Between the Poles

Integrating geospatial into construction: the challenge

I spent most of last week at the Geospatial World Forum 2013 (GWF 2013) in Rotterdam, which was an amazing event, because of its focus on monetizing geospatial value in vertical industries,  Industries for which there were symposia at GWF 2013 include construction and infrastructure, electic power and gas, mining and exploration, water as a resource, water distribution management, and agriculture in addition to more traditional sectors such as land management, photogrammetry and the environment.

I spent most of my time in Construction and Infrastructure sessions.  There were many absolutely fascinating pesentation on the applicaton of geospatial technology in this sector.  Among the most far-reaching in terms of potential impacts were three or four talks that explicitly addressed the challenge of finding a practical way to integrate geospatial into construction processes.

Value of geospatial information

To put this in context, there is a strong drive in the Netherlands to integrate geospatial information into govenrment organizations.  Geonovum is leading the charge in this area.   By way of motivation there is a very interesting cost-benefit analysis in the context of the European INSPIRE initiaive by Ecorys and Grontmij in November 2009.  The scope of study was the cost and benefits of the collection, maintenance and dissimilation of geographic information, but just within governmental organizations in the Netherlands.  The study did not attempt to estimate the value of geospatial information to society as a whole.  It concluded that over 15 years, the total net benefit to government organizations in the Netherlands would be € 34 million (Ralf Duinmeijer, Joulz ICT private communication).

Cost of poor interoperability

To put this in the context of interoperability and what poor interoperability costs the economy and individual firms, in 2004 in a remarkable study the U.S. National Institute of Standards and Technology (NIST) attempted to identify and estimate the efficiency losses in the U.S. capital facilities industry resulting from inadequate interoperability.  The NIST study focussed on interoperability problems attributed to the highly fragmented nature of the industry, the industry’s continued paperbased business practices, a lack of standardization, and inconsistent technology adoption among stakeholders.  It concluded that inadequate interoperability cost the U.S. capital facilities industry $15.8 billion in annually in 2002, but qualified the conclusion by saying that this is likely a conservative figure because there were additional significant inefficiency and lost opportunity costs associated with interoperability problems that were beyond the scope of NIST analysis.

At GWF 2013 it was reported that Rijkswaterstaat, responsible for public works and water management as part of the Dutch Ministry of Infrastructure, has estimated that poor interoperability costs it € 800 million per year.

Barriers to integrating BIM and geospatial

Bram Mommers, who is with ARCADIS Netherlands, set the stage by looking at what the barriers are that are hindering the integration of geospatial into the constrcution process.  (ARCADIS is a large international company that provides consultancy, design, engineering and management services in the fields of infrastructure, water, environment and buildings.)

Traditionally the challenge has been that civil engineering on one hand and geospatial on the other have been different cultures.  The way Carl Steinitz put is that they work at different scales.  Geospatial scientists deal with the universal, engineers with the very specific. 

Bram gave some examples of these parallel worlds. Geospatial folks make maps, engineers and architects make drawings.  Engineers and architects use CAD or BIM design tools.  Geospatial folks use GIS.  The geospatial standard for buildings and infrastructure is CityGML.  The AEC standard for BIM models is Industry Foundation Classes (IFC).

ARCADIS has been involved in projects that integrated geospatial into the desing process.  On the HOV Nijmegen project it was found that integrating geospatial and engineering design in a single database resulted in a single copy of each data element and multiple use.  It simplified communication and increased the quality of the final design.  It also enabled automated analysis of the consequences of design choices with the result that the planning cycle was shorter.   Bram mentioned several other projects that benefitted from the integration of geospatial with the construction process.

Based on their experience with these projects, Bram and his colleagues concluded that there are three main barriers to the integration of civll engineering and geospatial.

