Publication Date: 2017-08-31

Approval Date: 2017-08-17

Posted Date: 2017-08-03

Reference number of this document: OGC 17-048

Reference URL for this document: http://www.opengis.net/doc/PER/uicds

Category: Public Engineering Report

Editor: Josh Lieberman, Andy Ryan

Title: OGC Underground Infrastructure Concept Study Engineering Report


OGC Engineering Report

COPYRIGHT

Copyright © 2017 Open Geospatial Consortium. To obtain additional rights of use, visit http://www.opengeospatial.org/

WARNING

This document is not an OGC Standard. This document is an OGC Public Engineering Report created as a deliverable in an OGC Interoperability Initiative and is not an official position of the OGC membership. It is distributed for review and comment. It is subject to change without notice and may not be referred to as an OGC Standard. Further, any OGC Engineering Report should not be referenced as required or mandatory technology in procurements. However, the discussions in this document could very well lead to the definition of an OGC Standard.


1. Executive Summary

Every year the vast majority of seemingly routine street excavations occurring around the world are adversely impacted by lack of usable information about buried utility infrastructure. A project is delayed for days and weeks at a time to figure out where utilities are buried so work can be planned and performed without undue risk. A work crew replacing a sewer line accidentally or unknowingly strikes a gas main, causing a leak and the threat of an explosion. A large-scale construction project is stalled for months, incurring delay claims and change orders that significantly increase costs, because the locations of utility installations were never properly recorded or depicted and were later found to obstruct planned foundation work. Contractors, in response to onerous contract liability language, increase bid costs by a minimum of 10-30% for contingencies to deal with buried unknowns.

What these kinds of events have in common is that they all can be prevented if accurate, comprehensive utility and soils information are available for rapid integration and analysis. An essential first step toward achieving this capability involves developing geo-enabled utility data models with built-in tools for enabling data interoperability and integration.

The distinguishing and most powerful aspect of geo-enabled data is that it can support integration and interchange of any number of disparate datasets based on the common organizing principles of geospatial location, extent, and connectivity. Geo-enabled data can not only be integrated within a locality, but also across geographic and jurisdictional boundaries to encompass entire regions, countries, continents, even global extents. The stakes are very high to get models for geo-enabled data right. The mission of the Open Geospatial Consortium (OGC) has been since 1994 to promote data standards that allow geo-enabled data to be created, shared, and integrated seamlessly for many different domains and applications. OGC standards cover a wide variety of geodata types including natural features above and below ground as well as surficial components and infrastructure of the built environment.

Up until recently, OGC standards had not yet begun to address data associated with underground utilities such as water, sewer, gas, electricity or telecommunications. Neither had the standards really encompassed aspects of the urban underground environment such soil characteristics, bedrock geology, near-surface hydrology, and built components such as foundations and pilings. Data of these types, if collected at all, is characterized in most jurisdictions by isolated silos of incompatible information with different levels of accuracy and formats, making it challenging if not impossible to integrate data across the various utility networks typically entangled under most city streets. The need to improve this situation is clear.

This report documents the progress made to date by OGC and its members to build a complete picture of the present situation and develop a conceptual framework for action to improve underground infrastructure data interoperability. The report also identifies the most important steps to be taken next in order to develop the necessary data standards and foster their adoption.

Activities
  1. An OGC-assembled UICDS project team of sponsors, contributors, and staff solicited and assembled information on the state of underground infrastructure information and supporting systems. Sponsors included the Ordnance Survey of Great Britain, the Singapore Land Authority (SLA), and the Center for Geospatial Innovation for the Fund for the City of New York.

  2. The project team developed a request for information that sought input from companies, jurisdictions, and nations around the world about current information challenges and how to solve them. Twenty-nine organizations responded to the RFI and delivered extremely valuable information that is summarized in the following report.

  3. The project team then organized a workshop at the offices of the Fund for the City of New York, which brought together selected RFI responders for a two-day conference that explored the challenges and options associated with developing standardized infrastructure information.

  4. This report, the outcome of steps 1 – 3 above, presents the information gathered in those activities and points the way towards the development of eventual data standards for underground infrastructure through a series of activities including research, pilot projects, and demonstrations.

Outcomes
  1. Use cases and case studies: Through the input of RFI responders and Workshop participants, six major categories of use cases were identified:

    • Routine street excavations;

    • Emergency response;

    • Utility maintenance programs;

    • Large scale construction projects;

    • Disaster planning and response; and

    • Smart cities programs.

      The report details how underground infrastructure standards can provide improved options for each of these and cites relevant case studies where improved data yielded significant benefits, many of which can be quantified.

  2. Flanders KLIP case study: The Flanders region in Belgium presented encouraging information about their now well-established utility data integration program. Motivated by the Ghislenghien gas explosion in 2002 which killed 24 people and badly burned dozens more, Flanders now requires all of its 300 utilities to create and provide access to digital representations of their infrastructures conforming to a common data model based on INSPIRE standards, enhancing data interoperability and integration. As a result, excavation timelines have been significantly shortened and the frequency of utility strikes has been reduced.

