Towards the development of a knowledge graph-based decision support framework for Green Building Neighborhoods

Zero, positive energy buildings and green communities have over the past decade become central to research, policies, regulations and sustainability certification systems. Sustainability is considered in this context, as the unifying domain composed of interlinked complex objectives to be targeted via new technologies, services and active stakeholders' engagement. The role of stakeholders is of utmost importance in such a dynamic and continuous decision-oriented process which spans throughout the various life-cycle phases i.e., planning, designing, manufacturing, construction, operation, renovation and end of life. In this context, it is believed that decision making needs to be based on the active and transparent participation of various stakeholders and experts. This can be promoted through the development of a pool of decision support tools or functions to be exploited on a case-by-case basis. In this paper, a knowledge graph-based decision support framework for Green Building Neighborhoods (GBN) is proposed to demonstrate its main attributes and added value in facilitating indicative decision support functions such as: i) Urban Heat Island (UHI) assessment, ii) Life Cycle Analysis (LCA), iii) Life Cycle Cost (LCC) analysis and iv) Energy Management