Modeling and Implementing Scientific Hypothesis

摘要

Computational Simulations are important tools that enable scientists to study complex phenomena about which few data is available or that require dangerous human interventions. They involve complex and heterogeneous components, including: mathematical equations, hypothesis, computational models and data. In order to support in-silico scientific research this complex environment needs to be modeled and have its data and metadata managed enabling model evolution, prediction analysis and decision-making. This paper proposes a scientific hypothesis conceptual model that allows scientists to represent the phenomenon been investigated, the hypotheses formulated in the attempt to explain it, and provides the ability to store results of experiment simulations with their corresponding provenance metadata. The proposed model supports scientific life-cycle through: provenance management, exchange of hypothesis as data, experiment reproducibility, model steering and simulation result analyses. A cardiovascular numerical simulation illustrates the applicability of the model and an initial implementation using SciDB is discussed.