Optimal curation of human diseases requires an ontology or structured vocabulary that contains terms familiar to end users, is robust enough to support multiple levels of annotation granularity, is limited to disease terms and is stable enough to avoid extensive reannotation following updates. At Mouse Genome Informatics (MGI), we currently use disease terms from Online Mendelian Inheritance in...

Learning visual concepts is an important tool for automatic annotation and visual querying of networked multimedia databases. It allows the user to express queries in his own vocabulary instead of the computer’s vocabulary. This paper gives an overview of our current research directions in learning visual concepts for use in our online visual webcrawler, ImageScape. We discuss using the Kullbac...

The Gene Ontology (GO [5]) is a dynamic controlled vocabulary [6] that details the biological processes, molecular functions and cellular components of a generic cell. The UniProt-Gene Ontology Annotation (UniProt-GOA [7]) project uses GO to describe proteins in UniProtKB [8]. The project has assigned GO terms to all complete and incomplete proteomes that exist in UniProtKB, using a combination...

This paper presents the LSLink (or Life Science Link) methodology that provides users with a set of tools to explore the rich Web of interconnected and annotated objects in multiple repositories, and to identify meaningful associations. Consider a physical link between objects in two repositories, where each of the objects is annotated with controlled vocabulary (CV) terms from two ontologies. ...

Applications that use annotated multimedia assets need to be able to process all the annotations about a specific media asset. At first sight, this seems almost trivial, but annotations are needed for different levels of description, these need to be related to each other in the appropriate way and, in particular on the Semantic Web, annotations may not all be stored in the same place. We disti...

In this survey, we argue that using structured vocabularies is capital to the success of image annotation. We analyze literature on image annotation uses and user needs, and we stress the need for automatic annotation. We briefly expose the difficulties posed to machines for this task and how it relates to controlled vocabularies. We survey contributions in the field showing how structures are ...

This study was a qualitative exploration of the effect of multiple-choice glosses and periodic second language (L2) text reconstruction on lexical acquisition. L2 readers of German engaged in a think-aloud procedure while reading a short text and retelling its content in German after each of four short sections. In each section, four unfamiliar target words (TWs) were embedded. Half of the part...

Sixty-eight college students enrolled in a French course listened to a multimedia-based French passage in one of four groups to which they were randomly assigned: the listening text (a) alone, with no annotations; (b) in pairs, with no annotations; (c) alone, with written and pictorial annotations; and (d) in pairs, with written and pictorial annotations. The students identified or recalled voc...

Ontologies play an increasingly important role in annotation, integration, and analysis of biomedical data. In this paper, we describe the design and development of a PostTraumatic Stress Disorder (PTSD) Ontology and how we can use this ontology as a controlled vocabulary for supporting automatic annotation of clinical text. The automated annotation is performed using a natural language process...