Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views: Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017)

Lucas Godfrey; William Mackaness

doi:10.1007/978-3-319-63946-8_13

Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views: Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017)

Lucas Godfrey, William Mackaness

School of Geosciences

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract / Description of output

We present work from an on-going project to develop techniques of automated cartography. We introduce Artificial Cognitive Maps as an approach to integrating insights from spatial cognition with geographic data. The ultimate goal is to drive highly contextual map views that more effectively support navigation tasks such as travelling across large, complex cities. With a focus on our now ubiquitous small screen mobile devices, we propose that distortions on the traditional metric cartographic representation may support a reduction in cognitive load for the user, but that the logic and parameters of these distortions should be founded on the natural distortions present in our cognitive representations of geographic objects and their relation.

Original language	English
Title of host publication	Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views
Publisher	Springer
Pages	57-62
ISBN (Print)	978-3-319-63945-1
DOIs	https://doi.org/10.1007/978-3-319-63946-8_13
Publication status	Published - 16 Sept 2017

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10.1007/978-3-319-63946-8_13

https://link.springer.com/chapter/10.1007/978-3-319-63946-8_13

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Godfrey, L., & Mackaness, W. (2017). Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views: Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017) . In Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views (pp. 57-62). Springer. https://doi.org/10.1007/978-3-319-63946-8_13

Godfrey, Lucas ; Mackaness, William. / Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views : Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017) . Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views . Springer, 2017. pp. 57-62

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abstract = "We present work from an on-going project to develop techniques of automated cartography. We introduce Artificial Cognitive Maps as an approach to integrating insights from spatial cognition with geographic data. The ultimate goal is to drive highly contextual map views that more effectively support navigation tasks such as travelling across large, complex cities. With a focus on our now ubiquitous small screen mobile devices, we propose that distortions on the traditional metric cartographic representation may support a reduction in cognitive load for the user, but that the logic and parameters of these distortions should be founded on the natural distortions present in our cognitive representations of geographic objects and their relation.",

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Godfrey, L & Mackaness, W 2017, Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views: Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017) . in Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views . Springer, pp. 57-62. https://doi.org/10.1007/978-3-319-63946-8_13

Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views: Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017) . / Godfrey, Lucas; Mackaness, William.
Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views . Springer, 2017. p. 57-62.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

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Godfrey L, Mackaness W. Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views: Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017) . In Artificial Cognitive Maps: Selecting Heterogeneous Sets of Geographic Objects and Relations to Drive Highly Contextual Task-Oriented Map Views . Springer. 2017. p. 57-62 doi: 10.1007/978-3-319-63946-8_13