The significant computation in global environmental analysis is “context-oriented semantic computing” to interpret the meanings of natural phenomena occurring in the nature. Our semantic computing method realizes the semantic interpretation of natural phenomena and analyzes the changes of various environmental situations. It is important to realize global environmental computing methodology for analyzing difference and diversity of nature and livings in a context dependent way with a large amount of information resources in global environments. Semantic computations contribute to make “appropriate and urgent solutions” to the changes of environmental situations.
It is also significant to memorize those situations and compute environment changes in various aspects and contexts, in order to discover what are happening in the nature of our planet. We have various (almost infinite) aspects and contexts in environmental changes, and it is essential to realize a new analyzer for computing the meanings of those situations and making solutions for discovering actual aspects and contexts.
We propose a new method for semantic computing in our Multi-dimensional World map. We utilize a multi-dimensional computing model, the Mathematical Model of Meaning (MMM) [1–3], and a multi-dimensional space with an adaptive axis adjustment mechanism. In semantic computing for environmental changes in multi-aspects and contexts, we present important functional pillars for analyzing natural environment situations. We also present a method to analyze and visualize the highlighted pillars using our Multi-dimensional World Map (5-Dimensional World Map) System.
We introduce the concept of “SPA (Sensing, Processing and Analytical Actuation Functions)” for realizing a global environmental system, to apply it to Multi-dimensional World Map System. This concept is essential to design environmental systems with Physical-Cyber integration to detect environmental phenomena in a physical-space (real space), map them to cyber-space to make analytical and semantic computing, and actuate the analytically computed results to the real space with visualization for expressing environmental phenomena, causalities and influences. This system currently realizes the integration and semantic-analysis for KEIO-MDBL-UN-ESCAP Joint system for global ocean-water analysis with image databases. We have implemented an actual space integration system for accessing environmental information resources and image analysis.