Meta-data for absorption tomography measurements

Abstract

The simplicity of nonclinical x-ray tomography data collection has caused some to overlook the importance of saving additional experimental information or experiment meta-data. Sample meta-data are often saved in the experimenter’s logbook while meta-data about the instrument and experimental conditions are saved by the instrument itself or by the instrument operator. The lack of standardization of this approach has limited the development of automatic tools for data analysis and experiment logging but has also hindered the ability to reproduce the data collection and data analysis under the same conditions. In this paper we introduce tomo-meta, a publicly available repository of laboratory and synchrotron based tomography instrument meta-data files with the aim of presenting how meta-data are currently collected and identify best practices that enable data collection and data analysis repeatability. Structured and machine readable meta-data files, such as HDF, CSV, JSON, XML, etc., are essential for creating automatic processing pipeline. When the tomography meta-data files are structured as machine readable, we also provide a simple python script to automatically load them into a python dictionary.