We have been honored to be asked by the International Facility Management Association (IFMA) to write a white paper entitled "GIS for Facility Management". This is the third chapter in the series. A full copy of the paper can be downloaded from the IFMA web site. We would like to thank Manhattan Software and ESRI for their support of the white paper.
Chapter 3 - An Overview of Geographic Information Systems
Modern GIS is an integrated system of computer software and data and information about the location and geography of things and phenomena and the relationships between them. GIS is used to interact with, manage and display geographic information.
Figure 1: Dr. John Snow’s map of cholera victims living near the Broad Street pump in London, 1854
GIS was first computerized in the 1960s (GIS.net 2010) as an effort to automate the landscape planning process of separating design influences, such as hydrography, vegetation, soils and ownership boundaries, into different layers. The approach before computerization was to draw each of the layers to scale on a separate page of acetate and then physically recombine them by stacking the pages in order to visualize different aspects of a proposed design. In the ensuing decades, GIS has matured into an enterprise-class technology platform that allows users to model the spatial relationships between and among many important aspects of our complex world.
Before the specifics of how GIS is being applied to facility management are discussed, it is important to review some of the core concepts that define what a GIS is and how it works to better understand how this technology complements and extends other technologies that support the needs of facility managers.
3.1 GIS Basics
There are five basic core concepts of GIS:
• GIS has layers
• GIS provides seamless scaling
• GIS attribute data is strongly typed
• There are several kinds of GIS feature classes
• GIS supports topologically rich data models
Each of these core concepts is further discussed below.
3.1.1 GIS Has Layers
The layers in a GIS correspond to groups of features that have similar attributes and/or behaviors. Road centerlines are a good exampleof a common GIS layer. Each segment in a road centerline layer might have attributes that describe pavement width, number of lanes, speed limit or turn restrictions. A specific layer in a GIS is called a feature class. All of the features in a feature class share the same attributes and spatial reference. Traditional geospatial data layers that might be of interest to facility managers include:
• Transportation (road centerlines, edge of pavement, rail lines, airports)
• Hydrography (lakes, ponds, rivers, streams)
• Pedestrian corridors
• Land use
• Parcel ownership
• Aerial imagery
• Digital elevation models
• Facility condition index (FCI)
• Performance measurement by building
• Total cost of occupancy by building
The GIS data layers bulleted above are typical of traditional applications of GIS. Additional data layers specifically identifying components of the built environment, and possibly of greater interest to the facility management community, will be discussed in Part 4 GIS in Facility Management and Part 11 In-Building GIS.
3.1.2 GIS Provides Seamless Scaling
GIS provides seamless scaling from very large scale global data to very small-scale local perspectives. The various scales at which GIS is useful for facility management include from global, regional and local to campus and room or space scales. At the global scale GIS can:
• Visualize patterns in portfolio performance
• Symbolize portfolio elements by a key performance indicator (KPI) and show them on a map
At the regional to local scale, GIS can tie facilities, portfolio elements and customers together into a geographic context by:
• Providing an understanding of how well the portfolio is geographically aligned with customer base
• Supporting site selection based on business demographics
• Supporting site selection based on proximity to workforce
• Optimizing work order assignments and support with routing
At the local or campus scale GIS can:
• Provide analysis and visualization of 2.5D space data across the campus
• Visualize departmental fragmentation across campuses
• Analyze relationships between office and parking assignments
• Analyze potential use conflicts
• Visualize spatial and temporal space use patterns
• Understand work order patterns and asset locations
• Spatially enable infrastructure asset inventory
2.5D refers to visualization of buildings and other models in apparent 3D that is derived from a single averaged measurement of ceiling and/or floor-to-floor heights and then used to construct generally representative building models that show length (on the x axis), width (on the y axis) and height (on the z axis) of the structure. In contrast, true 3D is an architecturally accurate building model in three dimensions. For building and construction purposes, 3D modeling is sometimes the required standard. For the vast majority of maintenance and operations purposes, 2.5D is typically adequate and it is much less expensive and time consuming to establish.
At the room and space scale, GIS can visually interact with assets, inventory and their exact locations to support regulatory, maintenance and resourcing.
3.1.3 GIS Attribute Data Is Strongly Typed
GIS attribute data is descriptive data that is linked to map features. If an attribute in a feature class is, for example, of a date type, it will only accept properly formatted dates as inputs, and if it is a number type, it will not accept text characters. The result of this is strong data typing, and is ideally suited for GIS data and analysis. Unlike CAD attribute blocks where annotation is stored as all text and annotation is only loosely associated with a feature, GIS attributes are directly tied to features and all of the attributes are strongly typed.
3.1.4 Basic Kinds of GIS Feature Classes
A GIS feature class is a homogenous collection of common features, each having the same spatial representation. The most basic kinds of GIS feature classes are points, lines and areas (polygons). In recent years, however, new kinds of data have found their way into the GIS platform. As 3D becomes more important to modeling, newtypes of data, such as surfaces and multipatches (see Glossary), are allowing for more precise modeling of three-dimensional features.
