Mathematical models as research data via flexiformal theory graphs

dc.bibliographicCitation.volume2385
dc.contributor.authorKohlhase, Michael
dc.contributor.authorKoprucki, Thomas
dc.contributor.authorMüller, Dennis
dc.contributor.authorTabelow, Karsten
dc.date.accessioned2017-04-13T11:51:33Z
dc.date.available2019-06-28T08:07:43Z
dc.date.issued2017
dc.description.abstractMathematical modeling and simulation (MMS) has now been established as an essential part of the scientific work in many disciplines. It is common to categorize the involved numerical data and to some extent the corresponding scientific software as research data. But both have their origin in mathematical models, therefore any holistic approach to research data in MMS should cover all three aspects: data, software, and models. While the problems of classifying, archiving and making accessible are largely solved for data and first frameworks and systems are emerging for software, the question of how to deal with mathematical models is completely open. In this paper we propose a solution to cover all aspects of mathematical models: the underlying mathematical knowledge, the equations, boundary conditions, numeric approximations, and documents in a flexiformal framework, which has enough structure to support the various uses of models in scientific and technology workflows. Concretely we propose to use the OMDoc/MMT framework to formalize mathematical models and show the adequacy of this approach by modeling a simple, but non-trivial model: van Roosbroecks drift-diffusion model for one-dimensional devices. This formalization and future extensions allows us to support the modeler by e.g. flexibly composing models, visualizing Model Pathway Diagrams, and annotating model equations in documents as induced from the formalized documents by flattening. This directly solves some of the problems in treating MMS as research data and opens the way towards more MKM services for models.eng
dc.description.versionpublishedVersioneng
dc.formatapplication/pdf
dc.identifier.issn2198-5855
dc.identifier.urihttps://doi.org/10.34657/2657
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/2523
dc.language.isoengeng
dc.publisherBerlin : Weierstraß-Institut für Angewandte Analysis und Stochastikeng
dc.relation.doihttps://doi.org/10.20347/WIAS.PREPRINT.2385
dc.relation.ispartofseriesPreprint / Weierstraß-Institut für Angewandte Analysis und Stochastik , Volume 2385, ISSN 2198-5855eng
dc.rights.licenseThis document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties.eng
dc.rights.licenseDieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.ger
dc.subjectMathematical modelseng
dc.subjectOMDoc/MMTeng
dc.subjectResearch dataeng
dc.subjectMathematical knowledge managementeng
dc.subject.ddc510eng
dc.titleMathematical models as research data via flexiformal theory graphseng
dc.typereporteng
dc.typeTexteng
dcterms.bibliographicCitation.journalTitlePreprint / Weierstraß-Institut für Angewandte Analysis und Stochastikeng
tib.accessRightsopenAccesseng
wgl.contributorWIASeng
wgl.subjectMathematikeng
wgl.typeReport / Forschungsbericht / Arbeitspapiereng
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