A Pattern for Features on a Hierarchical Spatial Grid

Cogan Shimizu; Rui Zhu; Gengchen Mai; Colby Fisher; Ling Cai; Mark Schildhauer; Krzysztof Janowicz; Pascal Hitzler; Lu Zhou; Shirly Stephen

doi:10.1145/3502223.3502236

A Pattern for Features on a Hierarchical Spatial Grid

Cogan Shimizu, Rui Zhu, Gengchen Mai, Colby Fisher, Ling Cai, Mark Schildhauer, Krzysztof Janowicz, Pascal Hitzler, Lu Zhou, Shirly Stephen

School of Geographical Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

8 Citations (Scopus)

Abstract

The integration of data along a common spatial component remains an obstacle in many problem spaces. One promising method for integrating data in such a way is through the use of a common, underlying spatial reference system, such as a Discrete Global Grid (e.g., the S2 Grid System), and pre-computing spatial relations between features and the constituent components at a spatial resolution appropriate for the data and use case. That is, by emphasizing the notion of the cell, we can examine what is in a cell, predict contents of its parent and child cells, and quickly get an overview of spatially co-located features and regions of interest without having to directly compute spatial interactions. This paper provides an ontology design pattern, to be used as a structural template, for modeling how features or regions map onto a hierarchical grid system and addresses how the attributes of these features may be inherited upwards or downwards through the hierarchy. We furthermore provide a motivating example and implementation.

Original language	English
Title of host publication	Proceedings of the 10th International Joint Conference on Knowledge Graphs, IJCKG 2021
Publisher	Association for Computing Machinery
Pages	108-114
Number of pages	7
ISBN (Electronic)	9781450395656
DOIs	https://doi.org/10.1145/3502223.3502236
Publication status	Published - 6 Dec 2021
Event	10th International Joint Conference on Knowledge Graphs, IJCKG 2021 - Virtual, Online, Thailand Duration: 6 Dec 2021 → 8 Dec 2021

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	10th International Joint Conference on Knowledge Graphs, IJCKG 2021
Country/Territory	Thailand
City	Virtual, Online
Period	6/12/21 → 8/12/21

Bibliographical note

Funding Information:
There is plenty of adjacent work to be accomplished with both this pattern and the surrounding paradigm. In particular, we wish to (1) define a SHACL11 shape for the pattern, to be used in validating the data mapped using this pattern; (2) incorporate temporality, as it may not be the case that a feature always is spatially related to a Cell; (3) incorporate the notion of an Event, which will greatly improve its applicability and usefulness, as well as immediately incorporate how persons may interact with the DGG; and, finally, (4) connect this pattern to the Causal Events Pattern [23], so as to enrich the relationship between where something may occur and how it affects that place, using the DGG as a medium. (5) provide a human-centered evaluation of the robustness of the pat-tern, as the pattern is currently used in prototype applications, the evaluation itself is still ongoing. Acknowledgements. The authors acknowledge support by the National Science Foundation under Grant 2033521 A1: KnowWhereGraph: Enriching and Linking Cross-Domain Knowledge Graphs using Spatially-Explicit AI Technologies. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Publisher Copyright:
© 2021 Owner/Author.

Keywords

geoinformation science
ontology design pattern
ontology engineering

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10.1145/3502223.3502236

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Cite this

Shimizu, C., Zhu, R., Mai, G., Fisher, C., Cai, L., Schildhauer, M., Janowicz, K., Hitzler, P., Zhou, L., & Stephen, S. (2021). A Pattern for Features on a Hierarchical Spatial Grid. In Proceedings of the 10th International Joint Conference on Knowledge Graphs, IJCKG 2021 (pp. 108-114). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3502223.3502236

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note = "Funding Information: There is plenty of adjacent work to be accomplished with both this pattern and the surrounding paradigm. In particular, we wish to (1) define a SHACL11 shape for the pattern, to be used in validating the data mapped using this pattern; (2) incorporate temporality, as it may not be the case that a feature always is spatially related to a Cell; (3) incorporate the notion of an Event, which will greatly improve its applicability and usefulness, as well as immediately incorporate how persons may interact with the DGG; and, finally, (4) connect this pattern to the Causal Events Pattern [23], so as to enrich the relationship between where something may occur and how it affects that place, using the DGG as a medium. (5) provide a human-centered evaluation of the robustness of the pat-tern, as the pattern is currently used in prototype applications, the evaluation itself is still ongoing. Acknowledgements. The authors acknowledge support by the National Science Foundation under Grant 2033521 A1: KnowWhereGraph: Enriching and Linking Cross-Domain Knowledge Graphs using Spatially-Explicit AI Technologies. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Publisher Copyright: {\textcopyright} 2021 Owner/Author.; 10th International Joint Conference on Knowledge Graphs, IJCKG 2021 ; Conference date: 06-12-2021 Through 08-12-2021",

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Shimizu, C, Zhu, R, Mai, G, Fisher, C, Cai, L, Schildhauer, M, Janowicz, K, Hitzler, P, Zhou, L & Stephen, S 2021, A Pattern for Features on a Hierarchical Spatial Grid. in Proceedings of the 10th International Joint Conference on Knowledge Graphs, IJCKG 2021. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 108-114, 10th International Joint Conference on Knowledge Graphs, IJCKG 2021, Virtual, Online, Thailand, 6/12/21. https://doi.org/10.1145/3502223.3502236

A Pattern for Features on a Hierarchical Spatial Grid. / Shimizu, Cogan; Zhu, Rui; Mai, Gengchen et al.
Proceedings of the 10th International Joint Conference on Knowledge Graphs, IJCKG 2021. Association for Computing Machinery, 2021. p. 108-114 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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AU - Zhu, Rui

AU - Mai, Gengchen

AU - Fisher, Colby

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AU - Schildhauer, Mark

AU - Janowicz, Krzysztof

AU - Hitzler, Pascal

AU - Zhou, Lu

AU - Stephen, Shirly

N1 - Funding Information: There is plenty of adjacent work to be accomplished with both this pattern and the surrounding paradigm. In particular, we wish to (1) define a SHACL11 shape for the pattern, to be used in validating the data mapped using this pattern; (2) incorporate temporality, as it may not be the case that a feature always is spatially related to a Cell; (3) incorporate the notion of an Event, which will greatly improve its applicability and usefulness, as well as immediately incorporate how persons may interact with the DGG; and, finally, (4) connect this pattern to the Causal Events Pattern [23], so as to enrich the relationship between where something may occur and how it affects that place, using the DGG as a medium. (5) provide a human-centered evaluation of the robustness of the pat-tern, as the pattern is currently used in prototype applications, the evaluation itself is still ongoing. Acknowledgements. The authors acknowledge support by the National Science Foundation under Grant 2033521 A1: KnowWhereGraph: Enriching and Linking Cross-Domain Knowledge Graphs using Spatially-Explicit AI Technologies. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Publisher Copyright: © 2021 Owner/Author.

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A Pattern for Features on a Hierarchical Spatial Grid

Abstract

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Bibliographical note

Keywords

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