An ontology-based description of nano computed tomography measurements in electronic laboratory notebooks: from metadata schema to first user experience

TL;DR

The paper tackles the metadata gap in experimental science by proposing an ontology-driven ELN workflow for SRnCT, implemented in the Herbie platform. It details the design of a dedicated SRnCT metadata schema, its mapping to a PRIMA-aligned ontology, and SHACL-based data capture forms that produce a FAIR RDF knowledge graph. Data collected during beamtime are transformable to XML schemas via SPARQL, and competency questions are used to validate and extract information. The approach enables reusable, beamline-agnostic metadata capture and demonstrates practical usability in a PETRA III SRnCT setting, with discussion of scalability and interoperability.

Abstract

In recent years, the importance of well-documented metadata has been discussed increasingly in many research fields. Making all metadata generated during scientific research available in a findable, accessible, interoperable, and reusable (FAIR) manner remains a significant challenge for researchers across fields. Scientific communities are agreeing to achieve this by making all data available in a semantically annotated knowledge graph using semantic web technologies. Most current approaches do not gather metadata in a consistent and community-agreed standardized way, and there are insufficient tools to support the process of turning them into a knowledge graph. We present an example solution in which the creation of a schema and ontology are placed at the beginning of the scientific process which is then - using the electronic laboratory notebook framework Herbie - turned into a bespoke data collection platform to facilitate validation and semantic annotation of the metadata immediately during an experiment. Using the example of synchrotron radiation-based nano computed tomography measurements, we present a holistic approach which can capture the complex metadata of such research instruments in a flexible and straightforward manner. Different instrument setups of this beamline can be considered, allowing a user-friendly experience. We show how Herbie turns all semantic documents into an accessible user interface, where all data entered automatically fulfills all requirements of being FAIR, and present how data can be directly extracted via competency questions without requiring familiarity with the fine-grained structure of the knowledge graph.

Figures (13)

• Figure 1: The hierarchy used in the schema to describe a scan measurement (entry).
• Figure 2: Hierarchy implemented in the SHACL-shapes to describe the experiment. The classes/shapes denoted by a star are single forms to be filled. Shapes marked in orange can most likely be reused in the development of a logbook for another beamline.
• Figure 3: Example of a shape implementation and resulting user interface for generating instances of the mbs:Beamline class. In this example, a root node shape is generated specifying a sh:targetClass, e.g. mbs:Beamline, containing property shapes such as the facility name.
• Figure 4: Example of a shape implementation and resulting user interface on the basis of entering the image pixel size property.
• Figure 5: Example of a shape implementation and later web form for parameters depending on the setup of the beamline. One of two different configurations mbs:NfhSetup and mbs:TxmSetup can be selected.