Infrastructure, which encompasses highways, rails, ports, terminals, energy, and telecommunication systems, is critical to sustaining productivity expansion, living standards, and stability. These projects widely rely on different skills and sources of capital. There is also widespread consensus that infrastructure complexities are often difficult to predict. Managing and controlling all these inputs for balancing different project sides play critical roles in this context. These processes can, however, be automated, and their duration and costs are reduced with emerging technologies, specifically blockchain technology and digital twins for infrastructure projects. Using decentralization in the construction industry can be advantageous for applications that make subjective and transparent decisions on complex and large infrastructure projects. There are currently no systems that can process large amounts of data efficiently while simultaneously taking into account user information to facilitate the development of such technologies. This research focuses on identifying data-driven techniques for automating data extraction from decentralized autonomous organizations (DAO), using volunteers (voters) for assistance.