identified through a literature review and integrated into a novel conversational agent that incorporates user preferences into the quality assessment. A usability evaluation with 14 users reveals its ease of use and usefulness for obtaining overall and detailed (meta)data quality.