Preface
IX
Distinct features of ecological informatics are: data integration across
ecosystem categories and levels of complexity, inference from data pattern to
ecological processes, and adaptive simulation and prediction of ecosystems.
Biologically-inspired computation techniques such as fuzzy logic, artificial neural
networks, evolutionary algorithms and adaptive agents are considered as core
concepts of ecological informatics.
Fig. 1 represents the current scope of ecological informatics indicating that
ecological data is consecutively refined to ecological information, ecosystem
theory and ecosystem decision support by two basic computational operations:
data archival, retrieval and visualization, and ecosystem analysis, synthesis and
forecasting.
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ECOLOGICAL INFORMATION
ECOSYSTEM THEORY
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DATA ARCHIVAL,
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RETRIEVAL
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VISUALISATION
FORECASTING
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TECHNOLOGY:
High Performance Computing
Object-Oriented Data Representation
Internet
Remote Sensing
GIS
Animation
etc.
COMPUTATIONAL
TECHNOLOGY:
High Performance Computing
Cellular Automata
Fuzzy Logic
Artificial Neural Networks
Genetic/Evolutionary Aigorithms
Hybrid Models
Adaptive Agents
Resembling Techniques
etc.
Figure 1. Scope of Ecological Informatics
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Computational technologies currently considered being crucial for data
archival, retrieval and visualization are:
- High performance computing to provide high-speed data access and processing,
and large internal storage (RAM);
- Object-oriented data representation to facilitate data standardization and data
integration by the embodiment of metadata and data operations into data
structures;
- Internet to facilitate sharing of dynamic, multi-authored data sets, and parallel
posting and retrieval of data;
- Remote sensing and GIS to facilitate spatial data visualization and acquisition;
- Animation to facilitate pictorial visualization and simulation.