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Computational creativity is broadly defined as the study of building software which exhibits behaviour that would be deemed creative if exhibited by a person. In more practical terms, we investigate how to engineer software that takes on some of the creative responsibility in arts and science projects which produce culturally interesting artefacts such as poems, theorems, paintings, melodies, etc. To this end, there are numerous examples of creative software being employed in musical composition, visual arts, pure mathematics , natural language generation, scientific discovery, video game design, and many more areas of discourse. Moreover, the computational creativity community is beginning to come to consensus on some of the thorny research questions that have arisen, such as: which AI processes are more suited to generative applications; how can we measure levels of creativity in software; and what roles can software have in creative acts? Our contributions to computational creativity research have revolved around our two pieces of research software: the HR system [2] and The Painting Fool (www.thepaintingfool.com). The former is mathematical theory formation software which can start with the bare minimum about a domain of pure mathematics, such as how to divide one number by another, and end with a rich theory of concepts, conjectures, theorems and proofs. The latter is an automated painter which we hope will one day be taken seriously as a creative artist in its own right. The majority of software developed by computational creativity researchers – including our own – is given domain knowledge only about its specific area of application. For instance, our HR software is given enough background information about domains of pure mathematics to enable it to invent concepts in those particular domains, but it is not given wider mathematical knowledge and is certainly not provided with information outside the sphere of pure mathematics. This is largely acceptable in domains where there are objective measures of value with which we can assess the artefacts produced by the creative systems. However, we argue in [3] that in certain domains (most noticeably the visual arts), the creativity and intelligence of the creator is taken into account when assessing the value of the artefacts that he/she/it produces. In particular, in such domains, the cultural awareness of the artist may well be questioned when people assess the value of their work. In these situations, there is much need for the kind of knowledge stored in ontologies, …

Towards Ontology Use, Re-use and Abuse in a Computational Creativity Collective - A Position Statement