Construction project and processes intelligence across the project lifecycle

建筑业的数字化转型预计将为该行业的历史挑战提供解决方案，包括缺乏数据可访问性和生产率停滞不前。Concordia大学和Aedo AI公司之间拟议的合作伙伴关系旨在通过语义基础和流程挖掘分析将现有Aedo的建筑项目数据平台纳入到一个新的水平。该项目有三个主要的研究目标(RO)，每个目标都将通过一些研究任务来实现。(RO1)通过项目生命周期本体实现自上而下的智能--该RO将包括(I)需求分析；以及(Ii)为建筑项目在其整个生命周期中的跨方面本体进行建模和验证。(RO2)使用AEDO的流程挖掘-该RO将通过(I)增强Aedo数据模式以支持事件日志；以及(Ii)开发提取流程分析的算法，即流程发现、合规性检查、瓶颈分析、项目社会网络分析等来实现。(R03)项目之间的语义交叉搜索-为实现这一目标定义了三项任务。(I)实施本体和流程挖掘结果以进行建设项目的多方面分析；(Ii)使用数据挖掘来了解建设项目和生命周期其他阶段之间的影响模式；以及(Iii)开发基于各方面之间的互动以及来自生命周期不同阶段的影响的关键绩效指标来评估建设项目。该项目将招聘五名主要的HQP(三名博士和两名硕士)，并将在三年的课程中培养更多的硕士学生。公平、多样性和包容性(EDI)是团队建设的基本属性，也是该项目培训计划的中心主题。此外，该项目的成果，即对进程和行为者业绩的数据驱动的分析，预计将通过消除传统业绩评估程序中的偏见，帮助打破针对施工中代表性不足群体的陈规定型障碍。

Digital transformation of the construction industry is expected to provide solutions to the historical challenges of the industry, including the lack of data accessibility and stagnant productivity. The proposed partnership between Concordia University and Aedo AI company aims to take the existing Aedo's construction project data platform to the next level by incorporating 'intelligence' through a semantic foundation and process mining analytics. The project has three main Research Objectives (RO's), each of which will be achieved through a number of research tasks. (RO1) Top-down Intelligence through project lifecycle ontology - This RO will include (i) a requirements analysis; and (ii) modeling and validation of a cross-faceted ontology for construction projects across their entire lifecycle. (RO2) Process Mining with Aedo - This RO will be achieved by (i) enhancing Aedo data schema to support event-logs; and (ii) developing algorithms for extracting process analytics, i.e., process discovery, compliance checking, bottleneck analysis, project social network analysis, etc. (RO3) Semantic cross-search among projects - Three tasks are defined to achieve this objective. (i) Implementing the ontology and process mining results for a cross-faceted analysis of construction project; (ii) using data mining for understanding influence patterns among construction and other phases of the = lifecycle; and (iii) developing KPIs for evaluation of construction projects based on interactions among various facets, as well as impacts from/on different phases of the lifecycle.This project will recruit five main HQP (three PhD and two MASc) and will train more MEng students, throughout the course of three years. Equity, Diversity, and Inclusion (EDI) is a fundamental attribute of team building, and a central theme of the training plan for this project. Furthermore, the project's outcome, i.e. data-driven analysis of processes' and actors' performance is expected to help break the stereotypical barriers against the presence of underrepresented groups in construction, by removing biases from the traditional performance assessment procedures.