Topic Summary Views for Exploration of Large Scholarly Datasets

In this article, we present the E-sch approach for exploration of large scholarly datasets based on topic summary views. The goal of E-sch is to semantically summarize the dataset related to a potentially very large number of scholar publications (e.g., millions) by a list of few thousands topics, up to an ultimate list of hundreds of topic summaries to use for analyzing research dynamics and evolution at a more semantic, high-level of inquiry. Filter and Slice operators are defined in E-sch to enforce interactive scholarly data exploration along thematic and temporal perspectives.