Schema Vocabularies and Value Vocabularies

There are different types of controlled vocabularies for information and knowledge management. Usually, we think of the various kinds of controlled vocabularies for purposes of tagging and finding information, such as term lists, authority files, thesauri, and taxonomies. In the broader context of information and knowledge management, there also exist higher-level controlled vocabularies called schema vocabularies. In this context, the better known (default) controlled vocabularies comprising specific concepts or terms for tagging content are called value vocabularies, since their terms/concepts are considered values.

This dichotomy of schema and value vocabularies occurs particularly within the context of metadata. Metadata management comprises two components: (1) a list of metadata types, also called elements, properties, or fields; and (2) the terms or values possible for each metadata element. I discussed types of metadata in more detail in my last blog post, "Types of Metadata Schema." Thus, a schema vocabulary comprises the names of metadata elements, and a value vocabulary is list of terms/concepts for a specific metadata element. For example, a schema vocabulary, might include Country, Language, Source, and Topic; and the multiple values vocabularies would be the lists of approved countries, languages, sources, and topics. Not all schema vocabulary elements have a corresponding value vocabulary (controlled vocabulary), though, as some metadata elements may be for such values as title, description, and date.

In my observation, we speak of “vocabularies” rather than “controlled vocabularies” in this context, especially with respect to schema, for various reasons. Schema vocabularies are referred to simply as “vocabularies,” rather than “controlled vocabularies,” because they are not traditional controlled vocabularies used for tagging, and also because their “control” is different from the control of value vocabularies. Value vocabularies can be changed but through defined policies and procedures, which depend on the implementation and ownership, and changes can be frequent, e.g. weekly, monthly, quarterly, or annually. Schema vocabularies, on the other hand, are intended to be standard, and are updated only very infrequently, such as once per 5-10 years, and usually by a standards body. Schema vocabularies provide control by their very nature. Meanwhile, it is often necessary to call out the controlled feature of value vocabularies, since some metadata properties may have uncontrolled keywords as their values.

Schema vocabularies may be metadata schema, such as Dublin Core (for published resources) or IPTC metadata (for photos), but other kinds of information and content management schema can also be considered as schema vocabularies in that a “vocabulary” defines the various elements. Such other schema vocabularies include SKOS (Simple Knowledge Organization System), DITA (Darwin Information Typing Architecture), DCAT (Data Catalog Vocabulary), and iiRDS (intelligent information Request and Delivery Standard), among others. These were ones that our panel “Using Schema and Value Vocabularies to Provide Consistency Across Structured Content” addressed at the DCMI (Dublin Core Metadata Initiative)conference in Barcelona, October 22 – 25. Other speakers were Joseph Busch, who had the idea of this topic for a conference panel, Lief Erickson, Noz Urbina, and Peter Winstanley.

DCMI 2025 Panel: "Schema and Value Vocabularies for Consistency"

My presentation the DCMI panel, was "Schema and Value Vocabularies for Thesauri and Taxonomies," which explained that SKOS is a schema vocabulary, and specific SKOS-based taxonomies and thesauri are value vocabularies. SKOS (Simple Knowledge Organization System) is the W3C data model schema for knowledge organization systems, especially taxonomies and thesauri. It can also be considered a schema vocabulary, because it has standard elements with defined display names and machine-readable concatenated forms. In fact, the designation “elements” is what is used in the SKOS model. SKOS, however, is a special kind of schema vocabulary, and it’s not a metadata schema. When SKOS-based taxonomies or thesauri serve as the value vocabularies for metadata elements, those metadata elements are managed as specific SKOS Concept Schemes. In a faceted taxonomy, each Concept Scheme serves as a facet.

Taxonomists don’t usually think of vocabularies being classified as either "schema vocabularies" or "value vocabularies." However, as taxonomies have increasingly been integrated with metadata and serve purposes beyond just browsing, searching and retrieving content, it’s important to see the bigger picture of where taxonomies as value vocabularies fit in, and where taxonomies can provide more benefits.