• Semantics - for example, different terms used for the me things by geospatial analysts and civil engineers and designers
• Different topology - examples,  (1) geospatial uses point, lines, and polygons; CAD/BIM uses splines, nurbs, and other parametric curves and treats polygons in a different way from geospatial topology; (2) features with location vs objects with location as an attribute
• Data formats - for example, geospatial data is stored in shape files, GML, and CityCML; CAD/BIM uses DWG, DGN, RVT files, and IFC

Mapping semantics

To address the first issue of semantics, a Dutch initiative called Concept Library (CB-NL) sponsored by the Dutch Council on Building Information (BIR), a joint government and industry initiative, has been created with the objective of developed an open, on-line system to map between the terminologies used in different domains.  The goal is a single integrated model for construction (buildings and infrastructure) that would allow design, construction, maintenance and operations to share the same data.  The concept library would be extended to include geospatial.  The overall goal as Bram stated it is

• Ontology for the build environment - multiple sets of domain terminologies mapped on to it
• One language
• Combines geospatial and construction

The impacts of this appproach that Bram sees are

• Store once, use multiple times - avoid redundant data
• Integrated information management - based on data custodians
• Geolocation as a property of an object - in additon to features

Bram listed a number of organizations in the private construction sector that are supporting this initiative.

Economic value of big geospatial data could reach $700 billion/yr by 2020

McKinsey Global Institute published a report Big data: The next frontier for innovation, competition, and productivity that analyzes the state of digital data, how it is used in different domains in both the private and public sectors, and offers suggestions for policy makers. In addition to looking at big data as a whole, the report examines five areas in detail including personal location data.

Real-time location data generated by mobile phones and other devices has created an entirely new set of location-based services from navigation to pricing property and casualty insurance. Personal location data is a new horizontal application domain that includes industry sectors from utilities to insurance to transportation. The growing smart phone market is creating an exponentially growing volume of location-aware data.  McKinsey sees this domain as a hotbed of innovation that has the potential to create significant value for consumers.  For example, use of real-time  traffic information for navigation will create a quantifiable consumer benefit by saving time spent traveling and fuel consumption. McKeinsey expects the economic value these innovations create to far exceed the revenue generated by service providers.

Economic value

Mobile phones with GNSS chips have created a revolution will continue over the next  decade. This personal location domain offers the potential for huge new value creation over the next ten years that McKinsey estimates at more than $100 billion/yr (about 0.14% of world GDP) in revenue to service providers and as much as $700 billion/yr (about 1% of world GDP) in value to consumer and business end users. Realizing this value will require investment in technology, infrastructure, and personnel as well as appropriate government action.

McKinsey's detailed analysis of the major applications of personal location data finds that, in ten years’ time, these applications could create value of $100 billion/yr or more for service providers  primarily from sales of navigation hardware and revenue from LBS, mobile LBS premiums, and geo-targeted advertising.

McKinsey estimates that by 2020 the benefits (difference between willingness to pay and the cost of applications) that customers, consumers and businesses, will enjoy from location-based applications will reach as as $700 billion/yr. Most of this, about 70 %, will be the consumer benefit from time and fuel saved by using GNSS navigation systems including those with real-time traffic information and mobile LBS applications. The remaining 30 % of the benefits will be through location-enabled applications such as geo-targeted mobile advertising.  Smart navigation applications are estimated to provide $500 billion in value to global consumers in time and fuel saved by 2020. Geo-targeted advertising could represent more than 5 percent of total global advertising spending by 2020.

For comparison, a recent study prepared for Google by Oxera Consulting Ltd in the UK estimated global revenues from geospatial products and services to be $150-$270 billion per year.  The geospatial industry is estimated to be growing by 13% per year through 2016.  These numbers were estimated using a different methodology to McKinsey's. The lower estimate of $150 billion/year was estimated using a bottom-up approach based on the Bloomberg BICS classification of companies worldwide and assumptions about allocating the revenue from companies that provide geospatial in addition to other services such as Trimble.  The $270 billion number was estimated by scaling up the US revenue estimated by Boston Consulting Group to come up with a world estimate.

Personal location data

McKinsey includes sources of personal location data that locate an individual to at least within a couple of city blocks in an urban settingin its analysis.

• Credit and debit card payments from cards processed at point-of-sale (POS) terminals and  automated teller machines. In 2008, there were 90 billion to 100 billion transactions of this type worldwide.
• Mobile phones - the location of such devices can be triangulated from cell-tower signals.  In 2011 there were about 6 billion of these.
• Smartphones with GPS - about 600 million devices in 2010 and the number is growing at about 20 % per year. Many smartphones also have Wi-Fi networking capability, which can be linked to a physical location of a Wi-Fi network.

