4 Search Results for "Wang, Shaowen"

Document
DOI: 10.4230/OASIcs.SpaceCHI.2025.23
(Can't) Fly Me to the Moon or Mars? Context of Use Analysis Approaches for Space Exploration

Authors: Tilo Mentler

Published in: OASIcs, Volume 130, Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)

Abstract
Contexts of use are a central concept of research and development in human-computer interaction (HCI). Their in-depth understanding is a key for usable and acceptable computer-aided solutions and a particular challenge in connection with space exploration. It is necessary to examine which of the established approaches can be implemented here and where methodological adjustments are necessary. This article provides a systematic consideration of three perspectives to understand space contexts of use: theory and literature, imparted experiential knowledge, and personal experience. Potentials and risks are evaluated. The findings of HCI research in safety-critical contexts and under COVID-19 conditions that can be transferred to space HCI are taken up.
Cite as

Tilo Mentler. (Can't) Fly Me to the Moon or Mars? Context of Use Analysis Approaches for Space Exploration. In Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025). Open Access Series in Informatics (OASIcs), Volume 130, pp. 23:1-23:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{mentler:OASIcs.SpaceCHI.2025.23,
  author =	{Mentler, Tilo},
  title =	{{(Can't) Fly Me to the Moon or Mars? Context of Use Analysis Approaches for Space Exploration}},
  booktitle =	{Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)},
  pages =	{23:1--23:7},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-384-3},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{130},
  editor =	{Bensch, Leonie and Nilsson, Tommy and Nisser, Martin and Pataranutaporn, Pat and Schmidt, Albrecht and Sumini, Valentina},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SpaceCHI.2025.23},
  URN =		{urn:nbn:de:0030-drops-240135},
  doi =		{10.4230/OASIcs.SpaceCHI.2025.23},
  annote =	{Keywords: Context of Use, Experiential Knowledge, Remote Contextual Inquiry}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.10
Geovicla: Automated Classification of Interactive Web-Based Geovisualizations

Authors: Phil Hüffer, Auriol Degbelo, and Benjamin Risse

Published in: LIPIcs, Volume 346, 13th International Conference on Geographic Information Science (GIScience 2025)

Abstract
The exponential growth of interactive geovisualizations on the Web has underscored the need for automated techniques to enhance their findability. In this paper, we present the Geovicla dataset (2.5K instances), constructed through the harvesting and manual labelling of webpages from a broad range of domains. The webpages are categorized into three groups: "interactive visualisation", "interactive geovisualisation" and "`no interactive visualisation". Using this dataset, we compared three approaches for interactive (geo)visualization classification: (i) a heuristic-based approach (i.e. using manually derived rules), (ii) a feature-engineering approach (i.e. hand-crafted feature vectors combined with machine learning classifiers) and (iii) an embedding-based approach (i.e. automatically generated large language model (LLM) embeddings with machine learning classifiers). The results indicate that LLM embeddings, when used in conjunction with a multilayer perceptron, form a promising combination, achieving up to 74% accuracy for multiclass classification and 75% for binary classification. The dataset and the insights gained from our empirical comparison offer valuable resources for GIScience researchers aiming to enhance the discoverability of interactive geovisualizations.
Cite as

Phil Hüffer, Auriol Degbelo, and Benjamin Risse. Geovicla: Automated Classification of Interactive Web-Based Geovisualizations. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 10:1-10:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{huffer_et_al:LIPIcs.GIScience.2025.10,
  author =	{H\"{u}ffer, Phil and Degbelo, Auriol and Risse, Benjamin},
  title =	{{Geovicla: Automated Classification of Interactive Web-Based Geovisualizations}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{10:1--10:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-378-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{346},
  editor =	{Sila-Nowicka, Katarzyna and Moore, Antoni and O'Sullivan, David and Adams, Benjamin and Gahegan, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2025.10},
  URN =		{urn:nbn:de:0030-drops-238397},
  doi =		{10.4230/LIPIcs.GIScience.2025.10},
  annote =	{Keywords: spatial information search, geovisualization search, findable interactive geovisualization, webpage classification}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.52
Impacts of Catchments Derived from Fine-Grained Mobility Data on Spatial Accessibility (Short Paper)

Authors: Alexander Michels, Jinwoo Park, Bo Li, Jeon-Young Kang, and Shaowen Wang

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
Spatial accessibility is a powerful tool for understanding how access to important services and resources varies across space. While spatial accessibility methods traditionally rely on origin-destination matrices between centroids of administrative zones, recent work has examined creating polygonal catchments - areas within a travel-time threshold - from point-based fine-grained mobility data. In this paper, we investigate the difference between the convex hull and alpha shape algorithms for determining catchment areas and how this affects the results of spatial accessibility analyses. Our analysis shows that the choice of how we define a catchment produces differences in the measured accessibility which correlate with social vulnerability. These findings highlight the importance of evaluating and communicating minor methodological choices in spatial accessibility analyses.
Cite as

Alexander Michels, Jinwoo Park, Bo Li, Jeon-Young Kang, and Shaowen Wang. Impacts of Catchments Derived from Fine-Grained Mobility Data on Spatial Accessibility (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 52:1-52:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{michels_et_al:LIPIcs.GIScience.2023.52,
  author =	{Michels, Alexander and Park, Jinwoo and Li, Bo and Kang, Jeon-Young and Wang, Shaowen},
  title =	{{Impacts of Catchments Derived from Fine-Grained Mobility Data on Spatial Accessibility}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{52:1--52:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.52},
  URN =		{urn:nbn:de:0030-drops-189470},
  doi =		{10.4230/LIPIcs.GIScience.2023.52},
  annote =	{Keywords: Spatial accessibility, alpha shape, convex hull, cyberGIS, social vulnerability}
}
Document
DOI: 10.4230/LIPIcs.GISCIENCE.2018.6
Outlier Detection and Comparison of Origin-Destination Flows Using Data Depth

Authors: Myeong-Hun Jeong, Junjun Yin, and Shaowen Wang

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)

Abstract
Advances in location-aware technology have resulted in massive trajectory data. Origin-destination (OD) trajectories provide rich information on urban flow and transport demand. This study describes a new method for detecting OD flows outliers and conducting hypothesis testing between two OD flow datasets in terms of the variations of spatial extent, that is, spread. The proposed method is based on data depth, which measures the centrality and outlyingness of a point with respect to a given dataset in R^d. Based on the center-outward ordering property, the proposed method analyzes the underlying characteristics of OD flows, such as location, outlyingness, and spread. The ability of the method to detect OD anomalies is compared with that of the Mahalanobis distance approach, and an F-test is used to verify the difference in scale. Empirical evaluation has demonstrated that our method effectively identifies OD flows outliers in an interactive way. Furthermore, the method can provide new perspectives such as spatial extent by considering the overall structure of data when comparing two different OD flows in terms of scale.
Cite as

Myeong-Hun Jeong, Junjun Yin, and Shaowen Wang. Outlier Detection and Comparison of Origin-Destination Flows Using Data Depth. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 6:1-6:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{jeong_et_al:LIPIcs.GISCIENCE.2018.6,
  author =	{Jeong, Myeong-Hun and Yin, Junjun and Wang, Shaowen},
  title =	{{Outlier Detection and Comparison of Origin-Destination Flows Using Data Depth}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{6:1--6:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.6},
  URN =		{urn:nbn:de:0030-drops-93341},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.6},
  annote =	{Keywords: Movement Analysis, Trajectory Data Mining, Data Depth, Outlier Detection}
}
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