automatically generated from their asset data requirement center hub (ARID) and follow the same data standard used throughout the entire agency. And once the collection work is done, the spreadsheets can be easily uploaded for data validation and then uploaded to their EAM CMMS system. Figure 2 illustrates a sample logic diagram of how each data resource could work cohesively under the regulation of CDE. The CDE is the data foundation of the entire data management plan that provides the frame- work for the upper data structure to build on. Once all the pieces are ready to assemble, it is time to talk about how to connect them together. Connect Everything End User-Oriented Approach Data integration is just a fancy concept if there is no efficient and effec - tive way to consolidate data from disparate sources into a single place for the user to access. To avoid that, the goals from the end users’ per- spective must be considered when initially designing the digital twin. With clearly understood expectations, we can better define functional requirements, then structure them into use cases, and dissemble use cases into data requirements. The latter one is what we should follow since it produces the digital twin which the end-user really wants. It is often called an end-user-oriented approach. It requires the digital twin program designer/architect to consider the following questions to make the final product practical and targeted. • Who are the targeted end-users? • What are their expectations? • To what extent can expectations be met? What technologies should be incorporated? • Will the data requirements be comprehensive and sufficient to support all defined requirements? If not, what else must be put into the data requirements? As an example, a client from the facility management department wants to enrich the work order in the CMMS with quality informa - tion, such as 3D asset representation, IoT sensor reading history, past work order history, and, if possible, information about its connected objects and surrounding area. This is a reasonable expectation since it will have the AM/FM operator better prepared for the onsite job. The 3D navigation function saves time that would be spent searching for 2D drawings and information about connected objects and the sur- rounding area can determine if special tools are needed. The sensor reading history helps in diagnosis and making better onsite decisions. In this case, data integration will include the BIM model, which pro - vides geometrical location information, CMMS, which provides O&M information and IoT sensor (with related gateway and data warehouse), which offers meter reading information. If a CDE was established and implemented, these three data sources could be mapped and work to- gether via a unique identifier. The CDE also provides the opportunity to connect the workflow with other compatible data sources. In this case, the PCR, a popular decision-making assisting module, could be plugged in to help the operator diagnose the root cause and suggest cor- responding remedy strategies. When designing the PCR database, its hierarchy should follow the asset classification requirement, so future cross-referencing is possible.
as Connected Data Environment, or Collaborated Data Environment. The metadata remains under the control of its appropriate host and is exposed through standardized connections for integration and access. In this circumstance, the standards-based CDE is essential to keep all connected databases talking in the same language. The development of GIS-BIM CDE is more critical for sizeable public transportation agen - cies like the Port Authority of New York & New Jersey (PANYNJ). The agency spans across two states and has substantial influence on the area’s infrastructure, mobility, and quality of life. Development of a standardized CDE between PANYNJ's facilities, line departments, and all contractors and service providers has proven beneficial. Internet of Things (IoT) The Internet of Things (IoT) describes the network of physical objects that are embedded with sensors, gateways, and other technologies for the purpose of connecting and exchanging data over the internet. IoT was introduced into the AECO industry years ago and now fulfills an essential role in the digital twin. As discussed in earlier parts of this series, the modularized digital twin system is driven by the utilization of all corresponding types of IoT implementation. When engaged with a digital twin project, IoT readings need to be collected in the data gateway , massaged in a data warehouse and then assigned to certain assets or locations. Appropriate data analytics and reporting are also essential to interpret the readings in a practical manner. Here, CDE is the foundation to facilitate the “handshaking” between IoT readings with CMMS data requirements and BIM objects. In a real-world proj - ect, substantial time is spent on mapping thousands of IoT readings with thousands of data points coming from thousands of assets. A solid CDE will pave a wide and flat road for data mapping and integration and therefore benefit digital twin implementation. Spreadsheets & Miscellaneous At least for now, the spreadsheet is a tool that will not be eliminated no matter how advanced the technology. The spreadsheet is still widely used to support multiple processes including engineering design, estimation, data collection, submission, and O&M records. While us - ing spreadsheets can be challenging, they are still essential for some processes, serving as a means for gathering important information required by the digital twin. Specific databases can host these spread - sheets and integrate them but only if they speak the same language from the beginning. in fact, the PANYNJ still uses spreadsheets for most of their asset data collection. However, these spreadsheets are
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