61 Search Results for "Janowicz, Krzysztof"

Volume

LIPIcs, Volume 208

11th International Conference on Geographic Information Science (GIScience 2021) - Part II

GIScience 2021, September 27-30, 2021, Poznań, Poland (Virtual Conference)

Editors: Krzysztof Janowicz and Judith A. Verstegen

Volume

LIPIcs, Volume 177

11th International Conference on Geographic Information Science (GIScience 2021) - Part I

GIScience 2021, September 27-30, 2021, Poznań, Poland

Editors: Krzysztof Janowicz and Judith A. Verstegen

Document
Research
DOI: 10.4230/TGDK.4.1.4
Native Provenance Computation for Federated and Non-Federated SPARQL Queries

Authors: Zubaria Asma, Daniel Hernández, Luis Galárraga, Giorgos Flouris, Irini Fundulaki, and Katja Hose

Published in: TGDK, Volume 4, Issue 1 (2026). Transactions on Graph Data and Knowledge, Volume 4, Issue 1

Abstract
The popularity of knowledge graphs (KGs) owes credit to their flexible data model, which is suitable for data integration from multiple sources. Several KG-based applications, such as trust assessment, view maintenance, or data valuation on dynamic data, rely on the ability to compute provenance explanations for query results. This need becomes more urgent in federated query processing systems, which allow the online consumption of heterogeneous and decentralized Web data. However, the problem of computing and interacting with provenance has received little attention, especially in the federated setting. On those grounds, this paper introduces the NPCS (Native Provenance Computation for SPARQL) approach, and its federated variant Fed-NPCS, that compute provenance for SPARQL query results. Both approaches build upon spm-semirings to annotate the results of monotonic and non-monotonic SPARQL queries with their provenance. Due to their reliance on query rewriting techniques, the approaches are directly applicable to already deployed SPARQL engines and federations using different reification schemes, including RDF-star. Our experimental evaluation shows that our novel query rewriting approach brings significant run-time improvements w.r.t. the state-of-the-art across both centralized and federated settings. In centralized settings, our tests on two popular SPARQL engines (GraphDB and Stardog) reveal substantial runtime gains over existing query rewriting solutions, enabling scalability to RDF graphs with billions of triples. In federated settings, our experiments on the FedShop benchmark with GraphDB show the viability of Fed-NPCS for federations with up to 200 sources.
Cite as

Zubaria Asma, Daniel Hernández, Luis Galárraga, Giorgos Flouris, Irini Fundulaki, and Katja Hose. Native Provenance Computation for Federated and Non-Federated SPARQL Queries. In Transactions on Graph Data and Knowledge (TGDK), Volume 4, Issue 1, pp. 4:1-4:43, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Article{asma_et_al:TGDK.4.1.4,
  author =	{Asma, Zubaria and Hern\'{a}ndez, Daniel and Gal\'{a}rraga, Luis and Flouris, Giorgos and Fundulaki, Irini and Hose, Katja},
  title =	{{Native Provenance Computation for Federated and Non-Federated SPARQL Queries}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:43},
  ISSN =	{2942-7517},
  year =	{2026},
  volume =	{4},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.4.1.4},
  URN =		{urn:nbn:de:0030-drops-259642},
  doi =		{10.4230/TGDK.4.1.4},
  annote =	{Keywords: native provenance computation, federated SPARQL queries, data provenance, NPCS, Fed-NPCS}
}
Document
Research
DOI: 10.4230/TGDK.4.1.3
Semantically Reflected Programs

Authors: Eduard Kamburjan, Vidar Norstein Klungre, Yuanwei Qu, Rudolf Schlatte, Egor V. Kostylev, Martin Giese, and Einar Broch Johnsen

Published in: TGDK, Volume 4, Issue 1 (2026). Transactions on Graph Data and Knowledge, Volume 4, Issue 1

Abstract
This paper addresses the dichotomy between the formalization of structural and the formalization of executable behavioral knowledge by means of semantically lifted programs, which explore an intuitive connection between imperative programs and knowledge graphs. While knowledge graphs and ontologies are eminently useful to represent formal knowledge about a system’s individuals and universals, programming languages are designed to describe the system’s evolution. To address this dichotomy, we introduce a semantic lifting of the program states of an executing progam into a knowledge graph, for an object-oriented programming language. The resulting graph is exposed as a semantic reflection layer within the programming language, allowing programmers to leverage knowledge of the application domain in their programs during execution. In this paper, we formalize semantic lifting and semantic reflection for a small imperative programming language, SMOL, explain the operational aspects of the language, and consider type correctness and virtualization for runtime program queries through the semantic reflection layer. We illustrate semantic lifting and semantic reflection through a case study of geological modeling and discuss different applications of the technique. The language implementation is open source and available online.
Cite as

