Between the Poles

Modeling downtown The Hague to reduce energy consumption

I've blogged previously about a project by the Los Angeles Community College District, the largest community college district in the U.S., create 3D BIM models of all the buildings on the LACCD  campuses.  One of the most important motivations for creating these models was that BIM models would faciliate energy performance analyses of LACCD buildings.

Reducing energy usage in The Hague

At the Geospatial World Forum 2013 (GWF 2013) conference in Rotterdam Martinus Vranken and Jene van der Heide of the Dutch Kadasre described a project to model a square kilometer of downtown The Hague with the objective of reducing and stabilizing energy usage and costs for the entire area.

The Dutch Ministry of the Interior has initiated a joint project with the Municipal government of The Hague to reduce and stabiize energy usage and costs in downtown The Hague, including the use of renewable energy.  The study area is roughly about a square kilometer of The Hague where the buildings are large and mostly owned by the National and Municipal governments.  The Dutch Kadaster has been contracted to provide an information system to assist the Ministry of Interior in developing a business case.

The Kadaster has combined its own data with that from other government agencies

Kadaster

• Topography
• Ownership and building information
• Energy labels
• Underground grids electricity, gas and heat
• Monuments

Ministry of the Interior and City of The Hague

• Energy consumption
• Employees
• Surfaces suitable for solar panels
• 3D model

Province of South Holland

• Heat pump facilities
• Solar probability map
• Wind probability map

Ministry of Economic Affairs

• Geothermal facilities
• Permits for geothermal concessions

The Kadaster has assembled land registry information like ownership, monument status; building information such as year of completion, surface area, energy labels, energy indices; information on underground networks like heat networks, gas and electricity grids; together with government information on heat pump facilities, energy consumption of buildings, and available building facade area suited for solar panels.  Combining this information provides a tool that the Ministry is using to develop the busness case for a new form of energy supply that is reliable, clean, and affordable.

The two main challenges have been to translate this information to fit the perspective of the Ministry of the Interior and structuring the information so that it can be reused for similar projects in the future.

The next steps  on the project are data collection and processing, defining business case,  and tendering and then transition to the new energy supply.

The lessons learned so fare are interesting.  First of all, visualization using a geospatial information platform has been vital in developing the business case.  This approach has provided important Insight into the energy and heat exchange possibilities between buildings and enabled exploration of the possibilities of solar, wind and geothermal energy.  The geospatial approach also provides a platform which the private sector can use as a foundation in preparing bids for the project.

Executive order makes open and machine readable data the default for the US Federal Government

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.

An Executive Order has been released by the White House which makes open and machine readable (raw) data the default for government information.

"To promote continued job growth, Government efficiency, and the social good that can be gained from opening Government data to the public, the default state of new and modernized Government information resources shall be open and machine readable. Government information shall be managed as an asset throughout its life cycle to promote interoperability and openness, and, wherever possible and legally permissible, to ensure that data are released to the public in ways that make the data easy to find, accessible, and usable. In making this the new default state, executive departments and agencies (agencies) shall ensure that they safeguard individual privacy, confidentiality, and national security."

Open modeling standard released for public comment by OGC and OpenMI

The Open Geospatial Consortium (OGC) and the OpenMI Association (OpenMI) have released the proposed Open Modelling Interface Version 2 (OpenMI) standard for public comment.  This standard defines a standard apporach for independently developed computer models of environmental processes to exchange data as they run.
 
The original driver for the standard was the European Water Framework Directive and its requirement for an integrated approach to water management. The European Commission co-funded the research and development of a generic model interface, which is the OpenMI.
 
The immediate goal is to enable the  integrated modelling needed to understand Earth system processes.
 
Environmental modelling is not the only application of integrated modelling. For example, a possible shorter term application will simply be in enabling developers to convert their existing large, and often unmanageable, applications into sets of linkable components. This could change the modelling market from one for complete systems into one for components and services.
 
The documents being released for comment can be viewed and downloaded.  Comments are due by June 1 2013.

Oracle Spatial and Graph to support NURBS

At the Oracle Spatial and Graph User Meeting, the folks from Oracle outlined some of the things to expect in the next version of Oracle 12c.  I was very impressed.  All of the below is my interpretation of what will be in Oracle 12c.

