Searching OSM Planet with Context-Aware Spatial Relations

Bahrdt, Daniel; Funke, Stefan; Gelhausen, Rick; Storandt, Sabine

doi:10.1145/3139958.3140000

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…Negative co-occurrence patterns can be equally informative (e.g., benches are never located in open water). Several studies have applied methods from KDD such as association rule mining to discover spatial relationships within large databases (Bahrdt, Funke, Gelhausen, & Storandt, 2017). In the context of OSM, such co-occurrence rules may be used within data quality assessment by identifying logical inconsistencies (Mocnik et al, 2018) and have already been applied within tag recommendation systems (Kashian, Rajabifard, Richter, & Chen, 2019;Vandecasteele & Devillers, 2015).…”

Section: Introductionmentioning

confidence: 99%

Regional variations of context‐based association rules in OpenStreetMap

Ludwig

Fendrich²,

Zipf

2020

Transactions in GIS

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As a user-generated map of the whole world, OpenStreetMap (OSM) provides valuable information about the natural and built environment. However, the spatial heterogeneity of the data due to cultural differences and the spatially varying mapping process makes the extraction of reliable information difficult. This study investigates the variability of association rules extracted from OSM across different geographic regions and depending on different context variables, such as the number of OSM mappers. The focus of this study is the spatial co-occurrence of OSM tags mapped inside of parks within eight different cities. Without considering any context variable, most association rules were very region-specific without any rule being valid across all cities. Limiting the association rule analysis to parks based on specific context variables increased the number of rules which are applicable across multiple cities. Furthermore, additional region-specific association rules emerged. The most important context variables were found to be the number of features mapped inside the park, the number of tags and the park size. These results suggest that the mapping process has a significant influence on the emergence of association rules within user-generated data.Therefore, this subject needs further investigation to enable effective usage of OSM data across different cultural realms.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Introductionmentioning

confidence: 99%

Regional variations of context‐based association rules in OpenStreetMap

Ludwig

Fendrich²,

Zipf

2020

Transactions in GIS

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“…As we use OSM as a geographical database, we provide a natural language interface that can be used to query OSM without using any API or ontology directly. As a query engine, we use oscar [31]. Since oscar enables us to query for key-value pairs like amenity=theatre restricted to local surroundings, we trigger a query whenever either the name or type of an entity and its spatial containment are known, i.e., given as relational expressions (e.g., William street in/of Melbourne or st. Catherine at the entrance).…”

Section: Queryingmentioning

confidence: 99%

“…After extracting the information using spatio-ontological reasoning, this thesis's last task focuses on composing the queries and scheduling them for mapping the entities.The chapter tends to focus on the final two components of the processing pipeline described in section 7 of chapter 2.The primary objective is to create queries and algorithms that might strengthen the geo-referencing processes. The queries will be in the form of constraints and based on the type and the name extracted in previous chapters.As a query engine we use oscar 2 [31], [30]. oscar is a new geospatial search engine based on freely available OSM-data.…”

Section: Motivation and Goalsmentioning

confidence: 99%

Representing and Reasoning with Context-Sensitive Vague Place Descriptions

Yousaf¹

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This doctoral thesis aims to design a geographic information system based on locations to make the information about the human location interpretable for computers. This research employs natural language place descriptions as its primary research input and focuses on five research components as main goals towards understanding place descriptions: incorporating context-sensitive information, spatial information extraction, and modeling, reasoning, place geo-referencing, and querying.

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A reasoning model for geo-referencing named and unnamed spatial entities in natural language place descriptions

Yousaf

Wolter

2021

Spatial Cognition & Computation

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Searching OSM Planet with Context-Aware Spatial Relations

Cited by 4 publications

References 8 publications

Regional variations of context‐based association rules in OpenStreetMap

Regional variations of context‐based association rules in OpenStreetMap

Representing and Reasoning with Context-Sensitive Vague Place Descriptions

A reasoning model for geo-referencing named and unnamed spatial entities in natural language place descriptions

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