2 Search Results for "Claramunt, Christophe"


Document
What, When, and Where Do You Mean? Detecting Spatio-Temporal Concept Drift in Scientific Texts

Authors: Meilin Shi, Krzysztof Janowicz, Zilong Liu, Mina Karimi, Ivan Majic, and Alexandra Fortacz

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


Abstract
Inundated by the rapidly expanding AI research nowadays, the research community requires more effective research data management than ever. A key challenge lies in the evolving nature of concepts embedded in the growing body of research publications. As concepts evolve over time (e.g., keywords like global warming become more commonly referred to as climate change), past research may become harder to find and interpret in a modern context. This phenomenon, known as concept drift, affects how research topics and keywords are understood, categorized, and retrieved. Beyond temporal drift, such variations also occur across geographic space, reflecting differences in local policies, research priorities, and so forth. In this work, we introduce the notion of spatio-temporal concept drift to capture how concepts in scientific texts evolve across both space and time. Using a scientometric dataset in geographic information science, we detect how research keywords drifted across countries and years using word embeddings. By detecting spatio-temporal concept drift, we can better align archival research and bridge regional differences, ensuring scientific knowledge remains findable and interoperable within evolving research landscapes.

Cite as

Meilin Shi, Krzysztof Janowicz, Zilong Liu, Mina Karimi, Ivan Majic, and Alexandra Fortacz. What, When, and Where Do You Mean? Detecting Spatio-Temporal Concept Drift in Scientific Texts. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 16:1-16:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{shi_et_al:LIPIcs.GIScience.2025.16,
  author =	{Shi, Meilin and Janowicz, Krzysztof and Liu, Zilong and Karimi, Mina and Majic, Ivan and Fortacz, Alexandra},
  title =	{{What, When, and Where Do You Mean? Detecting Spatio-Temporal Concept Drift in Scientific Texts}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{16:1--16:18},
  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.2025.16},
  URN =		{urn:nbn:de:0030-drops-238450},
  doi =		{10.4230/LIPIcs.GIScience.2025.16},
  annote =	{Keywords: Concept Drift, Ontology, Large Language Models, Research Data Management}
}
Document
Towards a Multidimensional Interaction Framework for Promoting Public Engagement in Citizen Science Projects

Authors: Maryam Lotfian, Jens Ingensand, and Christophe Claramunt

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


Abstract
Citizen science (CS) projects are expanding into various fields and the number of CS applications is expanding. Despite this growth, engaging the public and sustaining their participation remains a challenge. Some studies have proposed that interacting with participants is an effective way to sustain their participation. This paper introduces a framework that outlines complementary levels of interaction including basic, incentivized, user-centered and action-oriented interactions. The interaction levels range from basic acknowledgments to instructions for taking action. The integration of these interactions within the spatial, temporal, and thematic dimensions is also discussed. The proposed framework is applied to a biodiversity CS project that involves different types of real-time feedback to participants based on the location, time, and image of the species observations. Location-based feedback is based on the species distribution models, and provides information on the probability of observing a certain species in a given location, as well as suggestions on the species to be observed in the participant’s vicinity. Overall, the multi-dimensional interaction framework provides CS practitioners with insights into the various ways they can maintain communication with participants, whether through real-time machine-generated interactions or interactions between the project team and participants.

Cite as

Maryam Lotfian, Jens Ingensand, and Christophe Claramunt. Towards a Multidimensional Interaction Framework for Promoting Public Engagement in Citizen Science Projects. In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 8:1-8:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


Copy BibTex To Clipboard

@InProceedings{lotfian_et_al:LIPIcs.GIScience.2023.8,
  author =	{Lotfian, Maryam and Ingensand, Jens and Claramunt, Christophe},
  title =	{{Towards a Multidimensional Interaction Framework for Promoting Public Engagement in Citizen Science Projects}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{8:1--8:16},
  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.2023.8},
  URN =		{urn:nbn:de:0030-drops-189030},
  doi =		{10.4230/LIPIcs.GIScience.2023.8},
  annote =	{Keywords: Citizen Science, Multidimensional Interaction, Participation, User-centered Feedback, Machine Learning, Biodiversity}
}
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