In the previous article, we explored the term metadata, its origin, and its relevance in the scientific as well as non-scientific community. In this article, we will dive into the types of metadata, developments and management of metadata standards, a few primary standards, and much more.
Types of metadata
The substantial growth in research and development (R&D) has led to a significant increase in data availability, resulting in a wider scope for metadata. With this varied scope in focus, the National Information Standards Organization (NISO) categorizes the metadata into four categories: (1) descriptive metadata, (2) administrative metadata, (3) structural metadata, and (4) markup languages. Figure 1 gives a classification of different metadata types.
Each of these categories supports different use cases of metadata. Among these types, the most commonly used metadata is descriptive metadata.
As described in the NISO publication [1], the descriptive metadata is used to find and understand a resource. For example, a document can be found using a combination of certain metadata such as the author’s name, data of creation, keywords, data of modifications, etc. These basic building blocks of any data describing it are descriptive metadata. For any digital object, one of the most significant elements of descriptive metadata is a unique identifier that exclusively identifies it [2].
While descriptive metadata simply describes a resource, administrative metadata provides technical details about the data (a resource or a file). Every technical aspect of a resource, including file size, file type, licensing, preservation, rights management, and much more, is clustered under the administrative metadata. Since the scope of this metadata type is so wide, it is further divided into technical metadata, preservation metadata, and rights metadata [1].
Technical metadata, as the name suggests, covers the technical details of a digital object, such as file type, file size, and other technical specifications, which are required to decode and render it. Preservation metadata, on the other hand, provides vital information necessary to preserve digital resources, such as version information. Rights metadata encompasses all aspects of intellectual property rights relating to content, including details of ownership and licensing. Structural metadata refers to the organization of a resource. For example, in a book, components such as a Table of Contents (TOC), Table of Figures, etc., form the structural metadata that helps us in navigating to the different chapters or figures of the book.
Lastly, markup languages, such as XML, HTML, RDF, etc., refer to the structured formats used to annotate, define, or organize metadata within digital content. These languages use tags or annotations to describe data, making it easier for machines to process and classify information systematically. A detailed description of the types of metadata is published by NISO in their NISO Primer Series of publications [1].
Figure 1: Types of metadata
It’s safe to say that we all have come across at least one of these types of metadata, and knowing the role or application of different types of metadata helps us better understand, discover, and navigate through the data.
Metadata Standards
The primary purpose of metadata is to enhance machine readability. It streamlines the process of searching for and locating data, evaluates its usefulness, defines accessibility, and supports data reusability. Ultimately, metadata plays a key role in making your data FAIR (Findable, Accessible, Interoperable, and Reusable). However, every metadata ever created is to be standardized to be utilized well. Without standardized metadata, data repositories risk inconsistency, redundancy, and inefficiencies, ultimately hindering seamless data sharing and retrieval. Therefore, metadata standards come into the picture. Metadata standards serve as the foundation for organizing, managing, and exchanging data across different systems and platforms.
A well-defined metadata standard ensures that data is described consistently, making it easier to locate, understand, and use. Several widely accepted metadata standards exist, each tailored to specific fields and applications. Dublin Core, for example, is a widely used standard in digital libraries and online repositories. It consists of fifteen fundamental elements designed to describe web resources and other digital objects effectively. Another important standard is ISO/IEC 11179, which provides guidelines for metadata registries and ensures consistent data semantics across different databases. Additionally, the Metadata Encoding and Transmission Standard (METS) is widely used in digital archiving, enabling the encoding of descriptive, administrative, and structural metadata within a single XML document. Similarly, the PRISM (Publishing Requirements for Industry Standard Metadata) standard is used extensively in the publishing industry to facilitate content syndication and data aggregation.
The following table gives an overview of a few metadata standards used widely across different disciplines [3], [4], [5], [6], [7], [8]:
| Metadata Standard | Discipline | Examples of Use |
| Dublin Core, DataCite Schema, RADAR | General, Libraries, Research Data | Citation management, digital repositories |
| MODS, EAD, TEI Lex-0 | Libraries, Archives, Literary Studies | Library catalogs, archival descriptions |
| Learning Object Metadata (LOM) Standard | Standard Educational technology and e-learning | Describes a Learning Object – any digital or non-digital entity used during technology supported learning |
| AgMES, FGDC-CSDGM, ISO 19115, CF Conventions | Agriculture, Environmental Science, GIS, Climate Science, Earth System Models | Spatial data management, land-use planning, geospatial services, Standardized climate data representation |
| INSPIRE | European GIS, Environmental Data | Standardized geographic data for EU compliance |
| CDWA, MIDAS-Heritage, VRA Core | Arts and Cultural Studies, Museums | Heritage site records, museum documentation, Describing images of art and artifacts |
| CIF, CSMD, Darwin Core, EML, ICAT Schema | Biology, Ecology, Crystallography | Biodiversity databases, ecological modelling |
| DDI (Data Documentation Initiative) | Social science, Demographic studies, Economic Sciences, and Health Sciences | Statistical surveys, demographic research |
| MatCore | Materials Science | Captures material properties data |
| MINSEQE | Genomics, Bioinformatics | Minimum standards for sequencing experiments |
| FITS (Flexible Image Transport System) | Astronomy | Standardized astronomical data storage |
| PREMIS (Preservation Metadata: Implementation Strategies) | Archiving, Digital Libraries | Long-term digital preservation strategies |
Several other disciplinary metadata standards can be found on various resources such as the Digital Curation Centre and RDA Metadata Standards Catalog.
Despite their advantages, implementing metadata standards comes with challenges. The complexity of some standards requires specialized expertise, making their adoption difficult for organizations without dedicated data management teams. Maintaining metadata consistency across different systems can also be resource-intensive, requiring continuous monitoring and updates. Moreover, as technology evolves, metadata standards must adapt to accommodate new data formats, storage methods, and user needs. This dynamic nature requires organizations to stay updated with emerging standards to ensure their metadata remains relevant and functional.
In an era where data is becoming increasingly important, the role of metadata standards cannot be overlooked. They provide a structured approach to the management of data, thereby ensuring that information remains accessible, interoperable, and usable over time. By adopting and adhering to appropriate metadata standards, organizations can significantly enhance the efficiency and longevity of their data management practices. As data continues to grow in volume and complexity, the importance of standardized metadata will only become more pronounced, reinforcing its role as a cornerstone of modern information systems.
