Nöllenburg and Terziadis – COMPUTING DATA-DRIVEN MULTILINEAR METRO MAPS 2023

Description

This recent and academically robust publication, “Computing Data-driven Multilinear Metro Maps,” comes from Martin Nöllenburg and Soeren Terziadis of TU Wien, specializing in algorithms and complexity. Published in the prestigious and peer-reviewed *The Cartographic Journal* (2023, Vol. 60, No. 4, pp. 367-382), its explicit “Refereed Paper” status ensures high trustworthiness. Spanning 16 pages, the open-access article is richly illustrated with six figures, including examples of orientation systems, data clustering, and real-world metro map layouts, enhancing understanding of its complex algorithmic approach to schematic map design. Supported by significant funding from the Vienna Science and Technology Fund and the European Union, this research offers a valuable, data-driven perspective on generating flexible multilinear metro maps, a key topic in cartography and visualization, underpinned by a comprehensive bibliography.