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 language | English |
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Title of host publication | Proceedings of the 9th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD |
Editors | Slimane Hammoudi, Luis Ferreira Pires, Edwin Seidewitz, Richard Soley |
Publisher | SCITEPRESS-Science and Technology Publications, Lda. |
Pages | 314-321 |
Number of pages | 8 |
ISBN (Electronic) | 978-989-758-487-9 |
DOIs | |
Publication status | Published - 2021 |
Event | 9th International Conference on Model-Driven Engineering and Software Development - Online streaming, Vienna, Austria Duration: 8 Feb 2021 → 10 Feb 2021 |
Conference
Conference | 9th International Conference on Model-Driven Engineering and Software Development |
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Country/Territory | Austria |
City | Vienna |
Period | 8/02/21 → 10/02/21 |
Keywords
- Graph database
- Health behavior change
- Metamodel
- Scientific method
- Software tool
- Theory-building