Abstract
The core ambitions of map generalisation remain the same-as do a set of inter connected research activities concerned with algorithm developments, user requirements modelling, evaluation methodologies, and the handling and integration of multi scale, global datasets. Technology continues to afford new paradigms of data capture and use, in turn requiring generalisation techniques that are capable of working with a wider variety of data sources (including user generated content), and web friendly mapping services that conceal the complexities of the map design process from the lay user. This summarative chapter highlights yet again, the truly inter disciplinary nature of map generalisation research.
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Note that the users of generalisation are the mapmakers, not to be confused with the users of the map (even if in some cases both roles are undertaken by the same person).
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Acknowledgments
The authors are grateful to their colleagues from the COGIT Laboratory of IGN, the Dresden University of Technology and the University of Edinburgh for the discussions around the future research challenges in generalisation that indubitably made this chapter all the richer!
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Burghardt, D., Duchêne, C., Mackaness, W. (2014). Conclusion: Major Achievements and Research Challenges in Generalisation. In: Burghardt, D., Duchêne, C., Mackaness, W. (eds) Abstracting Geographic Information in a Data Rich World. Lecture Notes in Geoinformation and Cartography(). Springer, Cham. https://doi.org/10.1007/978-3-319-00203-3_12
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