Developing Enterprise Gis-Based Data Repositories For Municipal Infrastructure Asset Management

DEVELOPING ENTERPRISE GIS-BASED DATA
REPOSITORIES FOR MUNICIPAL

INFRASTRUCTURE ASSET MANAGEMENT
Advisor,
Prof. Dr. S.Y.Mhaske
By,
Shashank chandak
Roll no : 142030004
Contents:
 Introduction
 What is municipal Infra. asset management
 Role of integrated asset data repositories in municipal infrastructure
 Types of data models for asset management
 Case study
 References
Introduction
 Efficient integration and management of assets life-cycle data is the
key to successful management of municipal infrastructure systems.
 Lack of data integration can result in significant inefficiencies and
suboptimal operational and long-term asset management strategies.
 Integrated asset management systems can help municipalities
overcome these inefficiencies and improve the coordination and
cost-effectiveness of asset management decisions
What is municipal Infra. asset management
 Municipal asset data are typically characterized by their sheer size,

complexity, interdependencies, and dynamic nature.
 These data typically exist in disparate formats across multiple data
sources and software systems
 Asset management decisions typically require the integration of data
of different formats from multiple disparate and distributed sources
and software systems.
 Efficient data integration and management can significantly
improve operational efficiency and cost effective asset management
decision-making at the operational, tactical, and strategic levels.
 Asset spatial data constitute the core of most municipal information
systems, and are central to many asset management decision-
making processes.
 Infrastructure asset data are typically identified, associated with, or
referenced by their geographic locations and spatial relationships.
 As a result, there has been an increasing realization of the useful
role that Geographic Information Systems (GIS) and spatial data
analysis can play to support asset management processes
Role of integrated asset data repositories in municipal
infrastructure
Role of data repositories as integrators of asset data and processes

 The repository can potentially improve the efficiency, cost-
effectiveness, and coordination of various asset management
processes.
 The integrated GIS-based asset data repository is built on top of a
relational Database Management System (DBMS), and therefore
can provide a wide range of data sharing, integration, and
management services, such as version management, multi-user
concurrent access and edit, security and authorization, and metadata
services.
Benefits of asset data repositories
 Enabling efficient storage, correlation, indexing, query, and analysis

of asset data, and enable concurrent retrieval and editing of these
data by multiple applications
 Enabling data reusability and sharing, and thus help eliminate the
duplication of efforts, and potential inconsistency and redundancy,
in gathering, validating, and storing asset data.
 Promoting the use of consistent, integrated, and standardized
vendor-neutral data models and formats
 Enabling easy integration of legacy software tools, previously
isolated in separate silos, into a unified and coherent enterprise-wide
environment.
Types of data models for asset management
 Tool specific models:
i) Translators: through the use of translators to map the data
between different vendor-specific data models and formats. The
translation process typically involves a tremendous amount of
redundant data retrieval, interpretation, and re-entry, and is known to
be prone to mapping and interpretation errors.
ii) Application programming interfaces (API): access the
application’s internal data model and to input or extract data directly to
and from the application
iii) XML standards: It potentially provide new opportunities to develop

integrated data models, as well as efficient data encoding and exchange
mechanisms.
Case study
 THE EXPERIENCE OF THE CITY OF REGINA :

