User Assessment of Coastal DSS
443
expectation of GIS to develop models such as predictive models and to perform
complex analysis was recognised, although no specific applications were suggested.
By far the most often-mentioned weakness of GIS with respect to
manipulating and analysing coastal data by Phase I questionnaire respondents was the
expertise required and difficulty in learning software. GIS analysis also was seen as
having the potential to mislead decision-makers either unintentionally through
seductive “smoke and mirrors”, or intentionally through the bias of those controlling
the analysis and data manipulation. Several respondents noted the inadequacy of GIS
to easily support advanced modelling, particularly with respect to GIS coastal models.
The derivation of GIS coastal models was noted to be complicated by the complexity
and dynamic nature of coastal data. Again, GIS were regarded as promoting spatial
technology as a “technical fix”, while neglecting “subjective” or “fuzzy logic” analyses
of multivariate problems and data that cannot be easily represented spatially, such as
spiritual and cultural values.
Data
The importance of data for coastal management was emphasised by a third of Phase I
respondents who identified data availability as a critical success factor for coastal
management decision making. This was second only to co-operation and commitment
to the process. Data availability factors included:
sharing information among participants
all participants having the same information
obtaining accurate data
obtaining up-to-date data
and
providing technical and objective information to substantiate
discussions, rather than basing on opinion
Furthermore, as described earlier, in Phase II participants were asked to
describe techniques and methods for exploring alternatives. The majority of responses
focused on information support topics rather than analytical topics. Information
support topics included:
the compilation of a comprehensive database which covers the
broad range of natural and human elements
data acquisition techniques such as identifying information
needs, identifying information sources, data availability and
sampling techniques
and
443
expectation of GIS to develop models such as predictive models and to perform
complex analysis was recognised, although no specific applications were suggested.
By far the most often-mentioned weakness of GIS with respect to
manipulating and analysing coastal data by Phase I questionnaire respondents was the
expertise required and difficulty in learning software. GIS analysis also was seen as
having the potential to mislead decision-makers either unintentionally through
seductive “smoke and mirrors”, or intentionally through the bias of those controlling
the analysis and data manipulation. Several respondents noted the inadequacy of GIS
to easily support advanced modelling, particularly with respect to GIS coastal models.
The derivation of GIS coastal models was noted to be complicated by the complexity
and dynamic nature of coastal data. Again, GIS were regarded as promoting spatial
technology as a “technical fix”, while neglecting “subjective” or “fuzzy logic” analyses
of multivariate problems and data that cannot be easily represented spatially, such as
spiritual and cultural values.
Data
The importance of data for coastal management was emphasised by a third of Phase I
respondents who identified data availability as a critical success factor for coastal
management decision making. This was second only to co-operation and commitment
to the process. Data availability factors included:
sharing information among participants
all participants having the same information
obtaining accurate data
obtaining up-to-date data
and
providing technical and objective information to substantiate
discussions, rather than basing on opinion
Furthermore, as described earlier, in Phase II participants were asked to
describe techniques and methods for exploring alternatives. The majority of responses
focused on information support topics rather than analytical topics. Information
support topics included:
the compilation of a comprehensive database which covers the
broad range of natural and human elements
data acquisition techniques such as identifying information
needs, identifying information sources, data availability and
sampling techniques
and