Multimodal signature file formats and performance in computational environments

Abstract

The dissemination formats for multimodal signature data generally favor either formats with extreme interoperability, such as Extensible Markup Language (XML), portable binary formats with very high levels of interoperability, such as Hierarchical Data Format 5 (HDF5), or proprietary binary formats, often optimized for a specific application but which offer very low levels of interoperability across various computer platforms. The lack of Free and Open Source Software (FOSS) tools for proprietary or application specific file formats, tends to make such formats inappropriate for sharing signature data across organizations such as U.S. Army Research Laboratory (ARL), Signatures Support Program (SSP), and other government agencies. Sharing signature data for computational purposes is of extreme interest to the scientific community. An initial study of similar signatures in two different popular data file formats (HDF5 and XML) and using three popular computational environments (MATLAB, Octave, and Python) reveals definite advantages of HDF5 over XML, especially for larger data sets. HDF5 provides several key benefits for scientific applications without sacrificing interoperability across many computer platforms. The combination of HDF5 and XML for dissemination of signature data and information may yield the best solution for data consumers and providers.