City of regina is a province in Canadian state of mantor.
In early 1990s, the City of Regina started its GIS implementation effort
by the development of the Land-Based Information System (LBIS), where
all City spatial data and related processes were identified and analyzed.
The LBIS development included tasks such as the conversion of maps
and data sets into digital format, setting a standard for street address
definition, and ownership parcel layer maintenance.
The implementation has evolved towards the goal of deploying a fully
integrated data repository to support various infrastructure management
processes.
Procedure followed for undertaking GIS data
models
 DATA CONVERSION: FROM PAPER RECORDS TO CAD MAPS
 The growing needs to produce infrastructure records (estimated at 50,000
plans/year) for various departments revealed several inefficiencies in the
use of paper-based records.
 The City launched a five-year initiative to convert infrastructure records
into digital format. The Infrastructure Record Conversion (IRC) project
started by re-drawing the infrastructure record plans (about 3,500 sheets)
and saving the data in CAD format.
 Instead of scanning the drawings, the project team decided to redraw all
plans to enable better quality assurance and control. As the demand for
CAD data grew higher, CAD records exhibited some serious limitations.
First, data access was limited to CAD users, while others had to rely on
mass printouts kept at the drafting counter.
 MIGRATING CAD MAPS TO GIS:
 The project team adopted the ESRI ArcGIS architecture, and started by developing a
geodatabase for domestic and storm sewer data.
 The ESRI geodatabase data model is an object-relational schema that includes
relational tables, feature classes, relationship classes, topologies, geometric networks,
raster datasets and raster catalogs, and data semantics and behavior rules.
 The geodatabase schema was defined using the Unified Modeling Language (UML),
which was then input to the ArcCatalog’s Schema Wizard to generate the database
tables, fields, and data types.
 As an example of the schema development process, the Domestic Feature dataset was
divided into six feature classes – Pipe, Fitting, Manhole, Structure, Lift station and
Pump station. Each of these feature classes was further divided into subtypes.
Subtypes are integer-valued attribute that are used within a feature class or a table to
emulate a class hierarchy.
 The Pipe Material domain is attached to the Material field in the Feature Class, while
the Main Pipe Diameter domain is attached to the Diameter field in the Main subtype
UML Domestic Sewer Line Feature Class Definition
Limitations encountered
 The geodatabase implementation was in the form of a personal

geodatabase (or PGDB).PGDB is stored in a Microsoft Access
(MDB) file, and can only be edited by one user at a time.
 Moreover, the size of PGDB is limited to 2 GB, which limits its
scalability. These limitations, combined with the need to leverage
the use of spatial data across various departments and processes,
made the project team move to migrate the GIS data to an enterprise
centralized system.
 MIGRATION TO ENTERPRISE GIS AND ASSET DATA REPOSITORY:
 In 2000, the project team started to build and maintain an enterprise
GIS system that can support the creation of multi-user versioned
geodatabases. The enterprise GIS implementation was based on
ArcSDE and Oracle relational DBMS.
 ArcSDE serves as a gateway that connects distributed client
applications to a relational DBMS
 ArcSDE creates and manages a set of tables (or data dictionary).
These tables store metadata about spatial data such as spatial
references, feature class names and structures, and spatial indexing
(ESRI 2004)
 Client applications communicate with ArcSDE (over a
Transmission Control Protocol/Internet Protocol, TCP/IP,
connection) by passing SQL statements to retrieve, store, or update
the data in the DBMS. The DBMS returns a set of rows to the
client.
Conclusion
 Using Gis based asset data repository can potentially result in

reducing or eliminating inefficiencies of info. Access and exchange
and thus lead to cost-effective and more efficient operational and
strategic decisions.
 GIS-based asset data repositories can significantly improve the

availability and consistency of the asset data across different
software systems, integrate data across various disciplines, and
facilitate the flow and exchange of asset information
References:
 “ESRI: Extending GIS to Enterprise Applications,” available online

at
<www.esri.com/library/whitepapers/pdfs/idc_enterprise_apps_feb_2
005.pdf>.
 Weston, A., G. Henry, D. Poshen (2001). “Geodatabase Modelling
for Infrastructure Records at the City of Regina,” Proc., GeoSASK
2001, Regina, SK, Canada.
 AISCE
 Wikipedia
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DEVELOPING ENTERPRISE GIS-BASED DATA

REPOSITORIES FOR MUNICIPAL

 Municipal asset data are typically characterized by their sheer size,

Role of data repositories as integrators of asset data and processes

 Enabling efficient storage, correlation, indexing, query, and analysis

iii) XML standards: It potentially provide new opportunities to develop

 THE EXPERIENCE OF THE CITY OF REGINA :

 The geodatabase implementation was in the form of a personal

 Using Gis based asset data repository can potentially result in

 GIS-based asset data repositories can significantly improve the

 “ESRI: Extending GIS to Enterprise Applications,” available online

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