Parametric curve support

The really big news for the architecture, engineering and construction community (AEC) who use CAD and BIM applications is that Oracle 12c is expected to support NURBS (non-uniform rational basis spline) a type of parametric curve widely used in the design space.  According the Siva Ravada the support will be very general and will be able to handle different ways of representing NURBS. Up to now the only parametric curve supported by Oracle was circular arcs.

To me it looks like Oracle is taking a major step toward being able to store natively and manipulate (in some cases by stroking) the parametrized curves used by CAD and BIM applications.  There is a lot of CAD and BIM data out there and being able to store it and manipulate it in Oracle Spatial and Graph is going to be a game changer.

Orthorectification

Oracle is providing support for orthorectification embedded directly in the database.  This will have important implications for the industry.   Up to now, you had to pull the image out of where ever it was stored, transfer it over the network to someone's application often from an image processing company to orthorectify it, and then transfer it back to store the image or stream it to the end user.  With 12c you will be able to orthorectify images in the database.  This is in line with Oracle's objective of bringing processing to the data, rather than the data to processing.

Raster algebra

Oracle 12c will also have support for raster algebra, again in the database.  For example, you will be able to average in the database12 months of national temperature data stored in monthly raster files.

GDAL and PDAL support

Oracle supports the open source GDAL raster libraries, the industry standard developed by Frank Warmerdam (now with Google) and used by just about everyone for accessing raster images including ESRI.  PDAL is a similar type of open source library for point clouds developed by Howard Butler and Michael Gerlek.

3D

Oracle supports three types of 3D data.  3D vectors, point clouds and terrain (surfaces).  Oracle 12c will provide full support for 3D geodetic data, lon lat and elevation in meters or feet.

Performance

Oracle has developed a new engine for handling massive point clouds.  Dan Geringer showed impressive results for a 2.8 billion point point cloud (286 gigabyte file). 

Processing vector geospatial data is reported to be 50 to 100 times faster in 12c than in 11g. 

Raster operations have been parallelized which can dramatically reduce the time it takes for these operations.

Engineered Database

Since acquiring Sun, Oracle has become a hardware and software company and is offering integrated hardware and software solutions that offer extremely good performance characteristics.  For example, processing LiDAR data benefits from hardware acceleration on engineered machines such as Exadata boxes.

Bundled data

Oracle is planning to bundle vector data from Nokia (Navteq), TomTom and others.

Oracle Spatial and Graph

The name of the product is changing to Oracle Spatial and Graph partly because it has had graph capabilities (network and RDF semantic) already for several years.  But probably more importantly because the demand for graph capabilities is accelerating, especially RDF semantic graphs for linked data, text mining, and for social media analytics, according to Xavier Lopez.  Even Oracle's NOSQL database (aka BerkeleyDB) is apparently getting graph capabilities.

Open source: then and now

I was asked participate on a panel on open source geospatial organized by Eclipse LocationTech at the Location Intelligence in Washington DC.  I decided to look at how software had changed since the early days of open source which I tend to tie to the formation of the Apache Software Foundation (ASF) in 1999.  What I found was that the proprietary and open source software landscape has changed dramatically in the last 13 years.  Here are some statistics that provide an indication of just how dramatic the change has been.

Apache Software Foundation

Apache which started off supporting the Apache http server developed at the National Center for Supercomputing Applications (NCSA) now supports over 100 top level projects. 

According to a Netcraft survey of 649,072,682 web sites in April 2013

• Over 51% run Apache http server
• Almost 20% run Microsoft IIS

Microsoft

In 1998 the infamous Halloween docs were leaked in which Microsoft identifed open source as a threat and discussed ways of combatting it. 

April 2013 is the first anniversary of Microsoft Open Technologies, Microsoft's own open source division.  Microsoft also has another open source group, Outercurve, where more than 50% of the projects are run by non-Microsoft developers.  Microsoft announced that Visual Studio now supports Github.

Browsers

Until several years ago, Internet Explorer was used by over 90% of users.  The most recent statistics from W3Schools for April 2013 show marketshare for browsers is dominated by open source browsers, Chrome and Firefox.  IE is a poor third now.