  3. 1-mile Urban Corridor Gas Main Installation Case Study: A recent professional engineering 3-D survey and modeling effort (per CI/ASCE 38-02 standards) of existing underground infrastructure was integrated with design development and then provided to bidding contractors. The result was extraordinary and unprecedented cost and time savings including: bid reductions of 10%, schedule reduction of 30%, labor reduction of 50%, and zero delays, damages, and change orders. The gas company is now including 3-D survey, modeling, and design of buried infrastructure as a routine practice with their project development and delivery program.

  4. Underground Environment: RFI responders and Workshop presenters made strong arguments to add the underground environment to consideration of underground infrastructure data models. Because the soils, moisture content and other characteristics of material surrounding and supporting utility lines play a significant role in their integrity and longevity, both the infrastructure and its environment need to be considered together.

  5. Governance and Policy Environment: developing data models to enable the integration of underground data will not by itself ensure that this data is actually brought together and benefits realized. The development of accurate and comprehensive underground data is expensive, and because many private and public organizations control portions of this data, getting them to work together is a challenge because of security, liability, competition, and cost concerns. The Project Team has agreed to include considerations of these issues in the CDS report.

Next Steps
  1. Develop prototype models for interoperable data standards.

  2. Research a series of governance and policy challenges in order to frame and guide outreach efforts.

  3. Plan and conduct a series of pilot projects to test prototype standards for different data sharing and integration use cases across multiple jurisdictions.

Beyond their own intrinsic value, common underground geodata standards may also serve to connect many existing data models and datasets associated with urban environments, making it possible to analyze and model them in ways never before possible. This holds enormous promise for the advancement of our society and achievement of smarter, more livable cities.

Table of Contents

1.1. Document contributor contact points

All questions regarding this document should be directed to the editor or the contributors:

Table 1. Contacts
Name Organization

Josh Lieberman

Tumbling Walls / OGC

Andy Ryan

Ordnance Survey

Alan Leidner

Fund for the City of New York

Gavin Chen

Singapore Land Authority

George Percivall

OGC

Carsten Roensdorf

Ordnance Survey

1.2. Future Work

As a concept development study result, this report is intended to form the basis for future standards prototyping, development, implementation, and outreach activities

1.3. Foreword

Attention is drawn to the possibility that some of the elements of this document may be the subject of patent rights. The Open Geospatial Consortium shall not be held responsible for identifying any or all such patent rights.

Recipients of this document are requested to submit, with their comments, notification of any relevant patent claims or other intellectual property rights of which they may be aware that might be infringed by any implementation of the standard set forth in this document, and to provide supporting documentation.

2. Normative References

The following normative documents are referenced in this document.

Note
Only normative standards are referenced here, e.g. OGC, ISO, or other SDO standards. All other references are listed in the bibliography.
ASCE 38-02

Standard Guideline for the Collection and Depiction of Existing Subsurface Utility Data, American Society of Civil Engineers, 2002.

CityGML Utility Network ADE

http://en.wiki.utilitynetworks.sig3d.org

EarthResourceML

http://www.cgi-iugs.org/tech_collaboration/earthResourceML.html

GeoSciML

http://www.opengeospatial.org/standards/geosciml

INSPIRE Utility Networks

http://inspire.ec.europa.eu/theme/us

Information model for cable and pipes

https://www.agiv.be/producten/klip/meer-over/technische-documentatie/technische-documentatie-imkl

Land Infra

Land and Infrastructure Conceptual Model Standard at http://www.opengeospatial.org/standards/landinfra

PAS 128:2014

Specification for Underground Utility Detection, Verification and Location, British Standards Institute, 2014.

PAS 256:2017

Buried assets. Capturing, Recording, Maintaining and Sharing of Location Information and Data, British Standards Institute, 2017.

Common Information Model

International Electrotechnical Commission global series of standards for electric power transmission and distribution at https://webstore.iec.ch/home?ReadForm.

MultiSpeak

North American standard for data exchange between enterprise systems at http://www.multispeak.org/

3. Terms and definitions

For the purposes of this report, the definitions specified in Clause 4 of the OWS Common Implementation Standard OGC 06-121r9 shall apply. In addition, the following terms and definitions apply.

Underground Infrastructure

The totality of built components or structures embedded below ground surface that are part of services such as utility networks and/or that support ground surface structures.

Subsurface Infrastructure

See Underground Infrastructure

Underground Environment

Material forming the ground in which underground infrastructure is embedded, and its aspects such as geology, hydrology, chemistry, and engineering properties. This term also covers dynamic subsurface processes such as fluid flow and chemical / biological alteration.

Soils

This term has a precise definition as the primary component of the Earth’s pedosphere. It is used here in a more general sense to refer to all overburden earth materials in the underground environment, including soils, sediments, and construction fill, that might surround and support underground infrastructure components.

UGI

Stands for Underground Infrastructure

UGII

Stands for Underground Infrastructure Information

UGE

Stands for Underground Environment

UGIIS

Stands for Underground Infrastructure Information System

Underground Infrastructure Information System

Computing system or platform that manages information pertaining to Underground Infrastructure

Underground Infrastructure Information

Information collected about or pertaining to Underground Infrastructure

4. Introduction and overview

Concept and Motivation

Over the past decades, Geospatial Information Systems and Technologies (GIST) have gained recognition as valuable tools that support a wide variety of essential operations and functions. Much of the power of GIST systems is based on their exceptional ability to integrate, visualize and analyze multiple data sets, by correlating them in space and time through the use of common location fields such as addresses and GPS positions. A significant part of the large-scale success of GIST is due to efforts, led by the Open Geospatial Consortium (OGC), to establish standards for geo-enabled information that facilitate data interchange and integration. Such standards make it possible for spatially enabled data to be accurately superimposed from many sources within a single area and connected across many adjoining areas.