In the future McKinsey expects indoor location to become more important.  They mention Shopkick, which allows merchants to track their customers from when they walk into a store, and Path Intelligence, which can track foot traffic within malls or amusement parks.

McKInsey's research estimates that the global pool of personal location data was at least 1 petabyte in 2009 and that this pool is growing by about 20 % a year. 

Location data generated by smartphones is growing at double the average rate of growth for all location data.  Asia is the leading region for the generation of personal location data because so many mobile phones are in use there. In 2010 the regions with the largest number of cell phone users were

• China 800 million
• India 650 million
• North America 300 million.

Applications of personal location data

McKInsey has identified three major categories of applications of personal location data.

• Location-based applications and services for individuals including smart routing, automotive telematics, and mobile-phone based location services
• Organizational use of individual personal location data that includes geo-targeted advertising, electronic toll collection, insurance pricing, and emergency response.
• Macro-level use of aggregate location data that includes urban planning and retail business intelligence.

Barriers to use of personal location data

Concerns about privacy and security was identified by McKinsey as a major barrier to future expansion of the use of personal location data. Laws are unclear about who owns that data and how it can be used.  McKinsey believes that a policy and legal framework that clearly describes the permissible and prohibited use of these data would be beneficial for all stakeholders.

For policy makers, McKinsey sees that a priority is incentives for innovation are in place including developing an up-to-date framework for intellectual property rules and rights, funding R&D in potential breakthrough areas, and ensuring that the infrastructure, including spectrum policies, is optimal.

Methodology

By looking at the value chain of location-based applications, McKinsey examined both the amount of data generation and the potential to create value.  McKInsey estimated the amount of personal location data generated in each category of application orsource device and in different geographic regions using the installed base of devices, usage behavior, and the frequency with which data are generated. To assess the potential value that data can generate, McKinsey estimated the economic value of each application to end users—individual consumers, enterprises, and government organizations.

Privacy and personal geographic data

At the Creating the Policy and Legal Framework for a Location-enabled Society conference in Boston, Kirk Goldsberry, who is a Visiting Scholar at the Center for Geographic Analysis at Harvard, gave a fascinatng presentation with the help of two of his students on the topic of personal geographic data and privacy.

According the the Federal Trace Commission, which is responsible for protecting privacy at the Federal level, the 4 holy data types are

• Financial data
• Medical data
• Data about children
• Geographic data

Goldsberry's main point was that the first three are treated as very sensitive and there is a legal framework to ensure these data types are protected.  When it comes to geographic data, on the other hand, there is very little by way of policy or legal infrastructure ro protect personal geographic data.

As an example he cited the iPhone.  About two years ago it was disclosed that iOS devices maintain a database that potentially could be used to track the movements of users. In response Steve Jobs in an email said that "We don't track anyone. The info circulating around is false."

Without the user's explicit consent iOS doesn't record GPS location, but does record the location of cell towers and Wi-Fi access points, which can be used to create a clear general track of a user's movements. 

To show what was possible with this iOS database, two of Goldsberry's students voluteered to carry an iPhone (with location disabled) for a couple of weeks.  Goldsberry used the iOS database recording cell towers and Wi-Fi access points to put together maps that showed pretty clearly where the students had been including long distance trips and their daily routines.  For example, one student had travelled to Seattle for a conference and had stayed in a hotel.  The student's location at and around the hotel and conference were not hard to discern.  The student went to a Mariner's game and from the location determined through the iOS database it was very clear that the student was at Safeco Field.

Limited legal and policy protection for personal geographic data

I interpreted what Goldsberry showed as not targetting Apple specifically, but that there is very little policy and legal protection for personal geographical data.

A number of speakers made the point that technology, including GPS and GIS, has moved so rapidly and regulation and legislation move so slowly that for personal geographic data, the horse has already left the barn.  It is too late to close to the door. 

Experiment

There is the risk that hasty legislation or regulation on privacy and personal geographic data could prevent or inhibit the very real social benefits the technology is capable of delivering.  The approach that several speakers recommended is to enable governments to experiment, so that regulation or legislation on privacy of personal geographic data is able to optimally walk the fine line between protecting privacy on one hand, and enabling the social beneifts the technology is capable of on the other.

