9.8 Conclusions
can help human users to define and answer questions, find and display relevant information, and in
some cases develop prescriptions for action. Such
systems usually entail efforts to link several of the
above tools with special rule-based systems (expert
systems: Saunders et aI., 1992; Wright et aI., 1993)
that in some sense can reason about the information contained in them. This mayor may not include spatial data in a GIS, data visualization tools,
and simulations. Fedra (1995) provides a nice
overview, and Baird et ai. (1994), McClean et al.
(1995), and Reynolds et ai. (1996) provide relevant
examples in fire management, land-use planning,
and watershed analysis, respectively.
Complex mu1titoo1 and knowledge-based systems can be useful on large projects where they will
have very wide applications; however, they are not
really necessary for useful information, and probably should not be developed before many of the
other approaches discussed in this paper have been
tried. The ultimate goal of information integration
should be flexible, integrated systems that can handle, display, and interpret almost any kind of information. But systems also should be transparent
and accessible and not consume resources to the
extent that basic tasks like data collection, analysis, and consultation are neglected. All tools have
their pluses and minuses, and the more complex the
tool, the harder it is to remain aware of them (cf.
Pickles, 1995, on GIS).
9.7 Trends and Opportunities
The most basic prerequisite for integration of biological, physical, and human information is its
availability. Some technologies are making data
more available, yet other trends, such as government cutbacks and cost recovery programs, are ending data collection or making data much more expensive to acquire. This is not a good trend from
the perspective of ecosystem management, ecological assessment, or efforts to integrate diverse information.
Communication technologies such as the Internet and the WWW are making more information
available and also providing a prime vehicle for the
display of integrated information. The power of distributed computing in information systems was
mentioned previously; the potential for linking networks of computers to increase computing power
also has implications for simulation of complex,
spatial systems (Alves, 1996). Posting information
integration efforts on the web is a key opportunity
to foster critical evaluation and progress. Other
newer technologies, such as interactive electronic
127
blackboards and videoconferencing, could further
support the processes of integration in the future.
Rapid advances in computer processing power
and fixed and movable storage media are making
data integration more and more feasible. We could
argue, however, that there is still a shortage of good
integrated software tools for all the functions described here-at any price, never mind mass market prices. Future developments in knowledgebased tools will almost certainly have great impact
in automating and organizing the volumes of information available and under development.
All these trends and technologies, as well as the
asking of questions that require synthetic answers,
are promoting better use of existing data, as well
as targeted efforts to use simple tools such as workshops and simulation to reassess and integrate the
data (e.g., Baskin, 1997). In addition, the development of complex systems ideas such as chaos, fractals, and self-organization is providing new paradigms and analytic tools for understanding complex
systems (e.g., see Chapters 2, 14 and 15). Although
their influence is still limited at a practical level, it
will almost certainly grow (cf. Grzybowski and
Slocombe, 1988; Slocombe, 1990, 1997; J!Ilrgensen
et aI., 1992; Mainzer, 1996). Somewhat similarly,
the growing interest in transdisciplinarity and integration has been catalyzed by systems and simulation ideas, as well as the need to understand the dynamics of complex systems. This interest itself is
fostering more and more studies that seek to integrate understanding of change in a watershed or
ecosystem (Smith, 1994; Frissel and Bayles, 1996).
This alone will produce a good deal of learning and
the experimentation on which it is based.
9.8 Conclusions
Integration from different domains, formats, and
sources is a complex task. It often takes place with
limited time and pressure to reach management decisions and faces debate over the validity, utility,
and nature of the results. Equally, information integration faces technical and conceptual challenges.
This chapter advocates an approach that combines
advance planning to determine goals and standards
with appropriate conceptual, process, and technical
tools to develop useful, flexible information products. The overall process needs to be adaptive, iterative, and nonlinear and needs to be tailored to a
particular information integration context (see Figure 9.1).