Utility infrastructure data – both above and below ground – presents a significant challenge to the establishment of common spatial data standards and is a “last frontier” of sorts for the geospatial revolution. Within any metropolitan area there may be as many as eight or more different utility infrastructure and networks including: water supply wells, potable and treated water, sanitary sewer, storm drainage, irrigation, natural gas, steam, traffic management and control systems, raw and refined petroleum and chemical product pipelines as well as electric power and telecommunications lines. These networks often include or are part of an array of transmission, distribution and service lines. In addition, there are all of the tracks, tunnels, bridges, conduits, and other structures that make up transit systems. Each utility network or system is often independently owned and operated by a distinct public or private organization which has unique engineering and technical characteristics and practices, along with particular data management needs, that have become established over many years. Unique manual record keeping systems have evolved over time into disparate, isolated digital systems with incompatible software and data formats, and schematic level spatial representation. Even different areas or systems within a single utility franchise may use distinct and incompatible ways of recording, managing, and depicting information. These incompatibilities make efficient and timely data integration across different utilities difficult and imprecise. Even when it is technically possible, utilities have often been reluctant to share their information for security, competitive and cultural reasons.

Above-ground infrastructure is at least straightforward to re-survey and validate. When infrastructure networks run underground, the problem of data incompatibilities is compounded further, because the structures themselves are invisible, covered over by street pavement and sidewalks, encased in different soil and sediment units, and entwined with other utility infrastructure. For many features, especially older sewers and water mains, the exact locations are not even known, having been referenced to curb lines and sidewalks long since vanished. Even less well known is the underground context of such structures, including soil conductivity, buried conductors (causing distorting or misleading electromagnetic fields), chemicals, moisture, heat, cold, geological faults, subsidence, vibration, and so on. The presence and effect of water, whether as groundwater, seepage, or infiltration, is not only significant, but dynamic and can follow a complexity of permeable paths which are difficult to identify and monitor. Most problematic of all, interactions between utility systems are often unknown; for example, the failure of one item, such as a transformer, can cause a dewatering pump to fail, which may cause a telecom vault to flood, etc. The potential for such cascading failures need to be understood in advance to develop appropriate counter measures to safeguard the resiliency of our utility infrastructure systems.

The problem would be more tractable if underground infrastructure networks never needed repair, maintenance, or replacement but in fact the exact opposite is the case. Across major cities like New York and London, hundreds of thousands of street excavations are done each year to fix, replace, or update infrastructure, as well as add new services where older infrastructure already exists. Ordnance Survey has collated existing research that indicates that approximately 4 million holes are dug each year by the United Kingdom (UK) utilities industry to repair, upgrade or provide new connections to their assets .

At the present time, few if any cities have been able to comprehensively collect and integrate data about the underground infrastructure networks that serve their citizens. Drawings of underground utilities projected onto the street surface are regularly created on a piecemeal basis, from a broad range of data sources, nearly all of which is non-standardized. The resulting composite drawings present depictions of infrastructure which vary greatly in reliability. To reduce the likelihood of hitting utility structures during a street excavation under these circumstances, “Call 811” notification services (such as, “One Call” and “Dig Safe”) were implemented to alert utilities of an ensuing excavation zone. Often the excavation limits are marked on the street itself, and each utility owner must send a representative or their contract locating service to visit the location and physically mark the location of their own lines on the same street surface. Alternatively, personnel from one utility must visit the map/drawing rooms of other utilities to do visual comparisons of structure location. Call 811 was established as a damage prevention service, and essentially provides a utility owner a last resort for protection; the process is reactive in nature, performed 24 to 48 hours prior to excavation, and not timely enough to allow proactive and predictive utility engineering measures such as advanced utility coordination, conflict analytics, and conflict resolution engineering as promoted by the American Society of Civil Engineers and Federal Highway Administration. Manually intensive methods, such as utilizing Call 811 to acquire and integrate utility information, add time and uncertainty to the construction process, especially given the highly variable quality of utility records, which are commonly a mixture of old, spatially inaccurate, incomplete, and non-standardized information

The Ordnance Survey’s Geovation Challenge 2016 has collated information from many different sources and reports that “Approximately £150 million is incurred by strike damage to third party assets alone by utilities across the UK with indirect costs around ten times this. Fatalities are a severe consequence, with for example, approximately 12 deaths and 600 serious injuries per year from contact with electricity cables. Furthermore, In emergency situations, the inability to quickly and accurately integrate quality data from multiple utilities can result in greater damage, larger outages and unnecessary injuries and deaths.”

Currently, the different utilities in most jurisdictions keep their infrastructure records (surface as well as underground) in a variety of formats that are not easily integrated. Moreover, utilities are reluctant to share with each other anything more that the barest information because of security and competitive concerns. This inability and reluctance to share data heightens the challenges of utility “strike” avoidance; acquisition of high-quality information for large-scale planning, design and construction; and emergency and disaster preparedness and response. Additionally, the lack of accurate and integrated infrastructure data impedes efforts to use new sensor and control technologies that characterize “smart” cities and counties, with their promise of greater efficiency and improved quality of life. This is an appropriate task for the OGC because the most effective way of representing utility networks is through geospatial visualization and analysis, and the best way of integrating different geospatial networks – and unlocking the power of data combinations - is through the adoption of compatible geo-data models that allow utilities operating in the same area to bring their data together- with utility feature location as a primary organizing and integrating principal - in ways that maximize functionality and collaboration.

