Hystorian: A processing tool for scanning probe microscopy and other n-dimensional datasets

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Abstract

Research in materials science increasingly depends on the correlation of information from multiple characterisation techniques, acquired in ever larger datasets. Efficient methods of processing and storing these complex datasets are therefore crucial. Reliably keeping track of data processing is also essential to conform with the goals of open science. Here, we introduce Hystorian, a generic materials science data analysis Python package built at its core to improve the traceability, reproducibility, and archival ability of data processing. Proprietary data formats are converted into open hierarchical data format (HDF5) files, with both datasets and subsequent workflows automatically stored into a single location, thus allowing easy management of multiple data types. At present, Hystorian provides a basic scanning probe microscopy and x-ray diffraction analysis toolkit, and is readily extensible to suit user needs. It is also able to wrap over any existing processing functions, making it easy to append in an extant workflow.

Original languageEnglish
Article number113345
JournalUltramicroscopy
Volume228
DOIs
StatePublished - Sep 2021

Funding

This work was supported by Division II of the Swiss National Science Foundation under project 200021_178782 . The authors would also like to thank Christian Weymann and Céline Lichtensteiger for their contributions to the code.

Keywords

  • Big data
  • Data processing
  • Image registration
  • Piezoresponse force microscopy
  • Scanning probe microscopy

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