Applying Multidimensional Navigation and Explanation in Semantic Dataset Summarization

A key objective of multidimensional dataset analysis is to reveal patterns of interest to users, but can be difficult to conduct due to the challenges of both presenting and navigating large datasets. This work explores how initial summarizations of multidimensional datasets can be generated (designed to reduce the number of data points which would need to be displayed), using summarization policies based on provided dataset values. Additionally, functionality for explaining the derivation of summarizations is being designed in line with prior work on aiding analyst interactions with data processing systems. To help drive development of this work, as well as provide illustrative use cases, we are presently designing a dataset summarization generator as part of greater work being done on an infrastructure for managing evidence of technical emergence in varying research disciplines via automated review of published materials.