Applications and benefits

Accurate three-dimensional geospatial information about the location, nature, condition and relationships of these assets would reduce the expense for the asset manager and other stakeholders. Holistic understanding of the relationships between underground assets and with above ground infrastructure would help minimize service breakdowns and mitigate the impact of disasters. Comprehensive, exchangeable and up-to-date datasets could benefit the following business and societal activities:

  • Utility services operation and maintenance;

  • Emergency management and disaster response;

  • Construction planning and management;

  • Medium and long term planning for development, utilities, transport; and

  • Information model foundations of smart cities.

These benefits would be realized by enabling a variety of efficiencies:

  • Less damage to existing assets when undertaking works;

  • Improved conflict analytics, engineered resolutions, and advance coordination between stakeholders that result in better relocation designs, implementation of joint trenches, and innovative contracting methods, leading to fewer wholesale utility relocations, lower construction risk, shorter project schedules, and decreased costs for all stakeholders;

  • Better estimation of timescales earlier in the process;

  • Improved assessment of impacts and risks to other assets from planned activities;

  • More effective prevention of, preparation for and response to emergencies;

  • More accurate analysis, prediction, and prevention of cascading utilities failures;

  • More comprehensive analysis of options for continuity of service;

  • Better understanding of points of vulnerability within and between assets; and

  • More secure sharing of sensitive underground information.

Numerous studies around the world have shown that these are common challenges in an increasingly urban and technical world. Through the Underground Infrastructure initiative, OGC and its members seek to lower the barriers to interchange and integration of infrastructure data in a number of critical applications. By means of a common, extensible data model and interchange standards, OGC expects to create a favorable environment that encourages uniform, high quality data development and enables straightforward, timely data integration. This will eventually make it possible to assemble complete “common operating pictures” of what is underground whenever and wherever needed. This should lead to large-scale efficiencies in the way that the “underground city” supports the life of a city as a whole.

Initiative Scope

Subsurface and below ground utility networks: A common data model for underground infrastructure will need to represent all the components necessary to characterize that infrastructure as a whole in order to enable infrastructure data interoperability and standards formation. Such components will at a minimum include or cover the following.

  • Infrastructure networks

    • Water

    • Sanitary Sewer

    • Stormwater Drainage

    • Fuel

    • Electric

    • Gas

    • Steam (District Heating)

    • Geothermal

    • Telecommunications

    • Transit

    • Any of the above that are present but inactive

  • Soils, surface and other underground features

    • Surface cover and usage, e.g. street, sidewalk, building and open space characteristics

    • Hydrography and bathymetry

    • Surface elevation

    • Soil

    • Bedrock

    • Water table

    • Foundations, basements, cellars, vaults, passageways

    • Geological faults and other geological features

  • Connectivity relations

    • Interdependencies between different infrastructure networks

      • Sewer connections to transit tubes

      • Electrical connections to subways

    • Production, transmission, distribution, and house connections

    • Relationship to aboveground features and data standards

  • Business processes/legal requirements

    • Data required to support business or legal processes around underground assets.

Surface and above-ground utility networks: The primary purpose of this project is to develop interoperability standards for underground infrastructure data in urban environments. In doing this OGC recognizes the need to look towards developing interoperability standards as well for infrastructure networks and features that run on or above the ground. Such above-ground utility networks are present even in dense urban areas but are more often found in suburban and rural areas.

Rural and suburban areas: It is the hope that this project will initiate and facilitate a process by which infrastructure interoperability standards are developed that encompass the characteristics of all kinds of utility networks located in all types of areas. From the standpoint of urban infrastructure, this is important because the supply chains of many types of utilities involve the transmission of resources from generation plants, wells and reservoirs located outside urban areas. Additionally, having infrastructure interoperability standards that cover every kind of community will enable regional planning efforts that examine infrastructure not as isolated islands of urban use, but as interdependent parts of a regional whole.

OGC Concept Development Study

The OGC Innovation Program utilizes a multi-step collaborative methodology for interoperability initiatives that seeks to uncover geospatial interoperability challenges and then develop ways to address them. The methodology begins with a Concept Development Study (CDS) in order to understand and frame the current state of information technology in a target knowledge domain. A critical step in a CDS involves gathering insights from domain experts and other stakeholders about productive future directions that can then be explored in subsequent initiative activities such as testbeds, experiments, and pilots. Ultimately the initiative methodology leads to development and adoption of consensus reference architectures and information standards that increase both the value and the utility of geospatial information.

