Towards Formal Representation of Memristor-Related Domain Knowledge - A Pragmatic Attempt

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Abstract

Computational ontologies (or knowledge graphs) are powerful established technologies to represent knowledge of a certain domain in a formal (i.e. machine-processable) way. While in the life sciences the usage of those technologies has been common for decades they are rarely applied to engineering domains. Especially for young and highly active sub-fields like the investigation of memristive devices and the related theory, formal knowledge representation promises a significant benefit for the consolidation of terminology and for knowledge transfer both within the scientific community and also towards practitioners. In this contribution we conduct a case study to create an experimental prototype - the Ontology of Memristor Technology (OMT). We present a pragmatic approach based on two simple question answering use-cases. To achieve this we semi-automatically incorporate knowledge from certain overview papers and background knowledge from Wikidata. Based on a critical discussion of our results we also outline directions for further research.

Details

Original languageEnglish
Title of host publication2025 14th International Conference on Modern Circuits and Systems Technologies (MOCAST)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-6
Number of pages6
ISBN (electronic)9798331539146
ISBN (print)979-8-3315-3915-3
Publication statusPublished - 13 Jun 2025
Peer-reviewedYes

Conference

Title14th International Conference on Modern Circuits and Systems Technologies
Abbreviated titleMOCAST 2025
Conference number14
Duration11 - 13 June 2025
Website
LocationTechnische Universität Dresden
CityDresden
CountryGermany

External IDs

ORCID /0000-0001-7436-0103/work/188859570
ORCID /0000-0003-3259-4571/work/188860249

Keywords

Keywords

  • Knowledge graphs, Knowledge transfer, Life sciences, Memristors, Ontologies, Pragmatics, Prototypes, Question answering (information retrieval), Resource description framework, Terminology