May 2015 |
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The best
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.
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Have
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.
Naming Conventions
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.
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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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