Metadata Interoperability Part 1

Interoperability refers to the ability of various systems to interact with one another. There are two fundamental forms of interoperability: semantic and syntactic. Semantic interoperability refers to the compatibility of the meanings assigned to the metadata elements of a schema, such as whether or not the term "author" in one schema corresponds in meaning with the term "creator" in another schema. Different applications, databases, and institutions may result in disparate meanings to the same terms or utilize distinct terms to express the same meaning (Gruninger & Kopena, 2005). Syntactic interoperability refers to the ability to extract and use metadata from other systems, requiring the use of a common language or encoding format. In general, metadata interoperability commonly refers to search interoperability, the ability to process various metadata records and retrieve desired results.

Differences in the semantics and syntax of metadata schemas usually cause difficulties in retrieving desired materials. The greater the dissimilarities, the more problematic the retrieval process can become. In terms of semantic differences, there is a wide range of possible variation and misinterpretation in meanings. For example, when comparing two schemas, one schema may require a more precise or well-defined set of rules in determining the meaning of a particular element than the other. For instance, the Dublic Core schema considers the Title element to be any name given to the resource whereas AARC2/MARC follows a strict set of guidelines when assigning what should be considered the Title Proper (Caplan, 2003, p. 41). As a result, there can be various degrees of misinterpretation between the two records. An even more obvious discrepancy would be if one record did not provide a corresponding element at all.


References

Caplan, P. (2003). Metadata fundamentals for all libraries. Chicago: American Library Association.

Gruninger, M., & Kopena, J.B. (2005). Semantic integration through invariants. AI Magazine, 26(1), 11-21. Retrieved May 20, 2008, from InfoTrac OneFile database.