Numerous efforts are being made to store descriptive morphological data in databases.
However, these efforts are often hampered by the tremendous complexity of the subject.
Many projects are therefore abandoned prematurely because funding expires. An improved solution for morphological data would support mapping complex data and 212 make them as easily accessible to the human mind as possible, as well as enabling cooperation of people who possibly live and work far apart. Topic maps, an ISO-standardized semantic technology, might meet these requirements. They are networks of topics connected by multiple and flexibly assignable associations.
Topic maps holding corresponding topics can be fused. Hypothetically, it would be
possible to construct a topic map containing data about all life on earth. Topic maps can be generated from common structured data sources such as spread sheet data or databases.
MyxoMap, a topic map on the morphology of myxogastrids, is used to demonstrate the advantages of the topic maps approach. It can be used as a synoptic key for determination of species. Furthermore, the associative structure enables a multiplicity of views promising new ways of data analysis.