This paper presents an ontology created for classifying and researching material culture and its visual representations, that forms a part of an emerging data-driven research framework on Neoclassicism (ca. 1760-1860). The framework, named Neoclassica, unites a topdown approach to knowledge discovery, represented by the Neoclassicaontology, with innovative methods and techniques for processing multimodal data corresponding with a bottom-up approach. Below we will first describe the Neoclassica framework, discussing the epistemological considerations related with it. Second, we outline the basic objectives of the ontology and explore differences to existing thesauri, as well as relationships with existing standards (CIDOC-CRM). Third, we will give an overview of the most important classes currently provided by the ontology and illustrate the features of the multilingual approach and the descriptive power already inherent to the ontology. Finally, we will give an outlook on the next steps for developing the Neoclassica framework.
We build on the results of our MARIO project to support the benefit of informing research taking place in the area of development of human consciousness models for use by robots to facilitate human robot interaction with research results from the area of collaborative systems. The main outcome of such a research would be a software model of a robot assistant that might offer functionality and features of a 'virtual coach' with an in-built evolution capability.
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