The Underground Infrastructure Concept Development Study (UICDS) is based upon responses to a Request for Information as well as results of a 2-day workshop and other inputs. The study examines opportunities for–and barriers to–establishing functional three-dimensional repositories of underground infrastructure and other relevant sub-surface information. The study will consider, among other issues, how different infrastructure data providers, consumers, and software vendors can best achieve:

  • Sustainable collection of geo-enabled data fit for purpose on all relevant underground infrastructure;

  • Exchange of data between platforms, systems, and organizations without loss of detail, attribution, or significance;

  • Interactive model-driven data access;

  • Enforcement of data security sufficient to protect appropriate public, private, and personal interests;

  • Integration of inputs from current and new generations of sensors and other intelligent infrastructure components;

  • Advanced data analysis including predictive analysis and big data analytics; and

  • Continuity of data and systems where infrastructure exists and/or extends onto and above the ground surface.

The CDS will also outline the scope of a multi-phase underground infrastructure interoperability initiative. Subsequent phases will seek to develop a deeper understanding of implementation and policy issues, as well as test standards-based components for enabling infrastructure data interoperability in realistic application scenarios. Scenarios will initially focus on urban landscapes but will take suburban and regional environments into consideration as well.

This report comprises:
  • Summaries of responses to a Request for Information;

  • Results of a workshop attended by key experts, stakeholders, and study sponsors;

  • Discussion of issues raised by these two activities:

    • Governance of underground data and models;

    • Use cases and applications;

    • Underground infrastructure data models;

    • Underground environments;

    • Sensing and data collection;

    • Application platforms and architectures;

    • Policy challenges;

  • Findings and recommendations;

  • Initial planning for next steps, including:

    • Prototype common data model;

    • Research in policy issues; and

    • Implementation pilots.

5. Request for Information and Study Workshop

5.1. Request for information

OGC issued a Request for Information to support the Concept Development Study. Twenty eight (28) responses were received. Responses came from: US, Europe, and Asia from the Government, Industry, and Academia sectors.

Note
Responses approved by the submitting organization for public release have been posted on the OGC website and cross-referenced by topic in Annex A of this report.
Table 2. Organizations responding to the RFI
Organization

Accenture including the Underground Infrastructure Mapping Team in Chicago, and Columbia University.

Bentley Systems, Inc.

British Geological Survey (BGS)

Bureau de Recherches Géologiques et Minières (BRGM)

Carl Stephen Smyth, Co-Chair, OGC CityGML Standards Working Group

Cesar Quiroga, Texas A&M

City of Boston

City of Rotterdam

City of St Paul, Minnesota

Dassault Systèmes

Delft University (Vector and Voxel responses)

Dubai Electricity and Water

Electric Power Research Institute, Inc. (EPRI)

Erik Stubkjaer (individual)

Geoweb 3D

HERE

HL Consulting BVBA

Informatie Vlaanderen

Paul Scarponcini, Chairman, OGC LandInfra SWG

Les Guest Associates

Luciad NV

Robin Danton (individual)

Spacetime Technology

Technics Group

Technische Universität München

UMS Berenice International Group

Verband Schweizer Abwasser- und Gewässerschutzfachleute (Swiss Water)

WinCan Europe Ltd

5.2. Workshop

An Underground Infrastructure (UGI) CDS workshop was held on 24-25 April 2017 in New York City. Some 40+ participants engaged in 28 presentations and breakout discussions on four main topics.

  1. Applications and benefits of UGI and UGIIS platforms;

  2. Utility data models;

  3. Underground environment characterization including soils; and

  4. Examples and case studies of data collection, integration, analysis, and visualization.

Note
The workshop agenda and summaries of presentations have been tabulated in Annex A

While not a principal focus of the workshop, discussions also touched on issues of information security, liability, and the financial / societal / legal context for underground infrastructure information.

Expected workshop actions and outcomes
  1. Identify methods for exchanging data between disparate information models, emphasizing comparison of information models to identify common concepts that enable integration.

  2. Review existing underground information systems that aim to support significant applications and provide valuable benefits.

  3. Identify successes as well as challenges of past and current projects.

  4. Plan for the next phases of the project including a pilot implementation that advances best practices and open standards to meet the application and benefits.

6. Discussion and knowledge synthesis

6.1. Historical perspective

Utilities And The Built Environment:
The economic life of communities of all kinds, and especially in developed and developing countries, depends to a significant extent upon the quality and efficiency of the built environment. This includes the structures where people live and work and the infrastructure that connects every structure – and serves all who use those structures - with essential resources such as water, energy, communications services. If buildings and their occupants can be compared to the cells in a human body then infrastructure networks are like the human circulatory and nervous systems without which life would not be possible. Infrastructure also cannot be static: technological change, and economic dynamics require that the infrastructure services we receive be in a constant state of repair, renewal and re-invention to keep up with society’s needs, technological advancement, and competitive necessities.

Utilities Go Underground:
In developed countries, most jurisdictions have made the decision, sometimes hundreds of years ago, that some or all of the infrastructure serving the populace should be placed underground, running along the street network and branching off to connect with buildings and other structures and street elements. The reasons for this decision are obvious: water and sewer networks cannot be efficiently engineered at the street level and other types of utilities are protected by being buried in the earth, where they do not clutter the streets and sidewalk which are needed to support safe public mobility. For example: the decision by New York City to put utility lines underground was made after the blizzard of 1888 when heavy snows caused the widespread collapse of utility poles and lines, resulting in widespread outages, and a major threat to public safety especially from severed electric wires.

