Numerous Earth and Environmental Science ontologies exist in various repositories that are useful to DataONE, for data access and delivery, and for data sharing. These ontologies can be used to enhance metadata annotations of each dataset, thus improving metadata quality overall. However, Earth and Environmental Science ontologies have very different degrees of quality and curation. As DataONE is poised as the main point of access to earth and environmental data and practices and is schema agnostic, semantic descriptions of these datasets and practices are crucial to discovery across schemas. One way to ascertain this degree of quality is to locate terms with similar semantics between two or more ontologies and, based on their annotations and surrounding concepts in the ontologies, have domain users assess the comparative quality. The scope of this task includes providing backend mappings to be used by automated assistance to the users in the form of semantically similar terms from different ontologies for the same domain. The ideal candidate will have a background in computer or information science and should be familiar with ontological concepts and possibly the application of algorithms to provide mappings. Expected outcomes may include the development of software prototype, a final report, or material for publication of results at a conference on earth and environmental sciences.