facettihaku

Facettihaku, or faceted search, is a search technique that allows users to refine results by filtering on multiple facets derived from item metadata. Each facet represents a category such as author, year of publication, language, subject, format, or collection. The interface presents facet values with counts, and selecting one or more values narrows the result set. Facets can also include ranges (for example dates or prices) and can be hierarchical to represent subcategories. The facet counts update dynamically to reflect the remaining results, guiding further exploration.

Implementation typically relies on a metadata schema (for example Dublin Core, MARC, or schema.org) and a search index capable of faceted counting, such as Apache Solr, Elasticsearch, or other engines. Facet values are built from indexing rules, often stored as keyword or numeric fields. Some systems support pivot or hierarchical facets to show aggregates across multiple levels. Users can combine multiple facets, with varying semantics such as AND for multiple selections or OR for alternative options, and they can clear selections to return to broader results.

Facettihaku is common in digital libraries, archives, museums, and e-commerce platforms, where it enhances discovery by letting users progressively narrow large result sets without composing complex queries. Benefits include faster navigation, better discovery of serendipitous items, and more intuitive filtering. Challenges include providing balanced facet sets, avoiding overwhelming users with too many options, ensuring facet values are well maintained in metadata, and maintaining performance for large catalogs.