8 nyc powerlines 1888
Figure 1. NYC Blizzard of 1888 ( http://historyimages.com/Vintage-NY/Blizzard-88.htm, New York Historical Society)

Invisible Infrastructure
Yet once infrastructure was placed underground, utilities were forced to deal with another set of problems arising from the fact that pipes, conduits and connections could not be seen at street level nor physically reached when work on them needed to be done – except for small segments of the network that could be accessed via manholes and vaults, and street accessible valve shafts. When new service connections needed to be made, when utility lines brake and needed to be repaired or replaced, when new kinds of services needed to be provided, when higher capacity services needed to be installed to deal with increased demand, it is almost always necessary for there to be an excavation below street level where there might be five, six, seven or more different kinds of utility pipe and conduit lying close to one another and often, on top of one other. Workmen were obliged to proceed with great caution because they could not see what might be hit, damaged or severed by their next blind shovel thrust. One miscalculation could lead to a flood from a punctured water line, a gas line explosion or even a lethal shock from severed electric conduit. Even so, accidental utility “strikes” were, and continue to be, a regular feature of utility work, delaying projects, wasting money and inconveniencing the public.

8 I 405 ui xsection
Figure 2. Utility Sizes and Placements (Professor George Deodatis Presentation, 4/25/17 OGC Workshop, NYC, from the California Department of Transportation (Caltrans))

Utility Data Sharing Procedures Solve Only Part of the Problem
Due to the persistent hazards of uninformed excavations into streets tightly packed with infrastructure, ultimately almost all jurisdictions with underground utilities adopted “One Call” or “Safe Dig” procedures that required all utilities with infrastructure elements near the site of a planned excavation to either share their records, or mark their locations on the street. But such excavation coordination efforts were only as good as their records were easily accessible, complete, accurate and understandable. All too often data flaws and incompatibility led to misinterpretation and mistakes which resulted in delays and in damages. This might only have been a minor annoyance if it were not for the fact that utility excavations are quite frequent. Looking at information from older cities like New York, Chicago and London; and regions like Flanders, Belgium; for every street mile there may be as many as 30 to 40 or more excavations annually, or more than 200,000 excavations on an annual basis. When dealing with the large scale of these transactions, inefficiencies in bringing data together, can be costly, annoying and even dangerous.

Utilities and Records Management
Organizations that own and manage underground utilities have always keep records that depict their networks including geographic location, feature attributes and logical/functional/engineering characteristics. This information supports utility business and field operations including customer service, utility hookup and repair; utility replacement and modernization, and customer billing and collecting. Because the infrastructures of many utilities were designed and created many decades ago, their records reflect the information technology – or absence of technology - available at the time. Even to this day, many records are still kept on manually drafted drawing sheets and service connection cards, more recently record keeping has progressed to include scanned drawings, CAD electronic designs, and databases to store attribute data. More advanced utilities have combined their old records and CAD drawings to create GIS based seamless utility maps with GIS features linked to attribute data.
For utilities, as with almost every other form of business, the efficiency with which information is handled, determines how effectively the business is run. For underground utilities, this challenge is complicated by the fact that safe and efficient utility operations require a knowledge of the location of other nearby utilities. Since different utilities have different methods for storing and formatting their data, and have a natural reluctance to share based on security concerns, the bringing together of data, even with excavation coordination programs, has always been problematic. As computer visualization and analytic capabilities have grown, opportunities to take full advantage of new information tools have foundered because compatible data capable of being quickly shared, integrated and analyzed just simply does not exist.

6.2. Governance

6.2.1. Introduction

For any hope of having an impact on how infrastructure information is captured, structured, stored, shared and used, it is essential to have an understanding of the various organizations that play important roles in owning, managing, and regulating underground assets.

6.2.2. Responsible entities

Who is responsible for the data ?

The parties responsible for collecting and curating data about the underground environment can be grouped into some general categories. There is inevitably some overlap between the categories.

  1. Asset operator – parties that own or operate infrastructure or manage locations that require underground information.

  2. Data supplier – a body that captures data as a potential commodity for sale to other users.

  3. Data collator – a body that combines data from different sources as a potential commodity or as a ‘public’ service.

  4. Project based – a body that requires information for a specific project.

  5. Land Administration - a body, normally governmental, that records ownership or other rights about the sub surface.

The status of the parties is variable they can be central or local government bodies, quasi-government bodies or commercial companies. Their drivers are inevitably different and generally reflect their role or status.

Asset Operator

Asset operators include bodies responsible for the supply of services such as water supply and disposal, electricity, gas, heating (for example steam) and telecommunications. Additionally, there are parties who manage transport networks that will have data about their infrastructure such as tunnels, stations, ventilation shafts, access points and so on as well as the roads and rail lines themselves. There are also organizations responsible for environmental management or protection, such as surface water drainage, flood prevention, public open space management and so on who will have data about underground assets to assist them in their activities.

Examples from the RFI include US Highway Authorities with 3D inventories and the Dubai government department responsible for electricity. Of note in the RFI, with the exception of Dubai, individual asset operators were not represented directly as participants.

Data supplier

Data suppliers in the underground environment as a purely commercial activity are not a common element. The costs of data capture and maintenance mean that the data entry costs are high if no specific users have been identified. Bodies such as the British Geological Survey (BGS) and BRGM (Bureau de Recherches Géologiques et Minières – French Geological Survey) collect and freely distribute relatively low resolution sub-surface geological data, though they also provide some higher-resolution data on a fee basis. Organizations such as Ordnance Survey collect surface topographic or land-base data which is used to register and depict underground assets.

