Mission of ISEI:

 The International Society for Ecological Informatics (ISEI) is devoted to promote: 

(1) the concept of Ecological Informatics by organising bi-annual international conferences, providing relevant information through its web page, newsletters and journal being issued by 2005, and networking specialised research groups 

(2) interdisciplinary research on information processing in ecosystems, biologically-inspired computation, data management and visualisation, and 

(3) education and training in ecologically-oriented informatics. 

Definition of Ecological Informatics:

Ecological Informatics is defined as interdisciplinary framework promoting the use of advanced computational technology for the elucidation of principles of information processing at and between all levels of complexity of ecosystems - from genes to ecological networks -, and aiding transparent decision-making in relation to important issues in ecology such as sustainability, biodiversity and global warming. 

Distinct Features of Ecological Informatics:

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, cellular automata, artificial neural networks, evolutionary algorithms and adaptive agents are considered as core concepts of ecological informatics. 

Scope of Ecological Informatics:

Figure 1. Scope 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. 

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. Following computational technologies are currently considered to be crucial for ecosystems analysis, synthesis and forecasting: 

- High performance computing to provide high-speed data access and processing and large internal storage (RAM), and to facilitate high speed simulations; 

- Internet and www to facilitate interactive and online simulation as well as software and model sharing; 

- Cellular automata to facilitate spatio-temporal and individual-based simulation; 

- Fuzzy logic to represent and process uncertain data; 

- Artificial neural networks to facilitate multivariate nonlinear regression, ordination and clustering, multivariate time series analysis, image analysis at micro to macro scale; 

- Genetic and evolutionary algorithms for the discovery and evolving of multivariate nonlinear rules, functions, differential equations and artificial neural networks;

- Hybrid and AI models by the embodiment of evolutionary algorithms in process-based differential equations, the embodiment of fuzzy logic in artificial neural networks or knowledge processing; 

- Adaptive agents to facilitate adaptive simulation and prediction of ecosystem composition and evolution.