The Synergy of Data Science, GIS Spatial Analysis and Knowledge Management as a Path to Sustainability Insights

Abstract

This chapter focuses on data science, GIS-based spatial analysis, and knowledge management (KM) threesome and its potential contributions to sustainability insights. Discussion commenced with tracing the historical evolution and essen-tiality of geography for comprehending environmental and social dimensions of sustainability. Then, argumentation delved into the interplay among the three-some's domains and their contributions to sustainability achievement. A prolonged elaboration was provided on geospatial data analytics, visualization, geospatial data mining, and predictive models and their significance for extracting informative and meaningful insights. Since data science has transformed and enriched most scientific disciplines, its empowering implications on GIS were explained. Spatial analysis, therefore, occupied a central position and enabled advanced GIS technique utilization to reveal patterns, relationships, and trends in geospatial data. Furthermore, the chapter explained the interdependent relationships between GIS and KM. Integrating GIS and KM techniques has revolutionized geospatial data organization, visualization, and dissemination and enhanced applications of decision support , environmental planning, and others. The Nexus of this threesome, therefore, serves as a roadmap for solving issues of intricate spatial problems via modeling and informed decisions. The chapter stressed and concluded that the integrated fusion of data science, GIS, and KM provides a robust framework and ideal tools supporting sustainability.