Authors:
Bill Roungas
1
;
Sebastiaan Meijer
2
and
Alexander Verbraeck
1
Affiliations:
1
Department of Multi Actor Systems, Delft University of Technology, Jaffalaan 5, Delft and The Netherlands
;
2
Department of Health Systems Engineering, KTH Royal Institute of Technology, Hälsovägen 11, Huddinge and Sweden
Keyword(s):
Simulation, Validation, Web Technologies, R Statistical Language, OpenTrack, Friso.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Cardiovascular Technologies
;
Case Studies
;
Collaboration and e-Services
;
Complex Systems Modeling and Simulation
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
e-Business
;
Enterprise Information Systems
;
Formal Methods
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Integration/Interoperability
;
Interoperability
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Logistics
;
Neural Rehabilitation
;
Neurotechnology, Electronics and Informatics
;
Ontologies and the Semantic Web
;
Sensor Networks
;
Simulation and Modeling
;
Simulation Tools and Platforms
;
Software Agents and Internet Computing
;
Software and Architectures
;
Symbolic Systems
Abstract:
The complexity of modern systems has made the use of simulations paramount, in order to test different scenarios in an affordable, ethical, and risk-free way. As such, simulations need to be validated, ensuring that the obtained results are meaningful. But validation apart from the computational difficulties, bears several other problems. The constant need for validation due to updates on the simulation software, the dependence on the validation experts to be always available for the new iterations and for presenting any new insights are just some of these problems. This paper proposes a framework, and applies it to two case studies, which is based on Web 3.0 technologies and the R statistical language as a mean to mitigate such problems.