multiidentifier

A multiidentifier is a concept in data management that refers to the use of multiple identifiers to refer to or locate a single entity across different systems, databases, or domains. It arises when a single reference is insufficient for reliable identification due to fragmented data, varying naming conventions, privacy constraints, or changing identifiers over time. The approach supports more robust entity matching, data integration, and cross-system analytics by maintaining several linked identifiers for the same real-world object.

Identifiers commonly involved include natural keys (such as emails or usernames), surrogate keys (internal IDs or UUIDs), and external identifiers (DOIs, ISBNs, ORCID IDs, vendor-specific IDs). In practice, organizations may also maintain composite or canonical identifiers that combine multiple references to improve disambiguation and traceability across contexts.

Architecture and patterns often associated with multiidentifiers include:

- Identity resolution and matching to determine when different identifiers refer to the same entity.

- Crosswalks or mapping tables that link related identifiers across systems.

- Canonical identity models that assign a single master identifier while preserving local IDs.

- Federated identity management to enable controlled access and attribution across domains.

Benefits of adopting a multiidentifier approach include improved data fidelity across systems, better support for data integration and consolidation, and enhanced analytics through richer linkage. Challenges include increased system complexity, potential performance considerations, governance and data-quality requirements, and privacy or security concerns when handling multiple identifiers.

See also: identity resolution, entity resolution, master data management, data integration.