There exist today a multitude of biological databases containing a wide array of information regarding different species including specimens in museum databases, occurrence information, genome sequence and expression data and image data to name a few. A common feature of these databases is that the information normally corresponds to a particular species (or taxa) and therefore the databases tend to employ some taxonomy to structure the information and access the data. However as yet there is no common taxonomy which is used across these databases to enable reliable linking across the databases. Matching species across databases is challenging. Different databases can and do use different classifications which use different names to represent the same underlying species or taxa. Tools that aid integration of data from these sources will be of benefit to biologists allowing them to incorporate additional data into their analyses and ensure the quality of the data and the accuracy of results are improved. The utility of visualising data is well established for tasks such as presentation of information. Visualisations are effective for a range of other tasks such as acting as ad-hoc error-checks for data e.g. spotting a record of a lion placed in the middle of the Pacific Ocean in a geographical information visualisation plot clearly suggests an error in the data. However, the true advantage of visualisation isn't in static presentation but in allowing users to interactively explore and view the effects of changes to constraints and variables, although suitable tools are frequently not available to biologists where they could be most useful. This project will build on the biological standards developed for taxonomic information and develop a set of web-based visualisation tools for use by a wide range of biologists and end-users of these databases to support them clean, explore and compare the data contained within. The resulting tools will have a wide ranging impact on the quality of data made available and the accessibility of the data to a wide range of users.