To provide on-line geographic information services effectively in an open,
distributed network environment, a new paradigm of GIS architecture must be
established and adopted. The architecture of distributed GIServices should be
platform-independent and application-independent. It should provide flexible and
distributed geographic information services on the Internet, without the
constraints of computer hardware and operating systems. The following figure shows three
alternatives for GIS architecture.
Three alternatives for GIS
Traditional GISystems are closed, centralized systems, incorporating
interfaces, programs and data. Each system is platform-dependent and
application-dependent. Migrating traditional GISystems into different operating
systems or platforms is difficult. Different GIS applications may require
different GIS packages and architecture design. Every element is embedded inside
traditional GISystems and can not be separated from the rest of the
Client/Server GISystems are based on generic client/server architecture in
network design. The client-side components are separated from server-side
components (databases and programs). Client/Server architecture allows
distributed clients to access a server remotely by using distributed computing
techniques, such as Remote Procedure Calls (RPC), or by using database
connectivity techniques, such as Open Database Connectivity (ODBC). The
client-side components are usually platform-independent, requiring only an
Internet browser to run. However, each client component can access only one
specified server at one time. The software components on client machines and
server machines are different and not interchangeable. Different geographic
information servers come with different client-server connection frameworks,
which can not be shared.
Distributed GIServices (Peer-to-Peer GIS nodes) are built upon a more advanced architecture.
The most significant difference is the adoption of distributed
component technology, which can access and interact with multiple and
heterogeneous systems and platforms, without the constraints of traditional
client/server relationships. Under a distributed GIService architecture, there
is no difference between a client and a server. Every GIS node embeds GIS
programs and geodata, and can become a client or a server based on the task at
hand. A client is defined as the requester of a service in a network. A server
provides a service. A distributed GIService architecture permits dynamic
combinations and linkages of geodata objects and GIS programs via networking.
What is Peer-to-Peer? What kinds of
GIServices can utilize this network model?
What are the similarities and differences between the Napster.COM
and "Data Clearinghouse"?
(This picture is from
"In this animation, the coloured bars beneath all of the clients represent
individual pieces of the file. After the initial pieces transfer from the seed,
the pieces are individually transferred from client to client. The original
seeder only needs to send out one copy of the file for all the clients to
receive a copy." (cited from
The Power of Networking
Value-added Information Processes
One implication of distributed GIServices is to add value to information
processes. A value-added information process is an information service that uses
available facilities to add additional services and in doing so, increases the
total value of services. By combining distributed GIS components and geodata
objects on the Internet, GIServices will be able to provide more types of
services and generate added worth to traditional GISystems. Two types of
value-added processes could work this way.
First, distributed GIServices can generate new services and add new values by
combining different GIS components. Traditional GISystems have limited GIS
functions inside the closed system framework. The value (X1) generated from a
single GISystem is constrained by system functions and closed architecture. With
the advantages of LEGO-like GIS components, distributed GIServices can combine
different functions/components to combine values (X1 + X2 + X3) under the
The new values generated from the
usage of GIS components.
The second type of value-added process is that multiple GIS projects can
access a single GIS database remotely via the network, adding value to it. Traditional GISystems lack remote database access capabilities and
require manual data conversion procedures. By adopting standardized
communication protocols and agent-based data conversion approaches, distributed
GIServices can facilitate the reuse of databases and reduce the cost of new data
generations for GIS projects. For example, a completed Boulder City GIS database
can be used for three different projects, such as Wal-Mart site selection, urban
zoning, and the school bus routing analysis. The total value of Boulder City
database becomes more valuable than if used by a single application. The more a
database is used, the more valuable that database becomes. In other words, the
distributed database access and management will encourage reuse of existing
geodata objects and prevent redundancy of data reproduction. The cost of data
production takes up 70% of the total application cost; this cut in data
production can also save labor and application program money and add value to
The value-added process in distributed
In general, the life cycle of information value for distributed GIServices is
quite different from traditional GISystems. The following figure illustrates the life
cycle of information value in traditional GISystems.
