Range searching is a classical problem that has been studied extensively both in computational geometry and databases, and problem to which Jirka contributed extensively. Over the last three decades, several sophisticated geometric techniques and data structures (e.g. range trees, eps-nets, cuttings, partition trees) have been proposed for range searching that have had a profound impact on the two fields, much beyond range searching. The first half of the talk reviews recent theoretical results on range searching, discusses a few variants of range searching that have emerged in the last few years, and sketches some of the approaches that are being used in practice. The second half focuses on an on-going interdisciplinary project focused on discerning subtle qualities of claims based on some underlying data, e.g., is a claim ``cherry-picking''? We propose a Query Response Surface (QRS) based framework that models claims based on structured data as parametrized queries. A claim is mapped to a point on the QRS, and often it is a singularity on QRS. A key insight is that we can learn much about a claim by analyzing the singularity. This framework allows us to formulate and tackle a variety of journalistic tasks as computational problems, such as reverse-engineering vague claims, countering questionable claims, and finding high-quality leads from data.