4.5 Review

THE ARC OF MASS SPECTROMETRY EXCHANGE FORMATS IS LONG, BUT IT BENDS TOWARD HDF5

Journal

MASS SPECTROMETRY REVIEWS
Volume 36, Issue 5, Pages 668-673

Publisher

WILEY
DOI: 10.1002/mas.21522

Keywords

mass spectrometry; data exchange formats; HDF5

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Funding

  1. Biomedical Research Program funds at Weill Cornell Medicine - Qatar, a program - Qatar Foundation

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The evolution of data exchange in Mass Spectrometry spans decades and has ranged from human-readable text files representing individual scans or collections thereof (McDonald et al., 2004) through the official standard XML-based (Harold, Means, & Udemadu, 2005) data interchange standard (Deutsch, 2012), to increasingly compressed (Teleman et al., 2014) variants of this standard sometimes requiring purely binary adjunct files (Rompp et al., 2011). While the desire to maintain even partial human readability is understandable, the inherent mismatch between XML's textual and irregular format relative to the numeric and highly regular nature of actual spectral data, along with the explosive growth in dataset scales and the resulting need for efficient (binary and indexed) access has led to a phenomenon referred to as technical drift (Davis, 2013). While the drift is being continuously corrected using adjunct formats, compression schemes, and programs (Rost et al., 2015), we propose that the future of Mass Spectrometry Exchange Formats lies in the continued reliance and development of the PSI-MS (Mayer et al., 2014) controlled vocabulary, along with an expedited shift to an alternative, thriving and well-supported ecosystem for scientific data-exchange, storage, and access in binary form, namely that of HDF5 (Koranne, 2011). Indeed, pioneering efforts to leverage this universal, binary, and hierarchical data-format have already been published (Wilhelm et al., 2012; Rubel et al., 2013) though they have under-utilized self-description, a key property shared by HDF5 and XML. We demonstrate that a straightforward usage of plain (vanilla) HDF5 yields immediate returns including, but not limited to, highly efficient data access, platform independent data viewers, a variety of libraries (Collette, 2014) for data retrieval and manipulation in many programming languages and remote data access through comprehensive RESTful data-servers. (C) 2016 Wiley Periodicals, Inc.

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