SciModeler: A Metamodel and Graph Database for Consolidating Scientific Knowledge by Linking Empirical Data with Theoretical Constructs
| Autor: | Nuijten, Raoul C.Y., Van Gorp, Pieter, Hammoudi, Slimane, Pires, Luis Ferreira, Seidewitz, Edwin, Soley, Richard |
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| Přispěvatelé: | Information Systems IE&IS, EAISI Health |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Empirical data
Sociology of scientific knowledge Graph database Theory-building Process (engineering) Computer science Software tool Scientific theory computer.software_genre Data science Field (computer science) Metamodeling Empirical research Scientific method Metamodel Health behavior change computer |
| Zdroj: | Proceedings of the 9th International Conference on Model-Driven Engineering and Software Development-Volume 1: MODELSWARD, 314-321 STARTPAGE=314;ENDPAGE=321;TITLE=Proceedings of the 9th International Conference on Model-Driven Engineering and Software Development-Volume 1: MODELSWARD MODELSWARD |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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