I commend Kevin Pomfret, Excecutive Director of the Center for Spatial Law and Policy, for organizing such an important conference at such a critical time for geospatial technology.

Location-enabled Society: Mapping tweets using real-time big data technology and privacy

In a very appropriately titled session Taking Society's Pulse in Real-time at the Creating the Policy and Legal Framework for a Location-enabled Society conference in Boston, one item really got people's attention focussed on the issues that arise from combining location with personal data. TweetMap is a technology that visualizes a large number of tweets on a map of the world. This is not the first time I have seen tweets mapped.  But what really got people's attention is that a speaker showed how to drill down to your neighbourhood and see what the people next door are tweeting about.  Of course you can do this without a map by simply following your neighbors on Twitter.  But somehow mapping it makes it seem more intrusive, even invasive to some people. In another demonstration, Tweetmap was used to show how a person sailing in the Caribbean could be tracked as they tweeted from their boat.

To be tracked geospatially on Twitter requires that you explicitly agree to geolocation tracking for Twitter on your iPhone or Android device.  For example, on an iPhone the geolocation option allows you to make your location known to others. Apps such as Facebook or Twitter for iPhone can report your location as well as the messages you post.  The iPhone requires that these applications obtain your permission before they can be enabled.  Apparently only about 2-4% of smart phone users, mostly younger folks, agree to this.  After seeing a Tweetmap drill down, I would expect that some people might have second thoughts about agreeing to the gelocation option. And in the not too distant future this will be possible in real-time on inexpensive hardware with open souce software.

TweetMap is an instance of MapD, a massively parallel database platform being developed through a collaboration between Todd Mostak, (a researcher at MIT), and the Harvard Center for Geographic Analysis (CGA).  Currently the tweet database starts on 12/10/2012 and ends on 12/31/2012 and contains 125 million tweets.  The database can be queried by time, space, and keyword.  The ultimate objective is to be able to query billions of tweets live in real-time.  In this case real-time means from tweet to tweet on a map in under a second.

MapD is a general purpose SQL database that can be used to provide real-time visualization and analysis of very large data sets.  MapD uses commodity Graphic Processing Units (GPUs) to parallelize compute intensive tasks such as querying and rendering very large data sets on-the-fly.  MapD runs on inexpensive hardware ( ~$1000) and is intended to be open source.

US Government releases national strategy for civil Earth observation

The National Science and Technology Council has released a National Strategy for Civil Earth Observation..  Currently, 11 Federal departments and agencies participate in over 100 Earth observation programs which together cost billions of dollars annually. The Strategy provides a mechanism for assessment and planning across all the Federal agencies engaged in Earth observations. It outlines a process for evaluating and prioritizing Earth-observation investments according to their social value in critical areas including agriculture, climate change, disasters, water resources, and weather.

The Strategy will be used as a blueprint for future investments in US Earth-observing systems. It will also support  the United States’ commitment to work with international partners through the multi-national Group on Earth Observations (GEO).

The National Strategy includes two main elements

• A policy framework and method for Federal Government assessment of Earth observations (data and products derived from Earth observing systems).
• Data management guidelines for improving information delivery systems for Earth observation data.

 

Providing web access to usable open geospatial data

The principle of free and open access to government geospatial data has been adopted by many governments including US Federal, Canada, Japan, South Africa, Brazil, California, and by the City of Vancouver and other cities.  But being able to access prepared maps and other derived material is just a first step, governments need to provide access to raw geospatial data in commonly used Web-friendly formats. Tim Berners-Lee, in Government Data Design Issues, is a strong advocate of making raw data accessible over the web including supporting standard Web methods, most critically, searching.

GeoREST

I blogged previously about an initiative called GeoREST developed by Haris Kurtagic and implemented by Jason Birch at Nanaimo for property records that attempted to enable visual browsing of open datasets, support standard search engines, plus enable simple access to raw geospatial data in web-friendly formats such as GeoJSON.

What do users want ?

Brian Timoney has reported metrics and a analysis of  how the public actually uses local goverment web maps. He has also created a minimally viable property lookup service.

