The use of ontologies to annotate data is an established method for adding semantics to metadata, facilitating integration and richer querying. By creating a repository of annotations and their mapped ontology terms, and scoring their quality (curated, predicted etc), a "smart" annotation and search service was created: Zooma is a linked data repository of annotation knowledge, incorporating information from a variety of biological databases, providing an integrated resource that allows annotation searches and facilitates curation activities.
ZOOMA should be used for data that has been described with any series of keywords. It provides a mechanism to search for these keywords, using typing or context information or combinations of co-occuring keywords to improve accuracy, and automatically annotate data to ontology terms.
Using ZOOMA, it is trivially easy to automatically annotate any data that has been richly described previously. This improves the interoperability of data, but also frees up curators to work on more difficult and interesting tasks rather than spending time making the same old fixes and corrections to align data with the current state of the art in ontologies.
ZOOMA can be accessed through a REST-like API, a user interface and an endpoint for SPARQL querying. It provides a service that allows querying by plain text and returns possible annotations between matching properties and concepts identified by a URI. Zooma has been applied to multiple datasets during BioMedBridges and the content, design and ontology availability have all been extended.