Innovations in Comfort, Efficiency, and Safety Solutions.
industry example of creating name conventions and models is
Project Haystack for data points of building automation systems.
“You can have data without information, but you cannot have information without data.” Daniel Keys Moran.
you ever looked for as-built building drawings or equipment
specification sheets, only to discover that they are not where they
should be? Without a structured approach to data management you waste
time because of the disorganization in the data and documents; many
times building operators will need to contact the original architects,
engineers or contractors for such data, thus wasting time and money.
The building industry has generally realized that building data and data analytics are major tools for improving building operations. Data software applications, such as energy management and fault detection and diagnostics, are probably the best examples of the effectiveness of managing and analyzing data. The effort for many building owners to acquire and manage facility data, however, appears either ad hoc or narrowly focused on specific aspects of the building, such as energy and HVAC systems. Unfortunately, a data management plan is usually an afterthought.
If however, we really think data is an asset, then we need to organize and manage the data. Buildings provide a substantial amount of data. The data is generated from building management systems, independent control systems, facility management systems, business systems, Building Information Modeling, data in the hands of third-party contractors that install, service and maintain building equipment, data from the utility grid, weather data, etc.
Most building data has a variety of different formats; some of this data is stored away in Excel spreadsheets, Access databases and a host of varied electronic and paper formats. The typical building has several "silos" of data scattered throughout the organization with no cohesive strategy for data management and little coordination. Also note that it's not only the data that is in silos but also the underlying technology systems for data management, different data management processes, and even the people involved.
There would seem to be a very good case for bringing all the facility data into a unified database architecture and putting into practice standard methodologies and processes to manage the data.
There are several benefits from having a data management system. Building data would be more widely available and sharable, and more accessible, and a structured approach can improve the archiving, preservation and retention of data for the long-term. There’s some data and information you'll want for the life cycle of the building and there are analytic opportunities in long-term data you'll want for comparison and trending. A comprehensive data management plan would improve the integrity of the data: Bad data is worthless data. You want accurate, reliable, consistent and complete data. A structured approach initially validates the data, and then puts into place a process where the data can't be changed or destroyed without authorization.
There are roughly 6,500 to 7,000 languages spoken in the world today; for data management, you only want one "language" of standard naming conventions, formats, indexing and data descriptors. It makes it easier to access and understand the data. Creating a naming convention for equipment should have different fields and a common number of characters. The key to naming is that once a naming convention is in place, that it be enforced for building employees and third party contractors.
The best industry example of creating name conventions and models is Project Haystack for data points of building automation systems. With the leadership of the Sky Foundry principals and the development of an industry community, they have created a valuable piece of a building’s “Big Data”, which eventually will become a standard. The open source Project Haystack effort has streamlined the interchange of data and the techniques for managing, presenting and analyzing the vast amount of data generated by today’s buildings.
We don't organize data just for the sake of organizing but are doing so in order to maximize the effectiveness and efficiency of operating buildings. A structured approach can provide additional opportunities for greater correlation between data, improved data analytics and the possibility of developing or identifying new building data metrics.
Data is an asset. During design and construction of a building, data will be generated; it is in the operations of the building that data not only will be generated but also consumed. Given that building operations and maintenance is the most expensive part of total life cycle costs and the longest time duration within the building's life cycle, we need data management during every building phase: design, construction and operations.
A key element is to elevate the importance of data management and provide a person or group of people with the responsibility and authority to manage all the facility data. It’s likely such a group would have IT, facility management and business representatives. During design and construction, we typically have two to three people tasked with managing various building data. One is the LEED consultant tasked with gathering energy and sustainability information for the building certification; another is the BIM consultant organizing BIM models and data; the third is the architect who uses project management software to communicate and share data with the project team. But after commissioning or occupancy of the new building, the roles of the BIM and LEED consultants, and the architect, expire; thus the need for an ongoing internal group with the responsibility for data management.
The facility data group would have a much larger responsibility in implementing the data management system for the building and the acquisition and management of the data from the initial building design through construction and facility management. The group would design, deploy, maintain, monitor and even enforce a comprehensive program for data management.
Practical Data Management Activities
Programming: If you're involved with new construction and going through the programming and conceptual design of the facility, the project team should establish rules for the data management that will be generated throughout the project with some thought given to the data that will need to be exported into operations and facility management systems. Yes, the focus in new construction is typically the construction schedule and budget, but any acknowledgement and appreciation of long-term operations and rules and standards for data management would be positive.
Building Information Modeling: BIM is a significant data management tool for new construction. While we’re all familiar with the three dimensional BIM models, many design teams do not require or enforce the use of COBie data collection by engineers or contractors, which affects facility management transitioning from commissioning and occupancy to full operation. Data can be generated, stored in the BIM COBie files throughout the process of design, construction and commissioning. The updating of data occurs several times during the project and responsibility for the data is shared and shifts from the designers to the contractors during the project. Data also needs to be updated based on RFIs, construction related changes and change orders.
Submittals: Construction submittals are an important milestone in new or renovation construction. Submittals usually involve shop drawings, product data, samples and coordination drawings. Quality assurance and quality control submittals involve design data, test reports, certificates and manufacturer's instructions. The requirement for contractors regarding submittals should be that the submittals are provided in an electronic form, preferable COBie for the product data, or a format that is part of a building owner's data management system.
Systems Integration: We generally integrate buildings systems to enhance functionality. We also integrate systems and data when building owners have multiple BMS systems but want one overall platform. In that case, the larger integration platform acquires data from multiple systems in various formats using different communications protocols and through the use of middleware standardizes the data and creates one database, much like a data management system may use. So in some cases the standardization of data to facilitate an advanced building management systems is in alignment and could be used with an enterprise data management system.
Commissioning: During commissioning and project closeout, data and information such as commissioning reports, project record documents, contract drawings, project manuals, contract modifications, startup logs, test reports, certifications, the complete as-built BIM and other documents and data are generated. All this information should be permanently retained and accessible. Some documents may be paper, such as certifications, but all documents and data should be submitted electronically and stored. The importance of many of these documents is that if the building or its systems are modified the designers and contractors will want to use the original record document as the base line.
An immense amount of building data is created during the design, construction and operation of a facility but we've only managing and analyzing a relatively small amount of the available data. The industry foray into data management and analytics is just in its infancy. At the starting point of data management is a building owner who understands the business proposition and value of data who can execute by organizing a small group to implement a structured data management system.
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