Semantic Mappings

The term semantic mapping as applied to metadataData about data. Metadata provides a context for research findings, ideally in a machine-readable format. It enables discovery of data via an electronic interface, and correct use and attribution of findings. Related Guide is a visual or tabular strategy for establishing the relationshipsConnections between metadata terms within a vocabulary. These relationships can connect terms by scope, provenance, or other well-defined criteria. of vocabulary termsA potential metadata value that is part of a set intended to restrict the available options in a particular metadata element. between data sets.

Basic Relationships

When creating mappings among vocabularyA set of terms (e.g., words) that are used in a specific community. Related Guide terms, the mapping organization requires a good set of basic relationships. The most common relationship, “is the same as,” is usually too narrow to adequately map all terms.

The following basic relationships have been taken from the Simple Knowledge Organization System's (SKOSSimple Knowledge Organization System ) Mapping Vocabulary Specification. They offer the ability to distinguish subtle relationships between two terms.

The URIUniform Resource Identifier name for each term is shown in brackets, after the labelA descriptor for a metadata value. This can be thought of as a question to which the value is providing an answer. For example, for the metadata label "date", the metadata value could be "March 16, 2008". of the term.

has-exact-match [exactMatch]
     If two concepts are an exact match, then the set of resources properly indexed against the first concept is identical to 
     the set of resources properly indexed against the second. 
     Therefore, the two concepts may be interchanged in queries and subject-based indexes. (Is inverse with itself.)


has-broad-match [broadMatch]
     If ”concept A has-broad-match concept B,” then the set of resources properly indexed against concept 
     A is a subset of the set of resources properly indexed against concept B.
     (Is inverse of has-narrow-match.)

has-narrow-match [narrowMatch]
     If “concept A has-narrow-match concept B,” then the set of resources properly indexed against concept 
     A is a superset of the set of resources properly indexed against concept B. 
     (Is inverse of has-broad-match.)

has-major-match [majorMatch]
     If “concept A has-major-match concept B,” then the set of resources properly indexed against concept 
     A shares more than 50% of its members with the set of resources properly indexed against concept B. 
     (No inverse relation can be inferred.)

has-minor-match [minorMatch]
     If “concept A has-minor-match concept B,” then the set of resources properly indexed against concept 
     A shares less than 50% but greater than 0 of its members with the set of resources properly indexed against concept B. 
     (No inverse relation can be inferred.)

Diagram and Discussion of Relationships

The diagram below shows these relations graphically (click for full view).

Broad and narrow. Be careful using has-broad-match and has-narrow-match, as they may, at first, be counterintuitive. If A has-broad-match B, this means (roughly speaking) that B is broader than A, and so A is smaller than B. Since the two relationships, has-broad-match and has-narrow-match, are the inverse of each other, A has-broad-match B also implies B has-narrow-match A (B is broader than A).

The concepts, has-major-match and has-minor-match, do not have an inverse relationship, as shown in the fourth example in the diagram. It is true that A has-minor-match B (because 1 relation mapping to concept A also maps to concept B, but 3 other relations of concept A do not map to column B, so only 1/4=25% of the relations mapping to concept A also map to concept B). But it is also true that B has-minor-match A, because only 1 out of 3 of B's relations also map to A.

A similar example could be constructed with has-major-match, where most of the relations in A can be mapped to B, and vice-versa. If both concepts have a has-major-match relation with the other, then the concepts are highly overlapping. If both concepts have a has-minor-match relation, then the concepts overlap a little bit. Finally, if A has-major-match B and B has-minor-match A, as shown in the third of the four examples, then the A can be considered mostly, but not entirely, a minor subset or part of B.

Unambiguous Web Reference

The generalized terms for these basic relationships, such as “has-broad-match,” are often used within tools or scripts that perform semantic mappingsIn the context of crosswalking, elements in the source schema are explicitly mapped to elements in the target schema during semantic mapping. Related Guide. When using a simple tool like Excel, these relationship terms are sufficient. However, as you begin using your mappings with semantic WebThe transformation of the web from an inherently human-interpretable medium to an inherently computer-interpretable medium. In the semantic web, machines can read and understand the content published in the network. tools and software, it is important to specify relationships in a universally understood syntax.

The Simple Knowledge Organization System (SKOS) Mapping Vocabulary Specification provides a syntax for distributing semantic mapping relationships over the Web. To represent the mapping relationship as a URI (Uniform Resource Identifier), add the prefix "http://www.w3.org/2004/02/skos/mapping#" to the name shown in brackets above. For example, use http://www.w3.org/2004/02/skos/mapping#narrowMatch to represent a has-narrow-match relationship. URI representation will allow your mapping to be incorporated in the Semantic Web.

Applying the Terms

Deciding whether one thing is the same as another thing in a particular context may not be straightforward. For example, if one data set has measurements of "water temperature" that were all taken at the surface of the ocean, and another data set uses "sea surface temperature," is that an exact match or a broad match? The answer may depend on the context, including the purposes and intended application of the relationships being created. Regardless of context, if the SKOS terms are chosen, a strict application of the definitions should be followed.

In general, developers should use mappings that are accurate in as wide a context as possible, even when considered by someone outside the system, the specific scientific domain, or the broader domain of environmental sciences. The more generally applicable the mappings, the more they can be used by others.

The basic relationship terms above are well defined and understood, and they can be used in a variety of tools and contexts. They provide a basic set of uniquely referenceable relationship terms for use in mapping vocabulary terms.

However, developers may also map data in a limited context with customized relationships defined to convey specific meanings, or they may wish to add other relationships that are specified in a project-specific dictionaryIn the context of metadata, a dictionary is a type of controlled flat vocabulary, which provides a list of metadata terms, definitions and additional information within a specific domain. Related Guide of terms or in another standardA set of documented rules which define the creation of metadata by providing a combination of terminology (vocabularies), syntactical rules, format rules, and other requirements. Metadata standards are approved, published and governed by a formal body or organization with broad community-based representation (international or national). Related Guide vocabulary. By using unique Web references for a project’s relationship vocabulary, such extensions can be easily created.

Additional Resources

Contact MMI or search in these pages for more information about defining and serving vocabulary terms. The MMI guidance document, "What is 'Same As'?,” was created for the MMI vocabulary mappingDocuments that map metadata terms between different controlled vocabularies. Related Guide workshop. It provides more information on defining and using mapping relationships and discusses some of the challenges and pitfalls involved in mapping terms in the real world. Contact MMI and review other guides in the MMI site for more information.