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@Mat-O-Lab

Materials Open Laboratory

Joint Venture of Fraunhofer Materials and BAM
README.md

Vision

Mat-O-Lab describes material science human and machine readable, proving the use from laboratory to product.

Mission

Mat-O-Lab stands for the digitization of materials, parts and components along their entire life cycle. For that purpose, concrete practical and applicable solutions for pilot cases centered about specific materials are developed and provide for public use. Key results (datasets, ontologies, tools for data structuring and data analysis) from parallel research projects are consolidated and constantly improved. Mat-O-Lab also stands for a new, open and agile collaboration between the institutes of the Fraunhofer Group Materials and Components (MATERIALS), the Bundesanstalt für Materialforschung und -prüfung (BAM) and interested partners from industry and academia.

Premises

  • We use the Basic Formal Ontology (BFO) as top level ontology (https://basic-formal-ontology.org/)
  • We focus on using Common Core Ontology Stack https://github.com/CommonCoreOntology/CommonCoreOntologies, therefore we migrated the BWMD Ontology and provide it as Material Science an Engineering Ontology (MSEO) https://github.com/Mat-O-Lab/MSEO
  • Tools and Ontologies created in Mat-O-Lab should be open source and publicly available
  • We aim to create meaningful metadata for primary experiment data, therefore raw data in files (Ascii, Images, ....) is referenced by an URI but all metadata is converted to sematic data. It also includes information on the structure of the raw data file, to enable digestion of the raw data itself . By combining it with a method knowledge representation, a graph. The tabular data is untouched and will not be converted.
  • Semantic data is to be shared in a decentral dataspace. Data sovereignty and security are primary aspects to be addressed in a practical solution. Mat-O-Lab considers a IDS based solution https://internationaldataspaces.org/ foremost.
  • Method knowledge graphs must be constructed by domain experts; therefore, we must provide tools for them to do so. mapping between data and method graphs must be done by domain experts, inherent knowledge about the specific method is necessary to do so.!

Networking

We try to actively connect to

and all willing partners

Popular repositories Loading

  1. ckanext-chat ckanext-chat Public

    Configurable Chat Interface for CKAN

    Python 13 2

  2. MSEO MSEO Public

    Repository of Material Science and Engineering Ontology MSEO

    Jupyter Notebook 10 3

  3. RDFConverter RDFConverter Public

    Transform your data into semantic, machine-readable knowledge graphs - no coding required.

    Python 7

  4. CSVToCSVW CSVToCSVW Public

    Generates CSVW JSON-LD for various types CSVs

    Jupyter Notebook 5

  5. KnowledgeUI KnowledgeUI Public

    Application to Interact with a Knowledge Base in a Triple Store

    HTML 4 1

  6. OrgSite OrgSite Public

    Repo to generate the OrgSite

    SCSS 3

Repositories

Showing 10 of 39 repositories
  • DataStack Public

    Docker Compose Stack to transform Material Science Data into Sematic Data

    Mat-O-Lab/DataStack’s past year of commit activity
    Shell 0 GPL-3.0 2 0 0 Updated Mar 23, 2026
  • ckanext-matolabtheme Public

    A CKAN extension providing the Mat-O-Lab theme for data portals. It includes configurable branding (logo, banner, favicon), GDPR-compliant privacy pages in English and German, and a customisable landing page suitable for materials science research data repositories.

    Mat-O-Lab/ckanext-matolabtheme’s past year of commit activity
    HTML 1 AGPL-3.0 0 1 0 Updated Mar 23, 2026
  • ckanext-fuseki Public Forked from etri-odp/ckanext-jena

    CKAN extension that automatically pushes RDF resources to an Apache Jena Fuseki triple store, provides a CKAN-authenticated SPARQL proxy with dataset-level access control, and embeds a YASGUI query interface for interactive SPARQL exploration.

    Mat-O-Lab/ckanext-fuseki’s past year of commit activity
    Python 2 AGPL-3.0 2 0 0 Updated Mar 20, 2026
  • ckanext-csvtocsvw Public

    Extention to automate meta data creation for csv files with the help of the csvtocsvw tool of mat-o-lab.

    Mat-O-Lab/ckanext-csvtocsvw’s past year of commit activity
    Python 0 AGPL-3.0 0 1 0 Updated Mar 19, 2026
  • RDFConverter Public

    Transform your data into semantic, machine-readable knowledge graphs - no coding required.

    Mat-O-Lab/RDFConverter’s past year of commit activity
    Python 7 Apache-2.0 0 0 0 Updated Mar 18, 2026
  • CSVToCSVW Public

    Generates CSVW JSON-LD for various types CSVs

    Mat-O-Lab/CSVToCSVW’s past year of commit activity
    Jupyter Notebook 5 Apache-2.0 0 0 0 Updated Mar 16, 2026
  • MapToMethod Public

    Create semantic YARRRML mapping rules for your data - no RML expertise required.

    Mat-O-Lab/MapToMethod’s past year of commit activity
    Python 2 1 0 0 Updated Feb 18, 2026
  • IOFMaterialsTutorial Public template
    Mat-O-Lab/IOFMaterialsTutorial’s past year of commit activity
    1 MIT 1 0 0 Updated Feb 18, 2026
  • ckanext-csvwmapandtransform Public

    CKAN extension facilitating YARRRML mappings in conjunction with RDFConverter to run automatic transforms matching best fitting maps as a background job.

    Mat-O-Lab/ckanext-csvwmapandtransform’s past year of commit activity
    Python 1 AGPL-3.0 1 0 0 Updated Feb 11, 2026
  • ckanext-chat Public

    Configurable Chat Interface for CKAN

    Mat-O-Lab/ckanext-chat’s past year of commit activity
    Python 13 2 0 1 Updated Feb 10, 2026
View all repositories

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