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The ImageCLEF 2013 Scalable Concept Image Annotation Subtask was the second edition of a challenge aimed at developing more scalable image annotation systems. Unlike traditional image annotation challenges, which rely on a set of manually annotated images as training data for each concept, the participants were only allowed to use auto- matically gathered web data instead. The main objective of the challenge was to focus not only on the image annotation algorithms developed by the participants, where given an input image and a set of concepts they were asked to decide which of them were present in the image and which ones were not, but also on the scalability of their systems, such that the concepts to detect were not exactly the same between the development and test sets. The participants were provided with web data consisting of 250,000 images, which included textual features obtained from the web pages on which the images appeared, as well as various visual features extracted from the images themselves. To evaluate the performance of the submitted systems a development set was provided containing 1,000 images that were manually annotated for 95 concepts and a test set con- taining 2,000 images that were annotated for 116 concepts. In total 13 teams participated, submitting a total of 58 runs, most of which signif- icantly outperformed the baseline system for both the development and test sets, including for the test concepts not present in the development set and thus clearly demonstrating potential for scalability.