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A specialized variation of associations for biodiversity data is defined and developed that makes the capture and discovery of information about biological images easier and more efficient. Biodiversity is the study of the diversity of plants and animals within a given region. Storing, understanding, and retrieving biodiversity data is a complex problem. Biodiversity experts disagree on the structure and the basic ontologies. Much of the knowledge on this subject is contained in private collections, paper notebooks, and the minds biologists. Collaboration among scientists is still problematic because of the logistics involved in sharing collections. This research adds value to image repositories by collecting and publishing semantically rich user specified associations among images and other objects. Current database and annotation techniques rely on structured data sets and ontologies to make storing, associating, and retrieving data efficient and reliable. A problem with biodiversity data is that the information is usually stored as ad-hoc text associated with non-standardized schemas and ontologies. This research developed a method that allows the storage of ad-hoc semantic associations through a complex relationship of working sets, phylogenetic character states, and image annotations. MorphBank is a collaborative research project supported by an NSF BDI grant (0446224 - $2,249,530.00) titled "Web Image Database Technology for Comparative Morphology and Biodiversity Research". MorphBank is an on-line museum-quality collection of biological images that facilitates the collaboration of biologists from around the world. This research proves the viability of using association semantics through annotations of biodiversity informatics for storing and discovery of new information.