BOLD: A Benchmark for Linked Data User Agents and a Simulation Framework for Dynamic Linked Data Environments

TL;DR

The paper introduces BOLD, a benchmark and simulation framework for evaluating Linked Data agents in dynamic environments like smart buildings, enabling performance measurement and task verification.

Contribution

It presents the BOLD benchmark and simulation framework, specifically designed for dynamic Linked Data environments such as smart buildings, with a focus on agent performance and task accuracy.

Findings

Agents based on condition-action rules were evaluated.

Performance metrics for Linked Data agents were established.

Simulation environment effectively tests agent task execution.

Abstract

The paper presents the BOLD (Buildings on Linked Data) benchmark for Linked Data agents, next to the framework to simulate dynamic Linked Data environments, using which we built BOLD. The BOLD benchmark instantiates the BOLD framework by providing a read-write Linked Data interface to a smart building with simulated time, occupancy movement and sensors and actuators around lighting. On the Linked Data representation of this environment, agents carry out several specified tasks, such as controlling illumination. The simulation environment provides means to check for the correct execution of the tasks and to measure the performance of agents. We conduct measurements on Linked Data agents based on condition-action rules.