Three-dimensional datasets with four or five dimensions are often referred to as "multidimensional" or "hyperdimensional" datasets. The additional dimensions beyond the three spatial dimensions (length, width, and height) are typically used to represent additional variables or attributes of the data.
For example, in a four-dimensional dataset, the first three dimensions might represent spatial coordinates, while the fourth dimension could represent a time variable or an additional attribute of the data. Similarly, in a five-dimensional dataset, the additional dimension could represent another attribute or variable.
These types of datasets are encountered in various fields such as physics, astronomy, computer science, and data analysis, where complex systems or phenomena require the consideration of multiple variables or attributes simultaneously. Analyzing and visualizing multidimensional datasets often involve specialized techniques like data reduction, dimensionality reduction, or advanced visualization methods to make sense of the data and extract meaningful insights.