# Development of Cost and Schedule Data Integration Algorithm Based on Big Data Technology
## 3 Cost-Schedule Integration and Big Data Technology  
### Characteristics of Cost and Schedule Data  
There has been a consensus that the cost-schedule integration provides improved information management and solutions for challenges in construction projects [5], [23]. However, its application in practice still at a nascent stage, compared to other industries, such as manufacturing. The core obstacles of it can be found in characteristics of cost and schedule data in construction projects, as follows. * **Mismatched level of cost and schedule data**: As addressed in Section 2.2, cost data and schedule data in construction projects consist of different information units at different LODs that are mismatched to each other [8]. In practice, schedules at various levels are created and utilized, such as overall schedules, monthly schedules, weekly schedules, and subcontractor schedules. Each of them requires cost assignment and aggregation at the appropriate level for corresponding the activity levels addressed in the schedule. To support it, the database structure needs to be flexible to various schedules; it is essential for achieving data consistency in the integrated management of project cost and schedule. * **A vast amount of data**: For cost-schedule integrated management, multiple dimensional data for construction projects need to be defined as lowest-level information units. The dimensions cover unit quantities of materials, spaces, building elements, activities, organization, and time. Each dimension contains multiple levels, and activity data associated with quantities needs to be connected to unit and unit pricing (unit material, unit labor, unit equipment). According to the authors' case studies, around 10 million building elements exist in a 90-million-dollar building project located in Korea, such as structure, envelope, fire safety, mechanical, electrical, and plumbing. Each element needs to be decomposed into lowest-level information units and linked to (1) space data (project, section, floor, zone, room); (2) activity data (i.e., forming, reinforcing, concrete curing); (3) working organization data (subcontractors, crew); (4) management organization data (contractors, management team, manager, construction manager); (5) time data (year, quarter, month, week, day); and (6) unit pricing data. The level of data decomposition can vary according to the required information level and management level. However, it has been identified that approximately one billion data cells should be prepared for achieving high data consistency for cost-schedule integrated management. * **Variable data**: The lowest-level information units are generated while operating a construction project. They are updated from time to time as design, construction methods, material, pricing, or contracts change. These updates need to be reflected in the database for cost-schedule integrated management in order to keep data integrity. * **Complicated data structure**: There have been efforts to establish databases for lowest-level information units using WBS, CBS, and OBS. The hierarchical approaches in existing studies are not sufficient to incorporate required data at all levels from all dimensions and show limitations in providing enough flexibility and connectivity of data for cost-schedule integration. Consequently, the limited flexibility results in an enormous amount of lower data created by data decomposition at a higher level, which causes challenges in information management. * **Semantic issues**: The existing methods utilized construction classification standards and their codes for data standardization as well as data mining. Key data represented as a complicated combination of codes hinder intuitive understanding and communication of the data. From the technical perspective, these methods rely on a database to store and manage the codes, whose establishment requires significant time and effort.