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A brief introduction is given into our data collection and organization procedure, and why we have settled on the HDF5-based NeXus format for describing experimental data.
The links between NeXus and the SciCat data catalog is also provided, showing how the NeXus metadata is automatically added as searchable metadata in the catalog.
How much do we, the small-angle scatterers, influence the results of an investigation? What uncertainty do we add by our human diversity in thoughts and approaches, and is this significant compared to the uncertainty from the instrumental measurement factors?
After our previous Round Robin on data collection, we know that many laboratories can collect reasonably consistent small-angle scattering data on easy samples1. To investigate the next, human component, we compiled four existing datasets from globular (roughly spherical) scatterers, each exhibiting a common complication, and asked the participants to apply their usual methods and toolset to the quantification of the results https://lookingatnothing.com/index.php/archives/3274).
Accompanying the datasets was a modicum of accompanying information to help with the interpretation of the data, similar to what we normally receive from our collaborators. More than 30 participants reported back with volume fractions, mean sizes and size distribution widths of the particle populations in the samples, as well as information on their self-assessed level of experience and years in the field.
While the Round Robin is still underway (until the 25th of April, 2022), the initial results already show significant spread in the results. Some of these are due to the variety in interpretation of the meaning of the requested parameters, as well as simple human errors, both of which are easy to correct for. Nevertheless, even after correcting for these differences in understanding, a significant spread remains. This highlights an urgent challenge to our community: how can we better help ourselves and our colleagues obtain more reliable results, how could we take the human factor out of the equation, so to speak?
In this talk, we will introduce the four datasets, their origins and challenges. Hot off the press, we will summarize the anonymized, quantified results of the Data Analysis Round Robin. (Incidentally, we will also see if a correlation exists between experience and proximity of the result to the median). Lastly, potential avenues for improving our field will be offered based on the findings, ranging from low-effort yet somehow controversial improvements, to high-effort foundational considerations.
Measuring an X-ray scattering pattern is relatively easy, but measuring a steady stream of high-quality, useful patterns requires significant effort and good laboratory organization.
Such laboratory organization can help address the reproducibility crisis in science, and easily multiply the scientific output of a laboratory, while greatly elevating the quality of the measurements. We have demonstrated this for small- and wide-angle X-ray scattering in the MOUSE project (Methodology Optimization for Ultrafine Structure Exploration).
With the MOUSE, we have combined a comprehensive and highly automated laboratory workflow with a heavily modified X-ray scattering instrument. This combination allows us to collect fully traceable scattering data, within a well-documented, FAIR-compliant data flow (akin to what is found at the more automated synchrotron beamlines). With two full-time researchers, our lab collects and interprets thousands of datasets, on hundreds of samples, for dozens of projects per year, supporting many users along the entire process from sample selection and preparation, to the analysis of the resulting data.
This talk will briefly introduce the foundations of X-ray scattering, present the MOUSE project, and will highlight the proven utility of the methodology for materials science. Upgrades to the methodology will also be discussed, as well as possible avenues for transferring this holistic methodology to other instruments