Towards a semantic store of data mining models and experiments

Semantic annotation provides machine readable structure to the stored data. We can use this structure to perform semantic querying, based on explicitly and implicitly derived information. In this paper, we focus on the approaches in semantic annotation, storage and querying in the context of data mining models and experiments. Having semantically annotated data mining models and experiments with terms from domain ontologies and vocabularies will enable researchers to verify, reproduce, and reuse the produced artefacts and with that improve the current research. Here, we first provide an overview of state-of-the-art approaches in the area of semantic web, data mining domain ontologies and vocabularies, experiment databases, representation of data mining models and experiments, and annotation frameworks. Next, we critically discuss the presented state-of-the-art. Further-more, we sketch our proposal for an ontology-based system for semantic annotation, storage, and querying of data mining models and experiments. Finally, we conclude the paper with a summary and future work.