Contextualizing Large-Scale Domain Knowledge for Conceptual Modeling and Simulation

TL;DR

This paper introduces VERA, an interactive tool that helps users acquire, contextualize, and utilize large-scale domain knowledge for building and simulating ecological models, enhancing understanding and prediction accuracy.

Contribution

The paper presents VERA, a novel interactive system that scaffolds domain knowledge acquisition and application in conceptual modeling and simulation of ecological phenomena.

Findings

VERA enables qualitative and quantitative ecological modeling.

Learners can construct, simulate, and review ecological models.

The approach integrates large-scale domain ontologies and trait data.

Abstract

We present an interactive modeling tool, VERA, that scaffolds the acquisition of domain knowledge involved in conceptual modeling and agent-based simulations. We describe the knowledge engineering process of contextualizing large-scale domain knowledge. Specifically, we use the ontology of biotic interactions in Global Biotic Interactions, and the trait data of species in Encyclopedia of Life to facilitate the model construction. Learners can use VERA to construct qualitative conceptual models of ecological phenomena, run them as quantitative simulations, and review their predictions.