Research from psychology, neurobiology and behavioral economics indicates that a binary view of motivation, based on approach and avoidance, may be too reductive. Instead, a literature review suggests that at least seven distinct motives are likely to affect human decisions: "consumption/resource seeking," "care," "affiliation," "achievement," "status-power," "threat approach" (or anger), and "threat avoidance" (or fear). To explore the conceptual distinctness and relatedness of these motives, we conducted a semantic categorization task. Here, participants were to assign provided words to one of the motives. By applying principal component analysis to the categorization assignments we represent the semantic inter-relations of these motives on a two-dimensional space, a "semantic atlas." This atlas suggests that, while care and affiliation are conceptually close, affiliation is closer to threat avoidance (or fear); opposite to these motives we find achievement, consumption and power, with the latter lying closer to threat approach (or anger). In a second study, we asked participants to rate how well the motive-specific words obtained in the first study described their currently experienced feelings. We find that semantically close motives are also more likely to be experienced together, that is, we replicate most of the semantic relations in the "subjective atlas." We discuss our findings in comparison to other multi-dimensional models of motivation, which show clear similarities. In addition to these motivational atlases, we provide a database of motive-specific words, together with the valence and arousal scores. These can be used for future research on the influence of motives on decision making.