The life cycle of information value in
(Costs are assumed to account for
inflation over time.)
The initial value of information is fixed (V0) in traditional GISystems. If
information items are not updated, the value will decrease gradually over time
due to the decrease in data quality, currentness, and the increase in data
uncertainty. Therefore, GIS database managers have to update information items
frequently in order to keep the information value relatively stable.
The cost of database management in traditional GISystems is also illustrated
in the previous figure. The initial cost carries a significant startup expense due to the
creation of new databases. The subsequent operation cost will be lower than the
initial cost because the GIS database has been established, but the cost will
increase again concurrently with data update operations.
The following figure indicates a different life cycle of information value in
distributed GIServices. The value of information items will not decrease but
increase gradually over time by sharing information with others.
The life cycle of information value in
(Costs are assumed to account for
inflation over time.)
There are three phases in the life cycle of information value in distributed
GIServices. The first phase (I) is the initial stage of data sharing and
exchange. The number of users is limited at this time because not many users are
aware that the information item is available on-line. As more people become
aware, data will be used in multiple applications (phase II), and the value of
information will increase during this time. In phase III, information sharing
will decrease because data become out of date and used only for specialized
tasks (historical). The growth of information value will slow down. When the
factor of information uncertainty becomes higher than the factor of corrected
errors, the growth of information value will drop or perhaps stabilize, unless
the data retain historical value.
The cost of database management in distributed GIServices also has three
stages. The initial cost requires a significant startup expense in
the first phase (I), same as the traditional databases. The subsequent operation
cost in phase II will be much lower than that of the traditional databases
because as more people use the information, they will report errors or
incompleteness to help data providers correct errors and improve the data
quality. When the number of users decreases in phase III, the cost of GIS
database management will increase again concurrently with data update
There are three phases similar to the life cycle of information value. The
first phase (I) is the initial data sharing and exchange. Few user feedbacks and
corrections happen at this stage and the information uncertainty increases
gradually because of temporal currentness. In phase II, the number of corrected
errors (Cn) will increase along with the popularity of the information items and
allow the original data providers to improve the data quality. The feedback from
users will slow down the growth of information uncertainty. Eventually, the
information uncertainty (Un) will rise again over time because of temporal
currentness and the decrease of corrected errors from users (phase III).
To summarize, distributing GIServices can add value to information.
Distributed GIServices can generate new information value by sharing geodata
objects, by combining GIS components, and by exchanging knowledge and metadata
between the members of the GIS community. Moreover, distributed database access
and maintenance can reduce the cost of database management. In short,
distributed GIServices will encourage collaborative error checking processes and
improve the data quality by user feedback and update.
In the computer industry, an example of value-added information processes can
be found in the development of the Linux operating system (Welsh et. al., 1999).
Because of the open environment provided by the Linux, the feedback from a large
number of users improved the kernel of Linux, making the operating system more
stable and therefore, more useful. By releasing the power of autocratic control,
the developers of Linux get thousands of free software engineers and programmers
working together via the Internet to improve this operating system. Thousands of
Linux applications are being developed by software companies, which will add
value to the Linux operating system and to software companies. Distributed
GIServices borrow the development strategy from the Linux example by releasing
the control of data objects and GIS components. The sharing of data sets and
programs for distributed GIServices will encourage the reuse of these computing
resources, improve data quality and reduce uncertainty, and reduce the cost of
data production and GIS programming.
The Exponential Growth of GIS
The second implication of distributed GIServices is the exponential growth of
GIS network values. As mentioned earlier, the increasing value of distributed
GIServices is derived from sharing and exchanging information and programs. The
basic requirement for sharing is the establishment of network connections for
GIServices. If a network builds more connections, the more sharing and
exchanging events may happen, and then more value would be generated from the
Kelly (1998: 23) states that "mathematics says the sum of value of a
network increases as the square of the number of members. In other words, as the
number of nodes in a network increases arithmetically, the value of the network
increases exponentially." According to his statements, a network value
will be increased according to the growth of nodes and links in a distributed
GIServices network. The mathematical results are shown in the following Figure.
