The Promise and Shortcomings of XML as an Interchange Format for Computational Models of Biology

aims for a wider scope of model description and isnot specific to any one field of biology.XML, a data exchange language closely related toHTML, is a widely accepted standard for describingstructured textual data. Its often advertised advantage isthat XML documents with different structure can be readby the same generic reusable parser. However, XML byitself does not enable information interchange. Humanreaders of XML may be able to guess the meaning of astatement such as g ¼ 0:1 but to a computer program, and and areallequallymeaningless.Whataprogramshoulddo with XML data is undefined by the XML standard.Frequently, in practice, the semantics (or meaning) ofXML-based model description languages are described inspecification documents written in natural human language.Softwareprogrammersmustreadthespecificationdocumentsand convert the requirements into programs (in Python, Java,etc.) for reading and writing model descriptions. But as newmodeling approaches emerge, and new simulation code iswritten, the semantics of model description languages mustbe reimplemented. A specification written in a human lan-guage often hides ambiguities, and as the complexity of thelanguages and the number of supported software platformsincreases, it is difficult or impossible to ensure that everylanguage construct is implemented consistently in every soft-ware package.The XML community has developed several schema lan-guages that can specify rules for structuring and validatingXML documents, but they offer weak support for data types,procedures, or complex dependencies between elements.Therefore, the expressive power of XML is greatly affectedby its interpretation.The use of XML for the syntactic structure of a modelinglanguage does indeed eliminate the need for specialized