A Web 3.0-driven Collaborative Multicriteria Spatial Decision Support System

Abstract

Multicriteria Spatial Decision Support System (MC-SDSS) is one of the most common tools for solving the spatial decision problems. Using the MC-SDSS in the Web 2.0 environment enhances the collaborative decision making by providing a flexible problem-solving framework, where the relevant GIS-based multicriteria decision analysis (MCDA) tools and information are provided for active participation/collaboration. However, the Web 2.0-based collaborative GIS-MCDA knowledge including the user generated content (preferences/opinions) and the GIS-MCDA elements are not machine-understandable. Thus, such knowledge cannot be interpreted, processed, searched, shared, and reused by the Web-based software agents and applications. Additionally, the GIS-MCDA models are often constructed based on the knowledge and understanding that arises out of the subjective viewpoints and they lack a shared and common reference for collaboration, thus making it hard for participants to collaboratively solve the decision problem. To address these problems, this paper proposes the Web 3.0-based collaborative MC-SDSS, which integrates the Web 2.0 (a Web of people) community methods and the Semantic Web (a Web of meaning) technologies. The collaborative/participatory GIS-MCDA knowledge is semantically modeled in an ontological framework as a backbone of the Semantic Web. The ontology is needed to express the collaborative GIS-MCDA knowledge in a shared, unified, structured, meaningful, and machine-interpretable form, ready for software agents and people to interpret, process, communicate, share, and reuse it. The paper demonstrates an implementation of the proposed Web 3.0-based MC-SDSS for solving the parking site selection problem in Tehran, Iran.