Choosing a journal appears simple until a researcher actually tries to do it.
A journal may match the manuscript's subject but not its article type. Another may be indexed in one database but absent from another. Publication charges, review timelines and open-access policies introduce additional considerations.
The result is an information problem.
Instead of treating journal discovery as a directory search, modern systems can treat it as structured data matching.
A manuscript's subject, keywords, references and article type can potentially be compared with a journal's publishing history, indexing status, scope and metadata.
Better journal discovery may therefore emerge not from larger journal lists but from better connected publishing data.
