A Tool for Automatic Metadata Extraction and Schema Mapping for SEM Images
Creators: name: Vitali, Elias Giulio Georg
name: Jejkal, Thomas
name: Kirar, Ajay
name: Joseph, Reetu Elza
name: Hartmann, Volker
name: Blumenröhr, Nicolas
name: Inckmann, Maximilian
name: Aversa, Rossella
name: Stotzka, Rainer
Publisher: name: Karlsruher Institut für Technologie (KIT)
Year: 2023
Subjects: mapping
metadata
service
extraction

description: Standardized metadata and its proper storage are essential for effective management of scientific research data. The challenge lies in manually compiling such metadata, a process which can be both tedious and prone to human error. To address this problem, we introduce the Mapping Service, developed within the framework of HMC. The Mapping Service helps to streamline the process of metadata extraction and mapping according to existing community-agreed schemas. This tool has been designed as an adaptable and extensible service suitable across various research disciplines. It allows for add-ons which facilitate the extraction of metadata from otherwise proprietary and non-standard file formats and the mapping to schemas, which strengthens the metadata’s interoperability and reusability. The Mapping Service functions as a platform hosting a diverse suite of plugins. These plugins, each equipped with two primary components—a reader and a mapper—are instrumental in achieving metadata extraction and mapping for various experimental techniques. In many research environments, accessing metadata is a bottleneck due to proprietary formats that demand specific software, often leading researchers to manually transcribe unstructured and poorly-documented metadata embedded within, for example, research images. This manual approach, especially for large datasets comprising hundreds of files, is not only time-consuming but also introduces the potential for human errors. The Mapping Service elegantly addresses these challenges: the reader retrieves metadata from a set of diverse research data, such as images or metadata files, while the mapper discerningly selects key variables prescribed by the user-selected schema from the extracted metadata. These variables are then mapped to their respective schema names, resulting in a systematically formatted JSON metadata document. Through this poster, we showcase one use case via the mapping of Scanning Electron Microscopy (SEM)/Focused Ion Beam (FIB) tomography metadata to our published schema. This functionality is available as a plugin or “Mapping Component”on the Mapping Service and works to emphasize how a large and complex dataset con- taining a large amount of research images may be easily and efficiently transformed into a single metadata document using an intuitive user interface.Though the poster showcases the use case of SEM/FIB tomogra- phy, the Mapping Service has been designed to be a general-purpose tool. Additional plugins tailored to map from one arbitrary schema to another can easily be integrated, and a suite of such plugins is currently in development. Additionally, the service’s standalone web service architecture and user interface ensures ease of adoption without any local dependencies or installations required by end users. In summary, researchers across various fields seeking a streamlined approach to consistent metadata process- ing will find the Mapping Service to be a useful tool. With this poster, we aim to illuminate the advantages of the Mapping Service’s automated extraction and mapping capabilities as well as the necessary considerations and prerequisites for its implementation in a research environment.