There are several issues to be addressed concerning the management and effective use of information (or data), generated from nanotechnology studies in biomedical research and medicine. These data are large in volume, diverse in content, and are beset with gaps and ambiguities in the description and characterization of nanomaterials. In this work, we have reviewed three areas of nanomedicine informatics: information resources; taxonomies, controlled vocabularies, and ontologies; and information standards. Informatics methods and standards in each of these areas are critical for enabling collaboration, data sharing, unambiguous representation and interpretation of data, semantic (meaningful) search and integration of data; and for ensuring data quality, reliability, and reproducibility. In particular, we have considered four types of information standards in this review, which are standard characterization protocols, common terminology standards, minimum information standards, and standard data communication (exchange) formats. Currently, due to gaps and ambiguities in the data, it is also difficult to apply computational methods and machine learning techniques to analyze, interpret and recognize patterns in data that are high dimensional in nature, and also to relate variations in nanomaterial properties to variations in their chemical composition, synthesis, characterization protocols, etc. Progress towards resolving the issues of information management in nanomedicine using informatics methods and standards discussed in this review will be essential to the rapidly growing field of nanomedicine informatics.