Articlecentric

Articlecentric is a term used to describe a content architecture or strategy that treats articles as the primary unit of information around which a system is built. In an article-centric design, data models, navigation, and workflows center on individual articles rather than pages, documents, or authors. The term is used in digital publishing, knowledge management, and content platforms to emphasize modular, reusable units of content.

In practice, article-centric systems model content as discrete articles with persistent identifiers. Each article carries metadata such as title, author, publication date, topics, and keywords, and may include sections, figures, and citations. Relationships to related articles, authors, topics, and versions are captured explicitly to enable cross-linking, recommendations, and provenance.

Applications include online journals, encyclopedic portals, learning management and corporate knowledge bases, and research databases. An article-centric approach supports reuse of components, precise search by article-level metadata, and stable citations even as individual elements evolve. Benefits include improved content reuse, consistent attribution, and enhanced discoverability. Challenges involve migrating from page- or document-centric models, defining a coherent taxonomy, ensuring performance for large article graphs, and establishing governance for metadata quality.

Related concepts include content management, metadata standards, knowledge graphs, and article-based indexing. The term remains flexible in practice, sometimes expressed as article-centric, article-centric architecture, or article-centric design, depending on the context and domain.