This paper presents a new analysis method and the functions for multidimensional sensing data, including multi-parameter sensor data and series of sensing images, for a collaborative knowledge creation system called 5D World Map System, and the applications in the field of multidisciplinary environmental researches. The main feature of 5D World Map System is to provide a platform of collaborative work for users to perform a global analysis for sensing data in a physical space along with the related multimedia data in a cyber space, on a single view of time-series maps based on the spatiotemporal and semantic correlation calculations. The concrete target data of the proposed new method and functions for world-wide evaluation is (1) multi-parameter sensor data such as water-quality, air-quality, soil-quality etc., and (2) multispectral and natural-color image data taken by moving cameras such as UAV/car-mounted cameras or mobile phones for environmental monitoring. The proposed world-wide evaluation functions enable multiple remote-users to acquire real-time sensing data from multiple sites around the world, perform analytical visualizations of the acquired sensing data by a selected world environmental standard to discover the incidental phenomena, and provide the analysed results to related users’ terminal equipment automatically. These new functions realize a new multidimensional data analysis and knowledge sharing for a collaborative environment. Especially, in the world-wide evaluation function, applying the concept of “semantic computing” to determining the environmental-quality levels of multiple places around the world. The results are able to be analysed by the time-series difference of the value of each place, the differences between the values of multiple places in a focused area, and the time-series differences between the values of multiple places, and calculated as a “world ranking”, to detect and predict an environmental irregularity and incident. In our world-wide evaluation method, we define the environmental impacts as “semantics” of environmental condition. The originality of our method is in (1) an interpreter to convert the numerical environmental quality-level to the qualitative impacts/meanings by the sentence or a set of words that even non-specialists or ordinary people are able to understand, and (2) a visualizer to realize a global comparison and “world-ranking” with a semantic computing for targeting the multi-parameter sensing values of multiple sites around the world.