• Chrome 52.7 % (increasing)
• Firefox 27.9 % (decreasing)
• IE 12.7% mostly IE8 and IE9 (declining)
• Safari 4% (decreasing)
• Opera 1.7% (decreasing)

Operating systems on personal devices

Until several years ago,  PCs running MS Windows were used by over 90% of users.  Now handheld devices such as smart phones lead PCs in annual sales.  IDC 1Q2013 statistics for smartphone shipments show that in the last quarter, open source operating systems are dominant

• Android 75.0%
• iOS 17.3%
• Windows Phone 3.2%
• Blackberry OS 2.9%
• Linux 1.0%
• Symbian 0.6%

Software procurement

In many large organizations until recently the procurement playing field was tilted in favour of proprietary cmmercial and against open source software.  In 2009 the Department of Defense (DOD), the world's largest IT organization, issued a memorandum that leveled the playing field by stating that “OSS [open source software] meets the definition of commercial computer software”.  The memorandum went on to identify some of the benefits of OSS for DOD.

• Fewer defects - many eyeballs means fewer defects
• Flexibility - easier to customize and adapt
• Multiple vendors instead of one - avoids vendor lock-in
• Unrestrictive license - simpler to deploy
• Cost advantage - when many copies are required
• Cost sharing  - reduces DOD costs
• Prototyping and experimentation - OSS particularly suitable for this

Large IT systems

I blogged earlier about a study by Henrik Ingo that found that the world's largest OSS projects including Linux, KDE, Apache, Eclipse, Perl+CPAN, Mozilla+Addons, Gnome, Drupal and GNU are collaborative community projects governed by non-profit foundations like Apache and Eclipse.  These projects are10 times larger than the largest single-vendor projects.  Ingo recommended that vendors seriously consider participating in a collaborative community run by a  non-profit foundation because they  could expect 10 time growth in the project and its addressable market.

Malware

Several years ago virtually all of the world's malware exploits targeted MS Windows.  Now according to F-Secure, exploits against mobile devices are exploding.  In 1Q2013 the main target for mobile exploits is Android which is open source.

• 91.3% Android (49% increase over 4Q2012) *
• 8.7% Symbian
• Apple, Microsoft, and Blackberry - free of malware

In 1Q 2013 for the first time Android malware was identified by F-Secure as being distributed by email in addition to apps.

Geospatial open source

The Open Source Geospatial Foundation was formed in 2006 supported by Autodesk.  Prior to that geospatial software was dominated by proprietary vendors ESRI, Intergraph, Autodesk, Bentley, and others.  Now there are many open source geospatial companies that provide alternatives to proprietary vendors.  They primarily rely on OSGEO software such as PostGIS, OpenLayers, MapServer, GeoServer, and others.  Earlier this year ESRI acquired GeoIQ and now offers both open source and proprietary software.

Open geospatial standards

One of the key reasons for the rapid expansion in the deployment and use of open source geospatial software solutions is the open standards developed by the Open Geospatial Consortium notably the SQL Simple Feature Specification, KML, WMS, WFS, GML, and CSW.  Open source and open standards are very different things, but open source gravitates to open standards.  It is hard to imagine that geospatial open source would have progressed as rapidly and widely as it has without the OGC standards.

Reusing integrated geospatial and design data across the construction lifecyle

One of the most important things that impressed me at the Geospatial World Forum 2013 (GWF 2013) conference in Rotterdam is the degree to which in the Netherlands that building information modeling (BIM) and geospatial are perceived to be tightly linked.  In my previous post I gave an overview of a presentation by Bram Mommers, who works for the large private engineering company ARCADIS, on why integrating geospatial into the construction process is important.

Jaap Bakkers, who is with the Rijkswaterstaat, the national water company in the Netherlands,  presented more details about the Concept Library (CB-NL) initiative. 

It is supported by the Dutch Council on Building Information (BIR), which is a joint industry and government council created to foster the development of building information modeling (BIM) in the Netherlands.  It includes government agencies such as Rijkswaterstaat, private construction contractors, and engineering and architural firms.  Government funds it, but most of its expertise is seconded from industry. 

