FAIR and scalable management of small-angle X-ray scattering data

J Appl Crystallogr. 2023 Mar 21;56(Pt 2):565-575. doi: 10.1107/S1600576723001577. eCollection 2023 Apr 1.

Abstract

A modular research data management toolbox based on the programming language Python, the widely used computing platform Jupyter Notebook, the standardized data exchange format for analytical data (AnIML) and the generic repository Dataverse has been established and applied to analyze small-angle X-ray scattering (SAXS) data according to the FAIR data principles (findable, accessible, interoperable and reusable). The SAS-tools library is a community-driven effort to develop tools for data acquisition, analysis, visualization and publishing of SAXS data. Metadata from the experiment and the results of data analysis are stored as an AnIML document using the novel Python-native pyAnIML API. The AnIML document, measured raw data and plots resulting from the analysis are combined into an archive in OMEX format and uploaded to Dataverse using the novel easyDataverse API, which makes each data set accessible via a unique DOI and searchable via a structured metadata block. SAS-tools is applied to study the effects of alkyl chain length and counterions on the phase diagrams of alkyltrimethyl-ammonium surfactants in order to demonstrate the feasibility and usefulness of a scalable data management workflow for experiments in physical chemistry.

Keywords: FAIR data principles; SAXS; alkyltrimethylammonium surfactants; lyotropic liquid crystals; phase diagrams; research data management; small-angle X-ray scattering.

Grants and funding

This project was supported by the Ministry of Science, Research and the Arts Baden-Württemberg. Financial support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, Project-ID 358283783 – SFB 1333 and EXC 2075) is gratefully acknowledged.