TriboDataFAIR Ontology
Creators: name: Garabedian, Nikolay
Publisher: name: Zenodo
Year: 2021
Subjects: tribology
FAIR data
ontology
friction

description: <strong>An ontology of FAIR tribological experiments</strong> The purpose of the ontology is to provide a controlled vocabulary of terms used to describe the scientific procedures in an experimental tribology lab. When used in conjunction with an Electronic Lab Notebook, the ontology provides the framework for creating a FAIR (findable, accessible, interoperable and reusable) data in experimental tribology. The scope of the ontology currently spans only one showcase experimental chain (soon to be published and linked here). The contents of the ontology are the result of &gt;20 meetings of 10 domain experts where the minimum requisite terms to make tribological data interoperable were agreed upon. The ontology has been validated by reimplementing the showcase experiment and producing a "FAIR Data Package" (soon to be published and linked here). Kadi4Mat (https://kadi.iam-cms.kit.edu/) was used to generate the data package. In order to use the ontology for it purpose on can use SurfTheOWL (https://github.com/nick-garabedian/SurfTheOWL) as a start. The software called Protégé (https://protege.stanford.edu/) was used for the development of the ontology, while SUMO (https://www.ontologyportal.org/) and EXPO (http://expo.sourceforge.net/) were used as foundational upper ontologies, and tribAIn (https://github.com/snow0815/tribAIn) was used to a limited extent when possible. More information and contact details found here: https://fairsharing.org/3597 <strong>Part of publication:</strong> https://www.nature.com/articles/s41597-022-01429-9 - Garabedian, N.T., Schreiber, P.J., Brandt, N., Greiner, C., et al. Abstract: Generating FAIR research data in experimental tribology. Sci Data 9, 315 (2022). Digital solutions for the generation of FAIR (Findable, Accessible, Interoperable and Reusable) data and metadata in experimental tribology are currently lacking, despite the looming challenge of integrating cutting-edge data science techniques – a promising scientific route for any field that often relies on phenomenology and empiricism. Additionally, the broad interdisciplinarity of tribology is probably a main contributing factor for the lack of community-wide data and metadata standards, and the heavy reliance on custom workflows and equipment. This paper, first, outlines a sample framework for scalable generation of FAIR data, and second, delivers a showcase FAIR data package for a pin-on-disk tribological experiment. The resulting curated data, consisting of 2,008 key-value pairs and 1,696 logical axioms, is the result of (1) the close collaboration with developers of a virtual research environment, (2) crowd-sourced controlled vocabulary, (3) ontology building and (4) numerous – seemingly – small-scale digital tools. Thereby, this paper demonstrates a collection of scalable non-intrusive techniques that extend the life, reliability and reusability of experimental tribological data beyond typical publication practices. https://youtu.be/xwCpRDnPFvs - Generating FAIR Research Data in Experimental Tribology - Get Scientific Results Ready for ML https://doi.org/10.5281/zenodo.5720626 - FAIR Data Package of a Tribological Showcase Pin-on-Disk Experiment https://doi.org/10.5281/zenodo.5720198 or https://github.com/nick-garabedian/TriboDataFAIR-Ontology or https://fairsharing.org/3597 - TriboDataFAIR Ontology https://doi.org/10.5281/zenodo.5720218 or https://github.com/nick-garabedian/SurfTheOWL - SurfTheOWL https://kadi4mat.iam-cms.kit.edu/ - Kadi4Mat Virtual Research Environment and Electronic Lab Notebook