3.1.5 GIS Supports Topologically Rich Data Models
As different components of the world were modeled digitally, it was determined quickly that things have important relationships to other things. For example, valves have important relationships to pipes when modeling how water can be delivered from one place to another. A GIS allows relationships to be built between features in different feature classes. For example, pipes in a line feature class and valves in a point feature class create more complex topological structure, such as geometric networks and transportation networks.
3.2 GIS Data Storage and Organization
The way GIS data is organized and stored makes it ideally suited for storage in database systems and for analysis. As GIS data is typically stored in a real-world spatial reference system, the analysis of the data can be applied across a campus, region, country or the world. A few of the many different types of geospatial analyses that are appropriate on facility data might include:
• Buffer analysis – How many unoccupied offices are within 1,000 ft. (305 m) of this parking space?
• Overlay analysis – Which wet labs are within the proposed project area?
• Find ‘n’ nearest – Find the five closest assets with open work orders to this particular point. (where n represents the number sought)
• Line of sight – What can be seen from this window?
• Way finding – What is the shortest wheelchair accessible route from room x to room y?
• Travel time – How many employees will have to travel more than half an hour to get to this
As the application of GIS has become more frequently used, particularly in the government arena, an enormous amount of geospatial data has been developed at a variety of scales. Much of this data is freely available over the Internet from a variety of GIS data portals like the US national geospatial data site geodata.gov.
3.3 Enterprise GIS Framework
In most sizable organizations, information technology (IT) management has been recognized as an essential strategic asset. The modern organization can no longer exist without a secure network backbone, centralized user authentication and entitlement control, e-mail administration, enterprise database management and support for a variety of enterprise applications, like accounting, personnel management and an array of loosely connected Web applications.
Over the past decade, GIS has similarly become a recognized component of the enterprise IT suite of capabilities. GIS can now be implemented on enterprise-class databases, published through Web services and integrated with a variety of mobile device platforms. While it is certainly possible, and in some cases most appropriate, to create a stand-alone GIS on a laptop or workstation, it is important to recognize that enterprise deployment has become available over the past decade. Enterprise deployment enables GIS capabilities to be shared with a wide variety of users throughout the organization.
Furthermore, professionals that manage IT capabilities of large organizations are becoming more aware of the value that geospatial support represents to decision makers across many different departments. It is very possible that GIS already exists in an organization and it can be utilized by facility managers. For example, if your organization is in telecommunications, your engineering group may have implemented GIS to track locations and rights of way. Therefore, this technology may be only a workstation away from being available to facility managers. The same is true in many higher education settings. It is very likely that there is an academic or research GIS installation that could be accessed by facility management.
3.4 Spatial Data Infrastructure
Many geodata portals have been established over time to enable and support the sharing of geospatial data and analytical models. As this activity has become more widespread, certain best practice patterns have emerged to support thiscooperative approach. One specific example of such a best practice is spatial data infrastructure (SDI).
Spatial data infrastructure is a framework of technologies, policies, standards and human resources necessary to acquire, process, store, distribute and improve the use of geospatial data across multiple public and private organizations. Therefore, SDI is a framework of connected spatial data, metadata and tools used to centrally manage data with tools and services connected via computer networks to various sources to make spatial data most efficient. SDI can be thought of as a shared repository of GIS layers and tools. Individuals adding data to the repository share the understanding that the contributions to the repository that are being made are generally freely available for the common good, and those who are closest to a particular layer will retain stewardship responsibilities for it.
Typically, when an SDI is to be established, the architects will begin by establishing framework layers. The landscape level of the framework will often include road centerlines, hydrography, parcels, a land use and elevation model, and some form of aerial imagery. These framework layers serve as a foundation from which other layers can be derived and to which many different kinds of business processes can be attached. For example, parcels are an important foundation layer because zoning layers usually are designed tobe coincident with parcel boundaries, and parcels are often an anchor for municipal processes concerned with taxation, permitting and public safety. Building footprints are another framework layer in SDI.
Spatial data infrastructure frameworks all have some number of similar components as described above and can be implemented on a range of scales from the most local level, such as a small town, to a virtually global scale. The most complex and comprehensive SDIs are similar to the United States’ National Spatial Data Infrastructure and the European Community’s Infrastructure for Spatial Information in Europe (INSPIRE) program. Most US states also have well-developed spatial data infrastructures that are often commonly used, regardless of community size. Disaster response and recovery is one such example. Within disaster response and recovery situations, SDI can be applied or accessed and be an invaluable tool. In the event of an earthquake, the combination of map data can be used to answer a variety of questions about where things are, ranging from collapsed bridges to operational water and sewer lines, to roadways for evacuation – all of which are components of an SDI. As demonstrated in this example, one of the most important aspects of an SDI is that it is a system for sharing information across functional boundaries, across jurisdictions and across geographic boundaries.