These organizations are also commonly data collators and will also work on project-based activities using their expertise and knowledge to deliver more precise content where demand exists (see below).

Data collator

Data collators combine data from different sources for conflation as a potential commodity or as a ‘public’ service.

Parties may combine data, often from disparate sources, to create content data that has more value, for example assembling borehole data, contaminated land, mining records, and surface data to create a model that can be owned. In these cases the data may be used to provide a service such as liability to subsidence for land and property. Responsibility for this combined data is likely to lie with the collator. As part of the RFI Columbia University, BRGM, and BGS outlined this type of approach.

In other cases the collator will not own the data but combine it to offer a service. For example the KLIP service in Flanders and KLIC service in the Netherlands combine and supply data to users to reduce conflicts when excavations are planned. In these collation services responsibility for the data still tends to sit with the asset owners. Such services are necessarily provided to the collator with caveats related to quality. Other services such as Dig Safe in New England and Call Before you Dig in Connecticut provide in essence a reverse collation service, by collating and distributing individual excavation notices to the utilities so they can respond without contributing their data.

Data collation services were quite prominent in the RFI responses, for example KLIP, CityGML – Rotterdam, ASK (BGS) and NUAG (Les Guest).

Another type of data collator would be public bodies charged with emergency responses such as those highlighted by University of Munich and New York City. In these examples the conflated data would need to be tested against the identified use cases but is not likely to be shared outside the government body, though findings and recommendations from analysis may be.

Project based

Project based actors are bodies that have a requirement to collect information for a specific project. They tend to capture data to a very high level of detail and quality in accordance with the CI/ASCE 38-02 Standard Guidelines for the Collection and Depiction of Existing Subsurface Utility Data, an engineering standard that raises the utility investigation activity to a professional effort akin to a geotechnical investigation or property boundary land survey, in which a licensed professional certifies the submittal. This costs of capture are typically small compared to the budget for a construction project, and the return on investment is typically on the order of 2 to 10 times the cost. For example UMS Berenice highlights recent light rail projects at the Los Angeles International Airport and in Honolulu.

At a different level, the City of Boston require conduits for broadband fiber to be installed and design / as-built data to be submitted whenever new street work projects take place. Another type of project based capture was highlighted in the submission from New York where commercial companies gather borehole data as part of actual and potential development activities.

It is likely that the ownership of the detailed data will lie with the construction project. However, in the case of the New York geo-technical boring data, it was reported that the companies who capture the data will tend to view it as valuable for use in future projects as it provides information not available to rival companies.

In comparison to mapping the above ground an obvious difference arises. In most cases the asset owner is responsible for the data about their asset and it many cases it is the only record. For above ground there are commonly bodies that collect at least a framework of shareable content, for example mapping or city authorities. If this approach was continued above ground it would be akin expecting the individual property owners, the highway authority, the river authority and so on to all capture data about their area of interest and then share it hoping to make a seamless dataset.

Land Administration

An additional type of responsibility is for registration of ownership or other rights, highlighted by the Singapore Land Authority and Erik Stubkjær. In this case a body, likely to be public, may be recording the location of the ownership or other rights below ground level. There are related uses where some local authorities require knowledge of basements and similar structures for planning, taxation and risk assessment. The correlation with other data may be variable. Land Administration systems also record easements, the right to cross or otherwise use someone’s land for underground utility purposes.

Singapore Land Authority for example report that landowners hold title to the land surface and to 30 m of depth from the Singapore Height Datum below that; everything deeper than 30 m from the SHD belongs to the State. In addition the government can acquire additional underground strata when developing public projects.

6.2.3. Mechanisms of ownership and authority

What makes a party own the data – running their business, legislation, best practice, benefits

Asset operators

Asset operators originally captured data on paper records, as described by Les Guest for UK and by Munich University for the City of Rotterdam. The driver was for the operator to be able to maintain and extend their services by knowing what assets they had and where they were located. Paper maps do not readily lend themselves to three dimensional representation and anyone combining the data from different operators in crowded areas would struggle with simply overlaying the maps physically. As data became increasingly digital then paper records were digitized to benefit from reduced costs of storage and longevity issues with paper records. This allowed data to be readily overlain but the source data quality limitations generally remain.

From RFI and experience in the UK it would seem that the main drivers for ‘business as usual’ data ownership is to capture only enough information to allow the asset owner to conduct their normal activity. Evidence for data improvements driven by the asset owners was not widespread from the RFI though the benefits were recognized. EPRI reported https://www.epri.com/#/pages/product/1024303/ that GIS data for underground assets is commonly not updated as changes occur in the real world as the team undertaking the work rarely consider themselves to be a data owner. EPRI report only 46% of respondents report significant benefits from high quality data, similarly only 15% reporting repercussions of poor data suggesting a perceived lack of benefit. Additional requirements may be created by those with a more holistic view where the main aim of is to facilitate data sharing and reduce accidental strikes; for example KLIP in Flanders, KLIC in Netherland, ASK in Glasgow, and so on.

Local standards do exist, for example in Switzerland for water (Robin Dainton) and Streetworks legislation in UK. However is most cases the operator is not required to enhance existing data due to the costs of capture/improvement. From the RFI responses there is little evidence of utility providers actively seeking to improve their data for internal operational reasons such as efficiency or best practice beyond that required by statute or contract.