Construction processes in the Netherlands

In the Netherlands many government projects are private-public partnerships (P3), where a private sector firm or consortium is responsible for the design-build-finance-maintain phases of the lifecycle and the government as the owner is responsible for operation.

Many AEC firms are adopting BIM because it is cheaper, reduces risk of budget, schedule overruns, and results in fewer change orders.  They may be motivated to adopt BIM to increase their margin or because they are required to by the owner, which is often a governmental organization such as the Rijkswaterstaat.  Once construction is complete, at commissioning, the owner is handed a large volume of facilities data and as-builts.  But this data is often unusable by the owner because it is incompatible or non-interoperable with the owner's asset management, GIS, and other systems.  This is the primary objective of the Concept Library (CB-NL), to create standards that enable re-use of design and construction data for operations.  This is one example of the data impedance problem, where at every handover, design to construction, construction to operations, data is lost and has to be recreated.

Geospatial in the construction process

Marcel Reuvers, Manager of Geo-standards at Geonovum, gave an overview of some the critical roles that geospatial plays on the construction lifecycle.

• Planning / preparation phase
• Asset management / maintenance
• Managing as-builts

I would add sustainable design which always requires geospatial information about local prevailing weather pattern and the location and orientation of neighbouring structures for right to light, wind, solar heating, natural lighting, solar PV generation potential, and other analysis.

I blogged previously about some fundamental changes to the construction process that will make geospatial central to the construction process.  What has been proposed is that a post-construction survey would become the critical source of reliable asset information in the form of a 3D intelligent model which would be maintained in a geospatially-enabled asset database.   When a new project is initiated,  80-90% of the necessary information would already available in the database making a complete resurvey, as is the current construction practice, unnecessary.  All that is required before design can begin is minimal due diligence to validate the as-builts.   The new process also implies that there is a reliable geospatially-enabled asset database that is maintained thoughout the operations and maintenance phase of the lifecycle.

Concept Library (CB-NL)

In the Netherlands there is already a standard decomposition for buildings called COINS.  The idea is to build on this to create a general approach for decomposing infrastructure as well as buildings and that it suffiiciently general to include geospatial. 

The Concept Library is intended to map different terminology across domains: design, engineering, architecture, construction, asset management, facilities manmagement,and geospatial.  For example, it interelates terms like arch bridge, rail bridge, spanning structure, viaduct, and crossing, each of which may be used by a different domain to refer to the same structure. The business benefit is that it would reduce the data impedance problem, where at every handover in the construction lifecycle, designer to contractor or contractor to owner, data is lost and has to be recreated.

The vision is that the Concept Library is an open database based on a standard ontology  that is searchable and has an open API  so that vendors such as Autodesk, Bentley or ESRI can develop interfaces to it for their products.  

CB=NL and geospatial

CB-NL was initially focused on BIM, but is being extended to include geospatial.  CB-NL enables designers, contractors, asset managers and GIS staff to share a common dataset.  It also makes it possible to automate the process of populating asset and facilities management application and GIS databases for the operations and maintenance phase of the lifecycle.

Concept Library (CB-NL)

A two year project to develop the Concept Library has just been initiated, in January 2013, which is supported by a large number of government and private organizations.   It is using the OWL ontology language, which has been endorsed by the W3C.  It uses tools and constructs from buildingSmart's Semantic Constructs for inputting and editing semantic content.   Real world pilots,  for example, a Rijkswaterstaat water services project and the Schipol, Amsterdam, Almere ring road project, will be used to demnstrate the practicality of the approach.

According to Marcel Reuvers, there are a number of standards that relate to the CB-NL project from a number of standards bodies including the OGC, buildingSmart, ISO/TC211, and LandXML.  Jaap Bakker said that the project team has been in touch wth the Open Geospatial Consortium (OGC) in additon to the buildingSmart Alliance about the CB-NL project.

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.

Geospatial analytics for the smart grid

At the annual Distributech conference, the largest electric power distribution conference in North America with attendance of about 9600, earler ths year in San Diego, if there was one consistent message, it was that smart grid has become mainstream - every utilty is doing something related to smart grid. 

