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. 2022 Jan 11;24(1):e25440.
doi: 10.2196/25440.

Understanding the Nature of Metadata: Systematic Review

Affiliations

Understanding the Nature of Metadata: Systematic Review

Hannes Ulrich et al. J Med Internet Res. .

Abstract

Background: Metadata are created to describe the corresponding data in a detailed and unambiguous way and is used for various applications in different research areas, for example, data identification and classification. However, a clear definition of metadata is crucial for further use. Unfortunately, extensive experience with the processing and management of metadata has shown that the term "metadata" and its use is not always unambiguous.

Objective: This study aimed to understand the definition of metadata and the challenges resulting from metadata reuse.

Methods: A systematic literature search was performed in this study following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for reporting on systematic reviews. Five research questions were identified to streamline the review process, addressing metadata characteristics, metadata standards, use cases, and problems encountered. This review was preceded by a harmonization process to achieve a general understanding of the terms used.

Results: The harmonization process resulted in a clear set of definitions for metadata processing focusing on data integration. The following literature review was conducted by 10 reviewers with different backgrounds and using the harmonized definitions. This study included 81 peer-reviewed papers from the last decade after applying various filtering steps to identify the most relevant papers. The 5 research questions could be answered, resulting in a broad overview of the standards, use cases, problems, and corresponding solutions for the application of metadata in different research areas.

Conclusions: Metadata can be a powerful tool for identifying, describing, and processing information, but its meaningful creation is costly and challenging. This review process uncovered many standards, use cases, problems, and solutions for dealing with metadata. The presented harmonized definitions and the new schema have the potential to improve the classification and generation of metadata by creating a shared understanding of metadata and its context.

Keywords: data classification; data identification; data integration; metadata; metadata definition; systematic review.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Reviewers' categorization of the tasks of a metadata-driven data integration process. Red: matching; yellow: mapping; and blue: transformation.
Figure 2
Figure 2
The process for literature selection in 2 search phases with different keyword sets. Two separate literature inquiries were performed: the first inquiry aimed at identifying suitable keywords for the second literature inquiry, which provided papers for the full-text analysis.
Figure 3
Figure 3
The distribution of the publications included in this review. The categories were letter-encoded: A is structural, B is descriptive, and C is administrative, as well as their resulting combination. Structural (40%) and descriptive (39%) papers were clearly in the majority, while administrative (14%) papers were rarely found. Lastly, 6% of the papers could not be clearly classified.
Figure 4
Figure 4
The building blocks of metadata: schema definition, metadata schema, and markup language are jointly used to instantiate metadata with an additional semantic descriptor to describe a real-world object.

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