George W. Furnas introduced the concept of generalized fisheye views, which balance local detail and global context by trading off a priori importance against distance. This approach is inspired by how humans naturally represent large structures, such as geographic maps or organizational charts. Fisheye views are particularly useful for displaying large information structures like programs, databases, and text, as they allow users to focus on relevant details while still understanding the overall structure. The paper explores naturally occurring fisheye views, such as how people represent states, presidents, and news stories. These views often emphasize what is "close to home" or of high a priori importance. The authors then formalize the concept of fisheye views using a "Degree of Interest" (DOI) function, which assigns interest levels based on a priori importance and distance from the current focus. For tree structures, the DOI function is defined as the sum of the distance from the root and the distance from the current focus, with higher values indicating more interest. The authors developed a program for creating fisheye views of tree-structured text files, demonstrating how such views can be applied to programming and other structured data. They also conducted an experiment showing that fisheye views are more effective than flat views for navigating and understanding large, unfamiliar structures. The results indicate that fisheye views provide a more efficient way to balance local detail and global context, making them valuable for computer interfaces. The paper concludes that fisheye views can be applied to a wide variety of information structures, including lists, trees, graphs, and Euclidean spaces. The concept is not limited to spatial structures and can be used for semantic networks and other non-geometric data. The authors also mention the development of a fisheye calendar, which shows different levels of detail for different time frames, demonstrating the versatility of fisheye views in various domains.George W. Furnas introduced the concept of generalized fisheye views, which balance local detail and global context by trading off a priori importance against distance. This approach is inspired by how humans naturally represent large structures, such as geographic maps or organizational charts. Fisheye views are particularly useful for displaying large information structures like programs, databases, and text, as they allow users to focus on relevant details while still understanding the overall structure. The paper explores naturally occurring fisheye views, such as how people represent states, presidents, and news stories. These views often emphasize what is "close to home" or of high a priori importance. The authors then formalize the concept of fisheye views using a "Degree of Interest" (DOI) function, which assigns interest levels based on a priori importance and distance from the current focus. For tree structures, the DOI function is defined as the sum of the distance from the root and the distance from the current focus, with higher values indicating more interest. The authors developed a program for creating fisheye views of tree-structured text files, demonstrating how such views can be applied to programming and other structured data. They also conducted an experiment showing that fisheye views are more effective than flat views for navigating and understanding large, unfamiliar structures. The results indicate that fisheye views provide a more efficient way to balance local detail and global context, making them valuable for computer interfaces. The paper concludes that fisheye views can be applied to a wide variety of information structures, including lists, trees, graphs, and Euclidean spaces. The concept is not limited to spatial structures and can be used for semantic networks and other non-geometric data. The authors also mention the development of a fisheye calendar, which shows different levels of detail for different time frames, demonstrating the versatility of fisheye views in various domains.