I was interested in how gespatial was being used for smart grid applications by vendors at Distributech.  At the conference there were something on the order of 400 talks and panels.  Of these only a few explicitly mentioned geospatial or GIS so you might have thought that geospatial was not playing a very important role in smart grid.  But the reality is quite different.  I talked directly to about 18 companies, mostly vendors, whom I asked about their use of geospatial technology.  All but two said that they were using geospatial technology in some capacity.

Geospatial analytics

One of the most interesting from the perspective of the application of geospatial technology for analytics was Tantalus Systems.  Tantalus provides utilities with an intelligent communications infrastructure supporting smart grid. Tantalus' network solutions rely on wired, wireless, or a combination for bidirectional communications.

RF network analytics

Geospatial technology is used by Tantalus customers in several different capacities.  The first is to help identify problems or misalignment of resources in the radio frequency (RF) and electric grid network.  Visualizing the RF and distribution network geographically enables customers to identify and resolve problems in the RF network.   According to Dave Kauffman, Senior Product Manager for Applications and Interfaces at Tantalus, “GIS brings an entirely new dimension to problem solving for utilities. Before, our customers had to try to understand the source of problems by looking at tables and reports, but they found that with the geospatial view, the source of the problem, typically obstructions, became much easier to identify and correct."

Predictive maintenance

Tantalus customers also use geospatial analytics to look for patterns in outages by overlaying historical outage events on the distribution network and maps showing soil types, weather patterns, and traffic density patterns. Using this type of analytical approach can identify patterns that make it possible to identify equipment that is susceptible to failure and correct the problem before it actually fails.

Reducing risk in Volt/VAR

One of the new areas where GIS is just beginning to be be applied is voltage maps, a new application that Dave is very excited about. When a utility is implementing Volt/VAR at a substation to reduce load, voltages reported by smart meters can be mapped geographically in real-time across the entire distribution network in the form of isovolt maps. This makes it possible to identify areas of low voltage in real time, which is critical because the voltage cannot be allowed to drop below a tolerance mandated by the regulator in order to avoid potential damage to utility and consumer devices.

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.

Estimating the economic and financial impact of poor data quality

I have blogged on numerous occasions about data quality issues relating to infrastructure data at utiltiies including geolocational accuracy, most recently here.  

There is an interesting compilation of statistics in an InsightSquared infographic relating to the cost  of poor data quality in general, not just for utilities.

• The cost of bad or dirty data exceeds $600 billion for US businesses annually.
• Poor data across businesses and the government costs the US economy $3.1 trillion a year.

But it's worthwhile remembering David Loshin's (The Practitioner's Guide to Data Quality Improvement) perspective about the statistics relating to data quality.  He cited some widely known statistics available in 2011

• Tom Redman’s 1998 article in Communications of the ACM said he was “aware of three proprietary studies that yielded estimates in the 8–12% of revenue range.”
• In 1999, Larry English suggested that “Based on numerous cost analyses, the typical organization may see from 15 to 25 percent of its revenue go to pay the costs of information scrap and rework.”
• In 2002, Tom Redman claimed that “Poor data quality costs the typical company up to twenty percent of revenue.”
• IN 2003, TDWI produced a report estimating that “that data quality problems cost U.S. businesses more than $600 billion a year.”
• More recently Larry English said “Poor information quality costs organizations 20-35% of operating revenue wasted in recovery from process failure and information scrap and rework.”

Loshin concluded that

1. There are few (if any) published papers on actual case studies providing tangible details about the cost of poor data quality.
2.  Academic notes and books base their numbers on estimates, “proprietary studies,” accumulations from survey responses, or extrapolation from other estimates of the “cost of quality.”
3. In the absence of tangible evidence of actual costs, according to the experts the costs seem to be rising, from a low of 8% of revenue in 1998 to 20-35% of operating revenue in 2009.  I'm not sure if that means that the cost of poor data quality is rising or that our understanding of the impact of poor data quality has expanded.

Some other interesting items in the InsightSquared infographic

• Data quality best practices boosts revenue by 66 %.
• If the median Fortune 1000 company were to increase the usability of its data by 10%, company revenue would be expected to increase by $2.02 billion.