Certainly, it is important to use process and conceptual tools as well as technical ones, although
their relative importance will vary depending on
can help human users to define and answer questions, find and display relevant information, and in
some cases develop prescriptions for action. Such
systems usually entail efforts to link several of the
above tools with special rule-based systems (expert
systems: Saunders et aI., 1992; Wright et aI., 1993)
that in some sense can reason about the information contained in them. This mayor may not include spatial data in a GIS, data visualization tools,
and simulations. Fedra (1995) provides a nice
overview, and Baird et ai. (1994), McClean et al.
(1995), and Reynolds et ai. (1996) provide relevant
examples in fire management, land-use planning,
and watershed analysis, respectively.
Complex mu1titoo1 and knowledge-based systems can be useful on large projects where they will
have very wide applications; however, they are not
really necessary for useful information, and probably should not be developed before many of the
other approaches discussed in this paper have been
tried. The ultimate goal of information integration
should be flexible, integrated systems that can handle, display, and interpret almost any kind of information. But systems also should be transparent
and accessible and not consume resources to the
extent that basic tasks like data collection, analysis, and consultation are neglected. All tools have
their pluses and minuses, and the more complex the
tool, the harder it is to remain aware of them (cf.
Pickles, 1995, on GIS).
9.7 Trends and Opportunities
The most basic prerequisite for integration of biological, physical, and human information is its
availability. Some technologies are making data
more available, yet other trends, such as government cutbacks and cost recovery programs, are ending data collection or making data much more expensive to acquire. This is not a good trend from
the perspective of ecosystem management, ecological assessment, or efforts to integrate diverse information.
Communication technologies such as the Internet and the WWW are making more information
available and also providing a prime vehicle for the
display of integrated information. The power of distributed computing in information systems was
mentioned previously; the potential for linking networks of computers to increase computing power
also has implications for simulation of complex,
spatial systems (Alves, 1996). Posting information
integration efforts on the web is a key opportunity
to foster critical evaluation and progress. Other
newer technologies, such as interactive electronic
127
blackboards and videoconferencing, could further
support the processes of integration in the future.
Rapid advances in computer processing power
and fixed and movable storage media are making
data integration more and more feasible. We could
argue, however, that there is still a shortage of good
integrated software tools for all the functions described here-at any price, never mind mass market prices. Future developments in knowledgebased tools will almost certainly have great impact
in automating and organizing the volumes of information available and under development.
All these trends and technologies, as well as the
asking of questions that require synthetic answers,
are promoting better use of existing data, as well
as targeted efforts to use simple tools such as workshops and simulation to reassess and integrate the
data (e.g., Baskin, 1997). In addition, the development of complex systems ideas such as chaos, fractals, and self-organization is providing new paradigms and analytic tools for understanding complex
systems (e.g., see Chapters 2, 14 and 15). Although
their influence is still limited at a practical level, it
will almost certainly grow (cf. Grzybowski and
Slocombe, 1988; Slocombe, 1990, 1997; J!Ilrgensen
et aI., 1992; Mainzer, 1996). Somewhat similarly,
the growing interest in transdisciplinarity and integration has been catalyzed by systems and simulation ideas, as well as the need to understand the dynamics of complex systems. This interest itself is
fostering more and more studies that seek to integrate understanding of change in a watershed or
ecosystem (Smith, 1994; Frissel and Bayles, 1996).
This alone will produce a good deal of learning and
the experimentation on which it is based.
9.8 Conclusions
Integration from different domains, formats, and
sources is a complex task. It often takes place with
limited time and pressure to reach management decisions and faces debate over the validity, utility,
and nature of the results. Equally, information integration faces technical and conceptual challenges.
This chapter advocates an approach that combines
advance planning to determine goals and standards
with appropriate conceptual, process, and technical
tools to develop useful, flexible information products. The overall process needs to be adaptive, iterative, and nonlinear and needs to be tailored to a
particular information integration context (see Figure 9.1).
Certainly, it is important to use process and conceptual tools as well as technical ones, although
their relative importance will vary depending on