The exponential growth of
distributed GIServices network.
This figure illustrates the growth of simplified GIS nodes and the network
connections in distributed GIServices. In this figure, each GIS node is
simplified as one grouped geodata object and one GIS component (two dots inside
each box). In the real world, the arrangement of geodata and components may be
more complicated in distributed network environments. If we only consider the
simplified situation, the growth of network connections comes along with the
increasing number of GIS nodes. The number of GIS nodes increases arithmetically
from 1, 2, 3 to 10, and the number of network connections increases
exponentially from 4, 12, 23, to 180. Along with the exponential growth of
connections, the values of the whole network will also grow exponentially.
This example shows the unique feature of network development. It also
illustrates that the power of network comes with the increasing number of
members in the network. In order to know how network connections facilitate the
increase of the total value of network, the following discussion will introduce three scenarios and put them together inside an
integrated GIServices network. By integrating computer resources, geodata
objects, and GIS components in all three scenarios, the three GIS users (Mike,
Dick, and Eva) can generate more valuable services for themselves. It can also
demonstrate the exponential growth of network values. The following paragraphs
will describe briefly the original design of the three scenarios and illustrate
their advantages and new values if we combine them together in an integrated
The first scenario illustrates
that Mike, a GIS user, plans a trip from Boulder, Colorado to Utah’s Arches
National Park during the spring break. He acquires related map information
(highways, park trails, city roads, and hotel locations) from the Internet,
prints out his travel maps, and makes an on-line hotel reservation in Moab, with
the help of a hotel reservation agent. In the second scenario,
Dick wants to locate a site for a new Wal-Mart store in Boulder. He obtains
related map information from the data server in Boulder’ Planning and Police
department and performs a GIS overlay analysis for his task. He also downloads a
GIS component called [Shape Fitting Analysis] to help him finish the location
analysis more efficiently. The third scenario indicates that Eva, a homemaker, wants to visit her friend in Superior,
Colorado. She uses her Palm-size PC, wireless phone and the Global Positioning
System (GPS) device in her car to navigate to her friend’s house. The Colorado
data sets in her Palm-size PC has been updated in real-time via her cellular
phone from the GPS-data.COM server. She also uses the same service to choose a
Chinese restaurant close to her friend’s house.
By integrating all computer resources, geodata objects, GIS components, users
in the three scenarios described above, the new GIService framework
will be able to provide many new services and add new value for the three GIS
users (Figure 6-7).
The integrated GIService network for
The following is a list of examples of possible new services in the
integrated GIService framework. GIS users can utilize the integrated computer
resources and accomplish different GIS tasks according to their needs.
- Mike can use the [Boulder GIS Database] and [Overlay Analysis] to make a
housing plan and find the potential housing area for his family.
- Mike can use the [Point of Interest (Colorado)] data object to locate the
possible gas stations for his spring break vacation.
- Dick can use the [Roads (Colorado)] data object and the routing function
in [Travel Plan] to make a routing plan for the UPS delivering system.
- Dick can use the routing function in the [Travel Plan] component and
[Boulder GIS Database] to generate the shortest route for the school bus.
- Eva can use the [Travel Plan] component with external database systems to
purchase an airplane ticket and rent a car.
- Eva can use the [Boulder Crime Rate Index] data objects generated from
Dick’s machine to monitor neighborhood safety for her community.
These six examples mentioned above are some representative applications and
projects which can benefit from combining the three scenarios. Under an
integrated GIServices framework, both geospatial data objects and GIS programs
are shared and can provide more flexible information services for different
users. In fact, dozens of new services can be generated from the integrated
network of the three scenarios. In short, the exponential growth of network
values is a very attractive advantage for the deployment of distributed
GIServices network. The exponential growth will attract more people and projects
to participate in the network with a distributed, dynamic architecture. As more
people join in the GIS network, more information and programs will be available
for sharing and exchanging, and thus the GIS network will become more valuable.
