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Because most experimental annotations are best provided by the researcher(s) who conducted the experiments, and it is unlikely that bench biologists would have had the time to become power users of several ontologies, we wanted to provide an easier method to use ontologies that would be rapid and require no expert knowledge of the ontology. For example, the NCBI Taxonomy might be used to describe the organism used as the source of the biological sample being studied, while an anatomy ontology might be used to describe the tissue that was sampled.

However, in the process of annotating a single investigation, a researcher might require several large and complex ontologies. Using biomedical ontologies to annotate experimental designs, experimental variables and biological samples helps to achieve consistency, to provide the opportunity for complex searches and to allow computational access to the annotations.

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Deploying the OntologyWidget can be accomplished in three simple steps: (1) install Apache Tomcat on one's web server, (2) download and install the OntologyWidget servlet stub that provides access to the SMD ontology web services, and (3) create an html (HyperText Markup Language) file that refers to the OntologyWidget using a simple, well-defined format.Īlthough there are many potential applications, we developed OntologyWidget to help microarray researchers use ontologies and controlled vocabularies to describe and annotate their experiments.

Adopters of the OntologyWidget can either use SMD's web services, or elect to rely on their own. We have implemented web services at the Stanford Microarray Database (SMD), which provide the OntologyWidget with access to over 40 ontologies from the Open Biological Ontology (OBO) website. The ontology browser shows the paths from a selected term to the root as well as parent/child tree hierarchies. Upon selection of a term from the list, the user can locate this term within a generic and dynamic ontology browser, which comprises the second element of the tool.

As a user enters characters into the search box, the appropriate ontology is queried remotely for terms that match the typed-in text, and the query results populate a drop-down list with all potential matches. The first is a dynamic auto-complete ontology search feature. OntologyWidget is written using AJAX (Asynchronous JavaScript and XML) and has two related elements. OntologyWidget can easily be embedded in other web-based applications. We have produced a tool, OntologyWidget, which allows users to rapidly search for and browse ontology terms.

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