Presentation MSE 2022
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The document summarizes research on the intersection of materials science engineering (MSE) and semantic web technologies (SWT). It conducted a literature review identifying 20 key papers using SWT in MSE. The review found ontologies and converting tabular data to RDF were most common applications. It also presented several projects at the Federal Institute for Materials Research and Testing applying SWT to MSE challenges like visualizing methods, natural language queries, and accelerating materials discovery. Overall, the document aimed to illustrate SWT's impact on MSE and identify open challenges at their intersection.
![BAM Motivation State of the art MSE
T
SWT at BAM Conclusion
MSE
T
SWT at BAM
Sequential Learning App for Materials Discovery - SLAMD [Völker et al. 2021]3
- RQ3
Ontology Embedding helping to improve the the prediction of ideal
material candidates
Mapping Tabular data to RDF
Machine Learning
Acceleration:
Before: 82 … 480 Years
After: 45 … 630 Days
3
https://slamd-web.herokuapp.com/
Page 15 of 17](https://image.slidesharecdn.com/surveypresentation-221010074128-d38dbae8/85/Presentation-MSE-2022-15-320.jpg)
Presentation MSE 2022
- 1. The intersection between Materials Science Engineering and Semantic Web Andre Valdestilhas, Bernd Bayerlein, Thilo Muth, Ghezal Ahmad Jan Zia, Benjamin Moreno Torres 27. September 2022
- 2. BAM Motivation State of the art MSE T SWT at BAM Conclusion Outline BAM Motivation State of the art MSE T SW at BAM Conclusion Page 2 of 17
- 3. BAM Motivation State of the art MSE T SWT at BAM Conclusion Federal Institute for Materials Research and Testing (BAM) Page 3 of 17
- 4. BAM Motivation State of the art MSE T SWT at BAM Conclusion BAM ● Scientific issues regarding digitalization ● Active since 2020 ● > 20 employees ● National and International activities ● Research ● Coordination & Consultancy Bundesanstalt für Materialforschung und -prüfung (BAM) eScience group S.3 Page 4 of 17
- 5. BAM Motivation State of the art MSE T SWT at BAM Conclusion Materials Science Engineering and Semantic Web Materials Science Engineering Page 5 of 17
- 6. BAM Motivation State of the art MSE T SWT at BAM Conclusion Research Questions RQ1. What are state-of-the-art approaches in MSE using SWT? RQ2. Which SWT are applied in MSE? RQ3. Does SWT influence the quality of an MSE experiment? RQ.4 What are the open challenges on the intersection between MSE and SWT? Page 6 of 17
- 7. BAM Motivation State of the art MSE T SWT at BAM Conclusion State of the art RQ1. What are state-of-the-art approaches in MSE using SWT? Search Engine / Digital Libraries Google Scholar = 2.990 ACM Digital Library= 14.690 IEEE Xplore Digital Library=150 Springer Link = 9.222 Science Direct=2.417 Semantics Scholar = 92 Journals / Conferences / Workshops ISWC/ESWC/KCAP/JWS/SWJ /OMDI/NatureMaterials = 21 STEP 1 Scan articles based on criteria Download+remov e duplicated articles STEP 2 Review abstract/ titles to include/exclude articles Scan references to identify suitable articles 105 STEP 3 Reviewing full-text 42 Final selection of articles covering SWT in MSE 20 Page 7 of 17
- 8. BAM Motivation State of the art MSE T SWT at BAM Conclusion MSE T SWT x year Ontologies RDF triples from tabular data Page 8 of 17
- 9. BAM Motivation State of the art MSE T SWT at BAM Conclusion SWT in MSE in percentage RQ2. Which SWT are applied in MSE? Page 9 of 17
- 10. BAM Motivation State of the art MSE T SWT at BAM Conclusion Classification RQ.4 What are the open challenges on the intersection between MSE and SWT? PN Age-hardenable Al-alloy ⨅ Big and FAIR Data Materials informatics NDT Bio materials Tribology WEDM Map Tabular 2 RDF ⨅ Visual Representation MSE Methods ⨅ Provenance MSE experiments ⨅ Ontology Embedding Materials Desing ⨅ MSE topic SWT areas ⨅ Intersection Polymer Nanocomposites (PN), Wire Eletrical Discharge Machining (WEDM),Non-Destructive Testing (NDT) Page 10 of 17
- 11. BAM Motivation State of the art MSE T SWT at BAM Conclusion MSE T SWT at BAM MatVis - A Framework to Visually Represent MSE Methods and RDF KG Creation - (RQ3) URIs URIs representing the data Convert RDF Domain expert Visual components off-the-shelf MSE ontologies Page 11 of 17
- 12. BAM Motivation State of the art MSE T SWT at BAM Conclusion MSE T SWT at BAM NaturalMSEQueries - RQ3. Does SWT influence the quality of an MSE experiment? Natural Language Processing applied to query MSE data easier than SPARQL queries NLP NaturalMSE Queries Page 12 of 17
- 13. BAM Motivation State of the art MSE T SWT at BAM Conclusion MSE T SWT at BAM MatPortal1 - RQ3. Does SWT influence the quality of an MSE experiment? 1 https://matportal.org/ Page 13 of 17
- 14. BAM Motivation State of the art MSE T SWT at BAM Conclusion MSE T SWT at BAM LebeDigital2 - RQ3. Does SWT influence the quality of an MSE experiment? RDF Graph to store MSE data provenance from experimental data to model prediction Sukhobok, Dina, et al. "Tabular data cleaning and linked data generation with Grafterizer." European Semantic Web Conference. Springer, Cham, 2016. 2 BMBF-funded - https://material-digital.de/project/3 Page 14 of 17
- 15. BAM Motivation State of the art MSE T SWT at BAM Conclusion MSE T SWT at BAM Sequential Learning App for Materials Discovery - SLAMD [Völker et al. 2021]3 - RQ3 Ontology Embedding helping to improve the the prediction of ideal material candidates Mapping Tabular data to RDF Machine Learning Acceleration: Before: 82 … 480 Years After: 45 … 630 Days 3 https://slamd-web.herokuapp.com/ Page 15 of 17
- 16. BAM Motivation State of the art MSE T SWT at BAM Conclusion Conclusion Detailed a systematic literature review of MSE using SW Illustrate the impact of applying SWT to MSE Present specific open challenges on the intersection between MSE and SWT Next steps (elaborate new approaches based the open challenges and the State of the art) Page 16 of 17
- 17. BAM Motivation State of the art MSE T SWT at BAM Conclusion Thanks! Contact: Andre Valdestilhas email: andre.valdestilhas@bam.de web page: bam.de/e-science twitter: @BamEscience Link to the presentation: https://tinyurl.com/andrelswt2022 Special thanks to: Christoph Völker and Thomas Hanke Page 17 of 17