In light of this Bill Morris has developed an alternative way of accessing public datasets that he feels is compelling to technicians as well as to the lay public, as an example, a template geoportal for accessing multipurpose public data, specifically, building records.

He targeted his geoportal on two audiences:

1. Citizens who want to access their own zoning information and permit history fast.  These folks can search for address, see buildings in context, and get the basic information in one minute or less.
2. GIS analysts who want to download raw building footprint geodata for urban planning, disaster response or cartography.   Thes folks acn download all the features within the current view extent, in a choice of interoperable formats.

Value of geospatial services to the global economy

Google released a report What is the economic impact of Geo services ? earlier this year prepared by Oxera Consulting Ltd in the UK.

What are geospatial services ?

Oxera incuded all interactive digital mapping and location-based data,  products, and services in its definition of geospatial services.  This includes providers of satellite imagery, digital maps, satellite positioning signals (GPS/GNSS), navigation devices, geographic information systems (GIS), and geospatial expert service providers.  Digital maps include online maps and locally stored maps, but not hardcopy maps.  Geospatial products and services generate direct revenue for companies such as ESRI, Garmen, or Digital Globe.

What is value ?

The study aims to quantify the impact of geospatial services on the world economy and consumer welfare.  It breaks these impacts down into

• direct effects - revenue generated by firms developong and providing geospatial data, products and services
• consumer effects - the benefits that consumers, business and government experience from using geospatial services from geospatial services
• wider economic benefts - productivity and efficiency improvements resulting in cost savings from geospatial services

Economic impact of global geoservices

Direct revenues

Global revenues from geospatial products and services as defined by Oxera is estimated to be $150-$270 billion per year.  The geospatial industry is estimated to be growing by 13% per year through 2016. [ There are important assumptions that led to these numbers.  The lower estimate of $150 billion/year was estimated using a bottom-up approach based on the Bloomberg BICS classification of companies worldwide and assumptions about allocating the revenue from companies that provide geospatial in addition to other services such as Trimble.  The $270 billion number was estimated by scaling up the US revenue estimated by Boston Consulting Group to come up with a world estimate.]

Gross value added (GVA) is the grand total of all revenues ( from final sales and subsidies minus direct taxes ) which are incomes into businesses.  Geospatial services are estimated to have a global GVA of $113 billion/year, which is about 0.2% of the world's GVA of $70 trillion.

Consumer benefits

Geospatial services provide benefits (not including direct purchases of geospatial products and services) to consumers.   For example, enabling consumers to find the nearest Thai restaurant in seconds rather than leafing through the yellow pages and looking up the location on a map saves time.   Finding the fastest route to the nearest hospital saves time and may actually save lives.

Some of the consumer benefts of geospatial services include time savings, fuel savings, emergency response, education, and competition.

Examples of categories of consumer benefits include more efficient navigation, estimated to provide benefits of  $22 billion/year, and educational benefits estimated to amount to $12 billion/year.  Faster emergency response to cardiac arrests is estimated to potentially save 152 lives/year in the UK.

Wider economic impact

Geospatial services also make users more efficient.  For example, a trucking company that has installed GPS trackers on its vehicles and uses location-aware routng software will be more efficient, delivering items faster and more efficiently.  There are also indirect benefits to the general public in improved safety.  By getting things to end users and businesses faster and more safely, geospatial services facilitate economic activity.

For example, GPS/GNSS is estimated to provide $10 billion in cost savings to the global economy.  Geospatial  services are estimated to save 1.1 billion hours of travel time/year and to reduce fuel demand by 3.5 billion liters of gasoline/year.

Thanks to Dr Bob Austin for pointing me to this.

SPAR 2013: Integrated geospatial, LiDAR and design datasets for large infrastructure construction projects

Kevin Gilson, of the Project Visualization group at Parsons Brinckerhoff (PB), gave an overview of how PB manages 3D+ datasets in support of design and construction for large infrastructure projects such as the San Francisco-Oakland Bay Bridge, the I-95 New Haven Harbour Crossing /Q-Bridge reconstrcution, and the Alaskan Way viaduct project.  He showed how the project visualization team leverages geospatial data, LiDAR data, design data and construction planning data together in large integrated datasets that concurrently support visualization, stakeholder communication, design, construction planning and site logistics.

