9.5 Conceptual Tools and Approaches
for participation and implementation. A range of
participation, negotiation, and conflict resolution
skills and experience may be relevant to the initial
phase of identifying goals and beginning the
process (e.g., Susskind and Cruikshank, 1987;
Cormick et aI., 1996).
The specific goals lead to decisions on such matters as hardware and software to be used, standard
data formats, and transfer and access protocols. It
is critical that these be determined as early as possible, because so much depends on good choices
here-and decisions are often irreversible once investments have been made in hardware and software. Choices must be consensual among all major partners; any partner's decision to go its own
way can have major repercussions on integration
later. While data format conversion is improving
and there are at least a few widely used standards
(e.g., Autocad's "dxf"), standardization can prevent many problems.
Guiding the process of integration is almost certainly a task for a dedicated interdisciplinary
team-not too large, but with a range of expertise
and links to all the major participants. Team members must have strong technical, disciplinary, organizational, and political skills. Making such
teams work also involves clear mandates, strong
senior support, appropriate tools, freedom to find
what will work, and opportunities to make a difference in ways that provide incentives for participation and implementation.
Two useful, participatory components of the
process can be identified. First is collection of local knowledge through participatory and consultative methods. This can serve as an excellent crosscheck on scientific knowledge, add a diachronic
dimension, and involve local people in the process
(cf. Inglis, 1993). Second, ongoing reporting and
pilot testing of integration products are important
in order to determine their usability and utility. The
whole information integration process needs to be
adaptive and probably iterative.
9.5 Conceptual Tools
and Approaches
The most basic conceptual tool is a systems approach, as highlighted previously. Next is an understanding of the conceptual process of information integration as nonlinear, adaptive, and
iterative, by which we seek to make connections,
develop insights, and find new ways of understanding typically separate bits of information. At
one level, this is a matter of fostering creativity
125
(e.g., de Bono, 1994) and trying many approaches
to analysis (e.g., Wyatt, 1989). Beyond this, postnormal science (Funtowicz and Ravetz, 1993) ideas
may also be useful in understanding the changing
context of science, the participants, the nature of
the information used, and the need for adaptive
processes and management (see Chapter 4). One
way of conceptualizing the process of information
integration is as a dialectical process of analysis
and synthesis of information moving toward transdisciplinarity. Synthetic transdisciplinary thinking
is important, but so are analytic, descriptive inputs
from the usual disciplines.
Complementary to the basic framework provided
by systems analysis and models are approaches to
identify system connections and linkages. Graphical, systems-oriented methods have been used in
environmental impact assessment, including network diagrams and impact hypotheses (Shopley
and Fuggle, 1984; Bisset, 1987; Kennedy and Ross,
1992). This is really just one variation of models,
conceptual or otherwise, for the interaction of different parts of systems. More generally, it can often be useful to pick a concept or dimension of the
system as a transdisciplinary starting point and
work outward, multidisciplinarily, to build an integrated understanding. For example, landscape
ecology or geomorphic processes in land planning
(e.g., Wright, 1987), ecosystem functions (de Groot,
1992), environmental history (Moore and Witham,
1996), or ecological-economic-social connections
may be useful (Svedin, 1991).
Of course, many frameworks also exist for identifying needed information, planning collection and
categories, and organizing data collection in a range
of environmental contexts such as land classification, state of the environment reporting, and environmental monitoring (e.g., Marshall et al., 1996;
Rowe, 1996; also see review in Slocombe, 1992).
The ABC Resource Survey methodology (Bastedo
et aI., 1984), Rapid Rural Appraisal (RRA) and
Rapid Biodiversity Assessment frameworks are
particularly relevant models.
Another more specific, technical approach is to
develop sets of indicators or single, integrative,
quantitative indices. The literature on indicators
and indices is large and diverse (Kelly and Harwell, 1990; Victor et aI., 1991; Indicators Evaluation Task Force, 1996). Their strengths lie in the
ability to synthesize a wide range of information
into a single, at least ordinal, number. There are,
however, many concerns about how to define any
single number, including choices of information to
include, relative weightings, and overacceptance of
the value of the number (remember Gross National
for participation and implementation. A range of
participation, negotiation, and conflict resolution
skills and experience may be relevant to the initial
phase of identifying goals and beginning the
process (e.g., Susskind and Cruikshank, 1987;
Cormick et aI., 1996).
