While research on reasoning using large models is in the spotlight, a symbolic method of making a compact model capable of reasoning is also attracting public attention. We introduce the Mini-ARC dataset, a 5x5 compact version of the Abstraction and Reasoning Corpus (ARC) to measure the abductive reasoning capability. The dataset is small but creative, which maintains the difficulty of the original dataset but improves usability for model training. Along with Mini-ARC, we introduce the O2ARC interface, which includes richer features for humans to solve the ARC tasks. By solving Mini-ARC with O2ARC, we collect human trajectories called Mini-ARC traces, which are potentially helpful in developing an AI with reasoning capability.