Extensible Markup Language (XML)

TL;DR: The development of NeuroML as a common description language for biophysically detailed neuronal and network models enables interoperability across multiple simulation environments, thereby improving model transparency, accessibility and reuse in computational neuroscience.

TL;DR: This work introduces five algorithms for structural join order optimization for XML tree pattern matching and presents an extensive experimental evaluation, demonstrating that many relational rules of thumb are no longer appropriate and recommending that DPP should be used in XML query optimizers where query execution time is expected to be significant, and that FP is used where it is important to find a good plan quickly.

TL;DR: A novel editor supporting interactive refinement in the development of structured documents and a new bidirectional transformation language that cannot only describe the relationship between the document source and its view, but also data dependency in the view is presented.

TL;DR: A novel approach to building and using statistical summaries of large XML data graphs for effective path-expression selectivity estimation, and the first work to address this timely problem in the most general setting of graph-structured data and complex (branching) path expressions.