Implementing Systemic Thinking for Automatic Schema Matching: An Agent-Based Modeling Approach

TL;DR

This paper introduces Reflex-SMAS, an agent-based modeling tool that applies systemic and complex adaptive system principles to improve the effectiveness and efficiency of automatic schema matching.

Contribution

It presents a novel systemic approach using agent-based modeling to address challenges in automatic schema matching, demonstrating improved quality and reduced effort.

Findings

Increased matching quality demonstrated in experiments

Reduced effort required for schema matching

Significant paradigm shift in ASM methodology

Abstract

Several approaches are proposed to deal with the problem of the Automatic Schema Matching (ASM). The challenges and difficulties caused by the complexity and uncertainty characterizing both the process and the outcome of Schema Matching motivated us to investigate how bio-inspired emerging paradigm can help with understanding, managing, and ultimately overcoming those challenges. In this paper, we explain how we approached Automatic Schema Matching as a systemic and Complex Adaptive System (CAS) and how we modeled it using the approach of Agent-Based Modeling and Simulation (ABMS). This effort gives birth to a tool (prototype) for schema matching called Reflex-SMAS. A set of experiments demonstrates the viability of our approach on two main aspects: (i) effectiveness (increasing the quality of the found matchings) and (ii) efficiency (reducing the effort required for this efficiency). Our approach represents a significant paradigm-shift, in the field of Automatic Schema Matching.