SciModeler: A Metamodel and Graph Database for Consolidating Scientific Knowledge by Linking Empirical Data with Theoretical Constructs

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Abstract

An important purpose of science is building and advancing general theories from empirical data. This process is complicated by the immense volume of empirical data and scientific theories in some fields. Particularly, the systematic linking of empirical data with theoretical constructs is currently lacking. Within this article, we propose a prototypical solution (i.e., a metamodel and graph database) for consolidating scientific knowledge by linking theoretical constructs with empirical data. We conducted a case study within the field of health behavior change where the system is used to record three scientific theories and three empirical studies as well as their mutual links. Finally, we demonstrate how the system can be queried to accumulate knowledge.
Original languageEnglish
Title of host publicationProceedings of the 9th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD
EditorsSlimane Hammoudi, Luis Ferreira Pires, Edwin Seidewitz, Richard Soley
PublisherSCITEPRESS-Science and Technology Publications, Lda.
Pages314-321
Number of pages8
ISBN (Electronic)978-989-758-487-9
DOIs
Publication statusPublished - 2021
Event9th International Conference on Model-Driven Engineering and Software Development - Online streaming, Vienna, Austria
Duration: 8 Feb 202110 Feb 2021

Conference

Conference9th International Conference on Model-Driven Engineering and Software Development
Country/TerritoryAustria
CityVienna
Period8/02/2110/02/21

Keywords

  • Graph database
  • Health behavior change
  • Metamodel
  • Scientific method
  • Software tool
  • Theory-building

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