Assessing metadata is of paramount importance for several critical reasons. Metadata plays a pivotal role in various aspects, including data retrieval and search, data organization, interoperability, data preservation, and the overall user experience. The purpose of this scoping review is to identify the most commonly measured dimensions of metadata quality in existing studies on metadata quality assessment. The study also investigates the types of data sources and countries contributing most to the literature on metadata quality assessment and the types of documents used to communicate their findings. The methodology involves the application of PRISMA model for qualitatively evaluating 55 studies on metadata quality assessment. The co-occurrence analysis is made on the title and abstract of selected articles using VOSviewer 1.6.18 version, visualization software. The review found that completeness, accuracy, consistency, accessibility, conformance, provenance, and timeliness are commonly used dimensions in metadata quality assessment. However, there is no consensus on their exact definition and measurement, indicating a need for further investigation into less commonly assessed quality dimensions. Digital repositories and open government data are the most commonly studied data sources, with the United States being the leading contributor and journal articles being the most commonly used document type. The cluster analysis based on co-occurrence of terms in title and abstract found three research areas, “Metadata Quality Assessment,” “Metadata Quality Dimensions,” and “Metadata Quality Applications, Frameworks, and Approaches” as prominent areas of research. The originality of the study lies in its methodology that involves rigorous screening of articles on metadata quality. It is a first attempt to qualitatively synthesize literature on metadata quality. The article emphasizes the importance of metadata quality research and the need to improve the flexibility of metadata quality assessment tools to facilitate better metadata quality assurance measures.
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