We present OntoDT, a generic ontology for the representation of scientific knowledge about datatypes. OntoDT defines basic entities, such as datatype, properties of datatypes, specifications, characterizing operations, and a datatype taxonomy. We demonstrate the utility of OntoDT on several use cases. OntoDT was used within an Ontology of core data mining entities for constructing taxonomies of datasets, data mining tasks, generalizations and data mining algorithms. Furthermore, we show how OntoDT can be used to annotate and query dataset repositories. We also show how OntoDT can improve the representation of datatypes in the BioXSD exchange format for basic bio-informatics types of data. The generic nature of OntoDT enables it to support a wide range of other applications, especially in combination with other domain specific ontologies: the construction of data mining workflows, annotation of software and algorithms, semantic annotation of scientific articles, etc. OntoDT is open source and is available at http://www.ontodt.comTest. European Commission through the projects: MAESTRA Learning from Massive, Incompletely annotated, and Structured data (grantnumberFP7-ICT-612944) and HBP–The Human Brain Project (grantnumberFP7-ICT-604102). Engineering and Physical Sciences Research Council UK (grant number EP/K030469/1)