PB has more than 30 staff dedicated to project visualization.  That included folks who do 3D modeling, design visualization, web design, and programming.  3D technologies include building information modeling (BIM), 3D design, virtual desgin and construction (VDC) and laser scanning (LiDAR).

3D modeling for design and construction

Some of the reasons that designers and construction firms are adopting 3D technology are the serious limitations of 2D sheet sets, still legally required fro s-builting but very unreliable, the design efficiencies of 3D parametric models, and the limitations of siloed project data.  PB has adopted the concept of project information models or PIMs, that integrate information about all aspects of the design and build process and that potentially can flow data through for operations and maintenance.

3D modeling and model-based design are used by PB for design validation, clash detection, and parameteric modeling, civil integration management, 4D modeling (time+3D), 5D (cost+time+3D), and design visualization.  Model-based design involves integrating CAD, GIS, survey, analytics, BIM and associated databases, and 3D visualization typically in a vitual gaming environment.

Construction firms in particular see tremendous advantages in 4D models that integrate design and gespatial data and allow the construction team to virtually build the project so that they can check staging and construction sequencing and site logistics virtually.  5D and higher dimensions allow them to add additional metrics including cost, resources, materials, and equipment.

The benefits that PB realize by this integrated approach based on 3D+ dataest include finding and fixing conflicts between different design groups (HVAC, plumbing, electrical, structural, and so on) during the design phase rather than during construction when clashes are much more expensive to fix.  Another benefit is being able to quantify things using analytics, so  that decisions are data-driven rather than subjective.

A major benefit is less re-work is required reducing the risk of cost and schedule overruns.  A big advantage is improved communication and coordination between all project stakeholders, and especially with non-technical decision makers.  Being able to see photorealistic visualizations of what the project is going to look like makes a huge difference in communicating with politicians and the public.  PB uses gaming technology making it possible to experience a project before a shovel has gone into the ground.  For example, on highway projects, PB's visualization makes it possible to drive the highway and even the detours required during construction in a virtual environment so that the public can experience the changes and be prepared for them before they actually happen.

Another important benefit that Kevin sees from a project approach that includes visualization is that "sexy deliverables" get peoples attention, within the project team as well as with external stakeholders.  Several other speakers at SPAR 2013 also emphasized the importance of the "sexiness" factor.

Laser scanning in construction

Kevin described a number of applications of laser scanning (LiDAR) as part of the 3D constrcution process.  A major application of LiDAR is contruction monitoring, capturing construction progress as well as being able to automate the process of checking for divergence from design when contractors for a variety of reasons don't build what is designed. 

Another important Laser scanning application is accurate and reliable as-builts.  At SPAR 2013, speaker after speaker in different sectors of the construction industry reiterated that current 2D as-builts, still legally required, are unreliable and rarely looked at by anyone post-construction.  Marco Vidali Castillo at ICA which is responsible for the Autopista Urbana Sur project in Mexico City  gave an example of how trying to use 2D as-builts can lead to problems necessitating major re-engineering.  LiDAR scans of a completed project can provide the reliability that 2D as-built sheet sets lack.  On the Autopista Urbana Sur project Marco says that ICA intends to deliver LiDAR scans as well as the legally required 2D as-built sheet sets.

3D modeling and sustainability

There are also benefits from the perspective of sustainability to PBs project approach. Collaboration typically has relied on the exchange of paper documents which on a large project can involve many thousands of paper documents.  Collaborating in a virtual environment can dramatically reduce paper flow while improving the quality of communication.  It can also improve traffic flow and resource management during construction, thereby reducing emissions. A life-cycle approach to data management during design and construction, with data being reused for operations and maintenenace can reduce rework resulting in significant efficiencies.  

Selecting software tools

The PB project visualization team takes a best of breed approach in selecting software for 3D modeling and visualization. An important criterion in selecting tools is interoperability between the different technologies.  Currently the software stack that PB relies on includes

Geospatial

• ESRI
• Global Mapper
• Infraworks (Autodesk Infrastructure Modeler)

CADD

• Microstation InRoads
• AutoCAD/Civil 3D
• Solidworks

Visualization

• 3ds Max
• Sketchup
• Realtime - UDK, Unity

Collaboration/4D

• Navisworks

SPAR 2013: BIM + GIS based facilities management at Denver International Airport

At SPAR 2013 Dennis Rodriguez, Project Manager at Denver International Airport (DIA), and Daniel Stonecipher of Immersiv, gave a fascinating presentation on how they combined a BIM-based design and construction process with GIS  to create a facilities and operations management (FM/OM) solution for managing DIA's infrastructure.

