An Ontology-based approach to Knowledge-assisted Integration and Visualization of Urban Mobility Data

Sobral, Thiago; Dias, Teresa Galvão; Borges, José

doi:10.1016/j.eswa.2020.113260

Cited by 30 publications

(10 citation statements)

References 19 publications

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“…Specifically, the knowledge can be standard procedures [21] and linguistic rules [48] collected from domain literature, relationships between samples [16,51,74] specified by users, constraints distilled from expert experiences [46], numeric features calculated based on pre-collected samples [72,73], etc. Besides, many recent works attempt to utilize knowledge involved in off-the-shelf digital resources, such as ontology [41,59], corpus [82], knowledge graphs [8,37], pre-trained models (e.g., knowledge distillation) [75], etc. There have been literature reviews on techniques for integrating human knowledge into machine learning models [17,71], and many of them are also applicable in visualization.…”

Section: Knowledge-assisted Visual Analyticsmentioning

confidence: 99%

Incorporation of Human Knowledge Into Data Embeddings to Improve Pattern Significance and Interpretability

Zhou

2022

IEEE Trans. Visual. Comput. Graphics

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2 a1 b1 c1 b2 a2 c1 c2 Fig. 1. The visualization system interface that consists of three components: (a) Knowledge Editor (KE), (b) Data Projector (DP), and (c) Pattern Explainer (PE). The analyst is analyzing the Covid-19 dataset [2] that consists of 173 sequences, each recording the number of monthly-confirmed cases (per million people) from May 2020 to April 2021 of a country. The analyst creates six country groups (see colored tree nodes) according to their knowledge using (a) and incorporates the class information into the embeddings of countries to generate the projection with clear and class-consistent visual structures that foreshadow underlying data patterns. (b2)The embedding projection without knowledge where does not exist visual structure.

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Section: Knowledge-assisted Visual Analyticsmentioning

confidence: 99%

Incorporation of Human Knowledge Into Data Embeddings to Improve Pattern Significance and Interpretability

Zhou

2022

IEEE Trans. Visual. Comput. Graphics

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“…To improve the quality of noisy and ambiguous data of OSM caused by its simple and open semantic structure, [22] proposes an OSM Semantic Network to compute semantic similarity through co-citation measures, providing a novel semantic tool for OSM and GIS communities. The exploitation of semantic meaning to facilitate content navigation is often assisted by an ontology, as in [23], whose support is beneficial in the specialisation of concepts within each context, such as in the CH domain described in [24]. This is also managed in MAGIS, where a meta-ontology is built to generally define the key concepts of the framework, and a topic-specific ontology is designed to structure the specific contents of a defined knowledge domain.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Ontologies for Multimedia Maps

2022

BSEWM-22, BSABE-22, SDAMN-22 &Amp; BMESH-22 Dec. 5-7, 2022 Barcelona (Spain)

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The paper illustrates a web-based framework linking geographic elements with geo and temporal-referenced multimedia contents. Among the key features, -multimedia content integration, time management and self-adaptivity to different application contexts are the most relevant ones. A hybrid approach to classify stored contents combines a Machine Learning (ML) technique for text classification with the intervention of human experts. A dynamically configured ontology-based navigation is proposed based on the adaptivity of the tool to dynamic classification of contents. Adaptive navigation is supported by a general world and by a domain-specific ontology. The approach is presented in a framework and prototype named Multimedia Adaptive Geographic Information System (MAGIS), an extension to Geographic Information Systems (GIS) devised as a common foundation to be adapted to different domainspecific implementations. A demonstration of the web-based MAGIS prototype is provided for Cultural Heritage (CH) events.

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“…These systems are often motivated by open data initiatives requiring city agencies to make their data publicly available through open data portals [12,11,63,27,4], which played a central role in helping experts to gain a deeper understanding of cities, evaluate policies, and plan developments [71]. Examples of such systems include ones designed to explore human mobility [2,22,3,61], public policy [13], air pollution [15,29], urban traffic [28], public transportation [57,69], real-estate ownership [32], land use labelling [62], urban change [46], and shadow impact on public spaces [45].…”

Section: Related Workmentioning

confidence: 99%

A Visual Analytics System for Profiling Urban Land Use Evolution

Santos¹,

Hosseini²,

Rulff³

et al. 2021

Preprint

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The growth of cities calls for regulations on how urban space is used and zoning resolutions define how and for what purpose each piece of land is going to be used. Tracking land use and zoning evolution can reveal a wealth of information about urban development. For that matter, cities have been releasing data sets describing the historical evolution of both the shape and the attributes of land units. The complex nature of zoning code and land-use data, however, makes the analysis of such data quite challenging and often time-consuming. We address these challenges by introducing URBAN CHRONICLES, an open-source web-based visual analytics system that enables interactive exploration of changes in land use patterns. Using New York City's Primary Land Use Tax Lot Output (PLUTO) as an example, we show the capabilities of the system by exploring the data over several years at different scales. URBAN CHRONICLES supports onthe-fly aggregation and filtering operations by using a tree-based data structure that leverages the hierarchical nature of the data set to index the shape and attributes of geographical regions that change over time. We demonstrate the utility of our system through a set of case studies that analyze the impact of Hurricane Sandy on land use attributes, as well as the effects of proposed rezoning plans in Downtown Brooklyn.

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An Ontology-based approach to Knowledge-assisted Integration and Visualization of Urban Mobility Data

Cited by 30 publications

References 19 publications

Incorporation of Human Knowledge Into Data Embeddings to Improve Pattern Significance and Interpretability

Incorporation of Human Knowledge Into Data Embeddings to Improve Pattern Significance and Interpretability

Adaptive Ontologies for Multimedia Maps

A Visual Analytics System for Profiling Urban Land Use Evolution

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