The specific goals lead to decisions on such matters as hardware and software to be used, standard
data formats, and transfer and access protocols. It
is critical that these be determined as early as possible, because so much depends on good choices
here-and decisions are often irreversible once investments have been made in hardware and software. Choices must be consensual among all major partners; any partner's decision to go its own
way can have major repercussions on integration
later. While data format conversion is improving
and there are at least a few widely used standards
(e.g., Autocad's "dxf"), standardization can prevent many problems.
Guiding the process of integration is almost certainly a task for a dedicated interdisciplinary
team-not too large, but with a range of expertise
and links to all the major participants. Team members must have strong technical, disciplinary, organizational, and political skills. Making such
teams work also involves clear mandates, strong
senior support, appropriate tools, freedom to find
what will work, and opportunities to make a difference in ways that provide incentives for participation and implementation.
Two useful, participatory components of the
process can be identified. First is collection of local knowledge through participatory and consultative methods. This can serve as an excellent crosscheck on scientific knowledge, add a diachronic
dimension, and involve local people in the process
(cf. Inglis, 1993). Second, ongoing reporting and
pilot testing of integration products are important
in order to determine their usability and utility. The
whole information integration process needs to be
adaptive and probably iterative.
9.5 Conceptual Tools
and Approaches
The most basic conceptual tool is a systems approach, as highlighted previously. Next is an understanding of the conceptual process of information integration as nonlinear, adaptive, and
iterative, by which we seek to make connections,
develop insights, and find new ways of understanding typically separate bits of information. At
one level, this is a matter of fostering creativity
125
(e.g., de Bono, 1994) and trying many approaches
to analysis (e.g., Wyatt, 1989). Beyond this, postnormal science (Funtowicz and Ravetz, 1993) ideas
may also be useful in understanding the changing
context of science, the participants, the nature of
the information used, and the need for adaptive
processes and management (see Chapter 4). One
way of conceptualizing the process of information
integration is as a dialectical process of analysis
and synthesis of information moving toward transdisciplinarity. Synthetic transdisciplinary thinking
is important, but so are analytic, descriptive inputs
from the usual disciplines.
Complementary to the basic framework provided
by systems analysis and models are approaches to
identify system connections and linkages. Graphical, systems-oriented methods have been used in
environmental impact assessment, including network diagrams and impact hypotheses (Shopley
and Fuggle, 1984; Bisset, 1987; Kennedy and Ross,
1992). This is really just one variation of models,
conceptual or otherwise, for the interaction of different parts of systems. More generally, it can often be useful to pick a concept or dimension of the
system as a transdisciplinary starting point and
work outward, multidisciplinarily, to build an integrated understanding. For example, landscape
ecology or geomorphic processes in land planning
(e.g., Wright, 1987), ecosystem functions (de Groot,
1992), environmental history (Moore and Witham,
1996), or ecological-economic-social connections
may be useful (Svedin, 1991).
Of course, many frameworks also exist for identifying needed information, planning collection and
categories, and organizing data collection in a range
of environmental contexts such as land classification, state of the environment reporting, and environmental monitoring (e.g., Marshall et al., 1996;
Rowe, 1996; also see review in Slocombe, 1992).
The ABC Resource Survey methodology (Bastedo
et aI., 1984), Rapid Rural Appraisal (RRA) and
Rapid Biodiversity Assessment frameworks are
particularly relevant models.
Another more specific, technical approach is to
develop sets of indicators or single, integrative,
quantitative indices. The literature on indicators
and indices is large and diverse (Kelly and Harwell, 1990; Victor et aI., 1991; Indicators Evaluation Task Force, 1996). Their strengths lie in the
ability to synthesize a wide range of information
into a single, at least ordinal, number. There are,
however, many concerns about how to define any
single number, including choices of information to
include, relative weightings, and overacceptance of
the value of the number (remember Gross National