SFB 1313 Publication "Optimizing Grid Layouts for Level-of-Detail Exploration of Large Data Collections"

New SFB 1313 Publication, published in Computer Graphics Forum (Wiley Online Library). The work has been developed within the SFB 1313 research project D01.

SFB 1313 Publication "Optimizing Grid Layouts for Level-of-Detail Exploration of Large Data Collections"

Author

• Steffen Frey (University of Groningen, The Netherlands, SFB 1313 research project D01)

Abstract

This paper introduces an optimization approach for generating grid layouts from large data collections such that they are amenable to level-of-detail presentation and exploration. Classic (flat) grid layouts visually do not scale to large collections, yielding overwhelming numbers of tiny member representations. The proposed local search-based progressive optimization scheme generates hierarchical grids: leaves correspond to one grid cell and represent one member, while inner nodes cover a quadratic range of cells and convey an aggregate of contained members. The scheme is solely based on pairwise distances and jointly optimizes for homogeneity within inner nodes and across grid neighbors. The generated grids allow to present and flexibly explore the whole data collection with arbitrary local granularity. Diverse use cases featuring large data collections exemplify the application: stock market predictions from a Black-Scholes model, channel structures in soil from Markov chain Monte Carlo, and image collections with feature vectors from neural network classification models. The paper presents feedback by a domain scientist, compares against previous approaches, and demonstrates visual and computational scalability to a million members, surpassing classic grid layout techniques by orders of magnitude.