DIA is a small city and managing its infrastructure involves many of the same probelms that utilities and municipal governments have to deal with.  As-builts are unreliable or not existent,  which meant that DIA really didn't know reliably where their assets were.   DIA has nine million CAD files which meant a major data management problem.  Their maintenance program  was dysfunctional because they didn't have the information they required to rationalize it with a data-driven process.  They had a lot of redundant data because of silos of information in different departments using different applications.  The most important impact of all of this was subjective decision making during the budget planning process, characterized by the so-called HiPPO (highest paid person's opinion) problem.

Their ultimate goal was data driven processes that supported predictive maintenance and objective metrics for decision making especially in prioritizing projects during the budgeting process.

The way they addressed this was by a combination of data normalization and business process rationalization.  The swiitched to an integrated building information management (BIM) design and construction process that produced a normalized data stream.  During design and construction the data that was required for facilities management and operations (FM/OM) was collected.  This involved collecting and validation existing data and developing continuous data and process management.  The result was FM/OM ready BIMs (both horizontal and vertical) and current relational data structures.

A critical aspect of their solution was that all data including BIM models was geolocated, which  made it possible to load all the data into a GIS linked to Maximo.  Geolocating all their facilities made it easy for them to organize maintenance work on different types of infrastructure concurrently, so that they could excavate once for multiple utilities rather than different crews reexcavating at the same location multiple times.

Dennis and Daniel said that a number of airports are interested in DIA's solution.  I would expect that universities, municipal governments,  and anyone who needs to manage infrastructure in a campus or municipal environment would find DIA's solution worthwhile investigating.

SPAR 2013: Digital highways require integrated engineering and geospatial data

At SPAR 2013 I had the opportunity to hear very forward looking presentations by Ron Singh, Chief of Surveys/Geometronics Manager at the Oregon Department of Transportation.  What Ron sees in the future and what motivates a lot of what Don sees needs to change in the highway construction process is autonomous vehicles, which will provide a major motivation for what Ron refers to as digital highways.

Automation over the last 25 years

If you look at the last 25 years there has been quite a lot of automation in the form of survey automation such as electronic data collection, GPS, and basic 3D laser scanning;  design automation such as computer aided design and drafting, and a bit of construction automation.  The primary focus has been on speeding up the project development process, but the end goal remains  2D paper construction documents.  Some people have been using what is called 2..5 D, a 3D roadbed prism with 2D objects on it.  In Ron's view the current way of designing and building highways has reached the end of it's lifetime and a complete transformation to a new paradigm is required.  The way Ron refers to this is standing the current process on its head and I blogged about it yesterday.  Fundamentally it involves intelligent 3D models replacing the current as-builts and a process that speeds up project development because it leverages existing engineering data rather that requiring a complete resurvey at the beginning of every project..

A new paradigm for intelligent highways

The objective is intelligent highways that will support autonomous and partially autonomous vehicles.  The new paradigm needs to be data-centric and real-time.  It will involve automated construction.   From a data management perspective it will require highway infrastructure lifecycle management, which will involve a very different approach to the survey/design/construct/maintain process that is currently used for highway projects in North America.

First of all, it will involve geospatially enabled 3D digital data. A key requirement is a low distortion geospatial coordinate system that will provide the foundation for geolocatiig all infrastructure including utilities.  It will require interoperability using industry standards for data exchange. Most importantly it will support a construction process that uses post-construction surveys to replace as-built plans with a full 3D engineered model that supports GIS/engineering data integration. 

It will require geospatially-enabled enterprise data management including version control and the ability to search for things geospatially.  It will provide tools for geospatially enabled asset management.  It will provide a framework for developing and maintaining engineering and geospatial data including 3D engineered models as well as scanned data for existiing structures for the entire life cycle of a highway.