Empirical approach to advance the generalisation of multi-scale maps

This dataset is described in the article Empirical approach to advance the generalisation of multi-scale maps; summarized below:  Since the advent of the web revolution, maps have undergone profound changes in their usage and design. Pan-scalar map design, in particular, emphasises interaction, enabling users to navigate diverse representations seamlessly across different scales.This study addresses gaps in understanding pan-scalar map specificity. Through empirical experimentation, a multi-scale map exemplar is constructed, focusing on map generalisation quality to reduce disorientation and facilitate information retrieval during exploration. Utilising a combination of generalisation strategies, including automatic and semi-automatic processes, this map serves as a foundational step in formalising new rules of map generalisation in a pan-scalar mapping context. Then, we initiate discussions on the lessons learnt from this exemplar construction. In particular, we discuss what constitutes good generalisation for pan-scalar maps and outline potential approaches for achieving it.  It is composed of four folder : All_Data contains all the data before generalisation.  MS_Hydro contains the shapefile of generalised hydrographic element for each zoom level. MS_Road contains the shapefile of generalised urban road elements for each zoom level. Styles contains the style file to apply to create our map.