Abstract

Scientific research is producing and consuming large volumes of multimedia data at an ever growing rate. Data annotations are used, among others, to provide context information and enhance content management, making it easier to interpret and share data. However, raw multimedia data often needs to go through complex processing steps before it can be consumed. During these transformation processes, original annotations from the production phase are often discarded or ignored, since their usefulness is usually limited to the first transformation step. New annotations must be made at each step, and associated with the final product, a time consuming task often carried out manually. The task of systematically associating new annotations to the result of each data transformation step is known as annotation propagation . This paper introduces techniques for structuring and propagating annotations, in parallel to the data transformation processes, thereby alleviating the overhead and decreasing the errors introduced by manual annotation. This helps the construction of new annotated multimedia data sets, preserving contextual information. The solution is based on: (i) the notion of semantic annotations; (ii) a set of transformations rules, based on ontological relations; and, (iii) workflows that deal with interrelated processing steps.

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