AbstractIn this paper, we present a novel approach to data collection for natural language processing (NLP), linguistic research and lexicographic work. Using the parlor game Fictionary as a framework, data can be crowd-sourced in a gamified manner, which carries the potential of faster, cheaper and better data when compared to traditional methods due to the engaging and competitive nature of the game. To improve data quality, the game includes a built-in review process where players review each other’s data and evaluate its quality. The paper proposes several games that can be used within this framework, and explains the value of the data generated by their use. These proposals include games that collect named entities along with their corresponding type tags, question-answer pairs, translation pairs and neologism, to name only a few. We are currently working on a digital platform that will host these games in Icelandic but wish to open the discussion around this topic and encourage other researchers to explore their own versions of the proposed games, all of which are language-independent.