Data supplier

Data suppliers in the underground environment, as evidenced by the RFI responses, tend to capture, collate, and distribute sub-surface geological data at a relatively low resolution. A proposal to periodically capture and monitor the NYC sub-surface was mentioned at the workshop; however, the costs of capture, if not driven by project, particular risk or asset owner, are likely to discourage enhanced or repeated capture. The national geological bodies are likely to have a mandate to maintain a national level of coverage, however the rates of change at this resolution are almost nil. The costs of capture at locally detailed levels are likely to be too high for wholesale capture to take place. This contrasts with the increasing availability of high-resolution surface topographic reference data.

Data collator

Data collators will conflate data from different sources to offer a service. For example Columbia University, BRGM, and BGS combine disparate subsurface sources into data that has value. This can be on a wholly commercial basis as a product, including services, that is sold or as part of some type of ‘public task’. For example data such as contaminated land or mining records may have to be made available.

For strike avoidance initiatives the collation can be voluntary and funded by the utility community; leading to distributed notification systems such as Dig Safe in New England and Call Before you Dig in Connecticut. Alternatively they can be mandated in legislation like the KLIP and KLIC programs in The Netherland and Flanders or the permit system implemented in Dubai and proposed for Chicago. They can also be implemented through contracts whereby a requirement is for an as-built survey to be provided once work in complete.

Collation for emergency responses is likely to be led by the Government bodies responsible for identifying risks, planning and responding. How the data is sourced did not emerge from the RFI.

Project based

Project based actors are bodies that have a requirement to collect information for a specific project. The data is required to plan and monitor a project. It is expected that the data belongs to the commissioning party and that is usually handed over to the operating body when a project is complete. Informal discussions in the UK would suggest that initial the high quality of data is not always maintained as changes occur after the initial completion of the project.

In other cases, such as those identified in New York, core borehole data typically gathered for one project is regarded as a valuable asset. This data is held by the companies that have collected it as it is costly to source and is expected to be reusable on future projects in such a dense urban area.

Land Registration

Land registration bodies are there to "Protect property ownership rights" as reported by Singapore Land Authority in addition to supporting decision making and planning. Singapore Land Authority described how two-dimensional plans have been converted to three-dimensional data.

Data is likely to created and shared as ownership is claimed or as projects are delivered that require ownership or other stakeholders to be established. This could be new construction where private ownership wishes to obtain security of tenure or driven by an infrastructure project in public ownership.

6.2.4. Stakeholder dynamics

How do the stakeholders relate- licensee/licensor, competitor, govt, supplier?

Asset operators

The asset operators may be in direct competition with one another, for example rival telecommunications operators. Asset operators may also be in competition for space in the real world to place their infrastructure. This may create some reluctance to share data, this was hard to identify from the RFI due to the lack of responses from utility operators. Government can have a role to play is it is likely to license operators to allow them to use public thoroughfares to route assets and in return demand they make their data available to other stakeholders. The KLIP and KLIC initiatives are good examples of this where the aim is to avoid utility strikes by mandating data sharing. There are similar but different versions of this approach around the world, for example in the UK the focus is on minimizing traffic disruption by mandating permits to excavate the pubic highway. Typically permits to dig are volunteered or mandated that alert utilities and traffic management bodies to possible activity and allow them to either supply data, to visit the ground to mark up assets or (ideally) to combine collocated works projects.

The asset owners are typically private companies and the costs of data capture and improvement are significant. In the UK regulation is fragmented across sectors and there is little appetite to impose additional costs that would be passed onto consumers either by sector or across all the asset operators.

The asset operators will supply data to the data collators either through self-interest or to meet statutory requirements. They may also consume data from these collators as part of their day to day activity to plan activity better and to reduce the chance of strikes.

If ownership of the sub-surface becomes an issue then bodies will engage with Land Administration bodies. To a certain extent the identification of who 'owns' a street is a light version of this.

Data supplier

Data suppliers in the underground environment, as evidenced by the RFI responses, tend to supply data at a level they have either been mandated to do by government and/or at a level where they can realize some return. They can also respond to specific projects, government or private sector led. There appears to be little demand from asset operators for soil/geology data; however the soil/geology community appear to be more pro-active in seeking out the asset owners for collaborations, for example the ASK project in Glasgow, Project Iceberg in the UK, and Columbia University in New York.

Data collator

Data collators will necessarily interact with asset owners, data suppliers to source the data required. The supply of data may be required in a contract, a statutory requirement or supplied out of self-interest (to reduce strikes or help with emergency response). In many cases the asset owners will also be customers of the data collator, for example strike avoidance services.

Project based

Project based actors will have a more ad hoc relationship with the other types of party. They may source data from them with a view to assessing and if necessary improving it or they may choose to recapture it entirely to a new standard, for example the Los Angeles airport World Airport Automated People Mover project described by UMS Berenice.

Land Registration

Land registration bodies are likely to interact with Asset owners when they want to create initial records of ownership and stakeholders and will offer a service to all of the other parties when their activities

Data is likely to created and shared as ownership is claimed or as projects are delivered that require ownership or other stakeholders to be established. This could be new construction where private ownership wishes to obtain security of tenure or driven by an infrastructure project in public ownership.