As the GIS network becomes more valuable, it will attract more people to join
in. Therefore, the positive reinforcement can ensure sustainable growth of
distributed GIServices and the popular use of geographic information in the
Related Links and Books:
Rules for the New Economy
the Swarm. A bit of intelligence in a lot of places—for example, a
microchip on every can of soup in a grocery store—is better than a lot
of intelligence in a single place.
Returns. The value of a network like the Internet increases
explosively the more people you add to it.
not scarcity, is key. The more people who use a technology, such as
fax machines or automated teller machines, the more valuable it is.
“Avoid proprietary systems,” Kelly writes, referring to online
services such as America Online. “Sooner or later closed systems have to
open up, or die.”
the Free. Prices in today’s economy fall inexorably as products
flood the market. Don’t fight it, because demand will rise faster than
prices will fall. The only thing that is scarce is human attention.
the Web first. People are loyal not to a company, but to a network, so
spend your time setting standards and building on the ones that people
have already accepted.
go at the top. To go from success to greater success, organizations
must devolve—“do business less efficiently, with less perfection,
relative to its current niche,” writes Kelly. That means “creative
destruction,” or walking away from successful business practices.
from places to spaces. The economy is moving from a physically defined
world to an electronic one, which leads to the rise of a new set of
intermediaries and communities based on special interests. “The Net
shifts from mass media to mess media,” Kelly writes.
harmony means all flux. If a company settles into harmony and
equilibrium, it will eventually stagnate and die. The key to robust growth
for all industries is to imitate the history of the movie business, which
transformed from the Hollywood studio system to a collection of
tech. The goal of the network economy is to amplify relationships.
Companies should go from creating what the customer wants, to remembering
it, to anticipating it, to changing it. Encouraging customers to talk to
one another and form affinity groups will make them smarter and more
opportunities before efficiencies. Don’t solve problems, pursue
opportunities. Waste is a beneficial byproduct of creativity. If you want
to make people more productive, give their work to a machine.
Source: New Rules for the New Economy: 10 Radical Strategies for a Connected
World by Kevin Kelly (1999).
The Progress of Network Technology is
an "Evolution" or
Who can control the NET? Government?
Public? or Private Sector?
Two alternative path (Open Standard vs.
In general, the
deployment of GIServices will facilitate scientific data management in
geographic domain. The scientific community, through government science
agencies, professional societies, and the actions of individual scientists,
should improve technical organization and management of scientific data
(National Research Council, 1998) in the following ways:
with the information and computer science communities to increase their
involvement in scientific information management;
computer science research in database technology, particularly to strengthen
standards for self-describing data representations, efficient storage of large
data sets, and integration of standards for configuration management;
science education and reward systems in the area of scientific data
the funding of data compilation and evaluation projects, and of data rescue
efforts for important data sets in transient or obsolete forms, especially
by scientists in developing countries.
(National Research Council, 1998, p 13)
Twentieth century, the visible world was re-shaped by the development of
engineering technology. People used technology to
create skyscrapers, airplanes, space shuttles, water dams, etc.
Twenty-first century, the invisible world is going to change by the progress
of information technology. The developments of the
Internet, wireless phones, biochemistry engineering, DNA-research, e-commerce,
virtual reality, and the Web, have already made our lives very different, and
will continue to do so. However, when technology is changing the world inside
out, one needs to consider whether to use the technology.
“The more interconnected a technology is, the more opportunities it spawns
for both use and misuse” (Kevin Kelly, 1998, p. 45.). While enjoying
the power of network-based GIServices in the Twenty-first century, one may want
to ask if technology is being used or misused. This dissertation designed a
dynamic framework for the GIS community to adopt new technologies in the
future. However, the GIS community will have to ensure that these new
technologies will be used appropriately to facilitate research in geography, the
growth of GIS industry, and better quality of life for the public.
Welsh, M., Dalheimer, M. K., Kaufman, L., & Welsh, M. (1999).
Linux (third edition). Sebastopol, California: O’Reilly &