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We propose a patterns-based approach to evaluating data visualization: a set of general and reusable solutions to commonly occurring problems in evaluating tools, techniques, and systems for visual sensemaking. Patterns have had significant impact in a wide array of disciplines, particularly software engineering, and we believe that they provide a powerful lens for looking at visualization evaluation by offering practical, tried-and-tested tips and tricks that can be adopted immediately. The 12 patterns presented here have also been added to a freely editable Wiki repository. The motivation for creating this evaluation pattern language is to (a) disseminate hard-won experience on visualization evaluation to researchers and practitioners alike; to (b) provide a standardized vocabulary for designing visualization evaluation; and to (c) invite the community to add new evaluation patterns to a growing repository of patterns.