Eduard Kamburjan, Vidar Norstein Klungre, Yuanwei Qu, Rudolf Schlatte, Egor V. Kostylev, Martin Giese, and Einar Broch Johnsen. Semantically Reflected Programs. In Transactions on Graph Data and Knowledge (TGDK), Volume 4, Issue 1, pp. 3:1-3:52, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Article{kamburjan_et_al:TGDK.4.1.3,
  author =	{Kamburjan, Eduard and Klungre, Vidar Norstein and Qu, Yuanwei and Schlatte, Rudolf and Kostylev, Egor V. and Giese, Martin and Johnsen, Einar Broch},
  title =	{{Semantically Reflected Programs}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{3:1--3:52},
  ISSN =	{2942-7517},
  year =	{2026},
  volume =	{4},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.4.1.3},
  URN =		{urn:nbn:de:0030-drops-256884},
  doi =		{10.4230/TGDK.4.1.3},
  annote =	{Keywords: Knowledge Graphs, Ontologies, Object-Oriented Modelling, Imperative Programming Languages, Reflection, Type Safety}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.105
Parameterized Algorithms for Computing Pareto Sets

Authors: Joshua Marc Könen, Heiko Röglin, and Tarek Stuck

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
The problem of computing the set of Pareto-optimal solutions has been studied for a variety of multiobjective optimization problems. For many such problems, algorithms are known that compute the Pareto set in (weak) output-polynomial time. These algorithms are often based on dynamic programming and by weak output-polynomial time, we mean that the running time depends polynomially on the size of the Pareto set but also on the sizes of the Pareto sets of the subproblems that occur in the dynamic program. For some problems, like the multiobjective minimum spanning tree problem, such algorithms are not known to exist and for other problems, like multiobjective versions of many NP-hard problems, such algorithms cannot exist, unless 𝒫 = 𝒩𝒫. Dynamic programming over tree decompositions is a common technique in parameterized algorithms. In this paper, we study whether this technique can also be applied to compute Pareto sets of multiobjective optimization problems. We first derive an algorithm to compute the Pareto set for the multicriteria s-t cut problem and show how this result can be applied to a polygon aggregation problem arising in cartography that has recently been introduced by Rottmann et al. (GIScience 2021). We also show how to apply these techniques to also compute the Pareto set of the multiobjective minimum spanning tree problem and for the multiobjective TSP. The running time of our algorithms is O(f(w)⋅poly(n,p_{max})), where f is some function in the treewidth w, n is the input size, and p_{max} is an upper bound on the size of the Pareto sets of the subproblems that occur in the dynamic program. Finally, we present an experimental evaluation of computing Pareto sets on real-world instances of polygon aggregation problems. For this matter we devised a task-specific data structure that allows for efficient storage and modification of large sets of Pareto-optimal solutions. Throughout the implementation process, we incorporated several improved strategies and heuristics that significantly reduced both runtime and memory usage, enabling us to solve instances with treewidth of up to 22 within reasonable amount of time. Moreover, we conducted a preprocessing study to compare different tree decompositions in terms of their estimated overall runtime.
Cite as

Joshua Marc Könen, Heiko Röglin, and Tarek Stuck. Parameterized Algorithms for Computing Pareto Sets. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 105:1-105:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{konen_et_al:LIPIcs.ESA.2025.105,
  author =	{K\"{o}nen, Joshua Marc and R\"{o}glin, Heiko and Stuck, Tarek},
  title =	{{Parameterized Algorithms for Computing Pareto Sets}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{105:1--105:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.105},
  URN =		{urn:nbn:de:0030-drops-245749},
  doi =		{10.4230/LIPIcs.ESA.2025.105},
  annote =	{Keywords: parameterized algorithms, treewidth, multicriteria optimization problems, multicriteria MST, multicriteria TSP, polygon aggregation}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.16
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
DOI: 10.4230/LIPIcs.GIScience.2025.17
The Inherent Structure of Experiments as a Constraint to Spatial Analysis and Modeling

Authors: Simon Scheider and Judith A. Verstegen

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

Abstract
We argue that in order to justify a modeling approach for a particular purpose, we need to better understand the experimental structure that is supposed to be represented by a given model application. For this purpose, we introduce a logic for specifying causal as well as spatio-temporal experiments, based on which we reinterpret Sinton’s structure of spatial information from a pragmatic, experimental viewpoint. We illustrate the use of this logic based on a landuse modeling example, showing to what extent remote sensing and simulation approaches can be justified by decomposing the example into experiments required for answering its main question.
Cite as

Simon Scheider and Judith A. Verstegen. The Inherent Structure of Experiments as a Constraint to Spatial Analysis and Modeling. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 17:1-17:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{scheider_et_al:LIPIcs.GIScience.2025.17,
  author =	{Scheider, Simon and Verstegen, Judith A.},
  title =	{{The Inherent Structure of Experiments as a Constraint to Spatial Analysis and Modeling}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{17:1--17:17},
  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.2025.17},
  URN =		{urn:nbn:de:0030-drops-238468},
  doi =		{10.4230/LIPIcs.GIScience.2025.17},
  annote =	{Keywords: pragmatic Logic, experimental Norms, spatio-temporal Models}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.4
Precomputed Topological Relations for Integrated Geospatial Analysis Across Knowledge Graphs

Authors: Katrina Schweikert, David K. Kedrowski, Shirly Stephen, and Torsten Hahmann

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

Abstract
Geospatial Knowledge Graphs (GeoKGs) represent a significant advancement in the integration of AI-driven geographic information, facilitating interoperable and semantically rich geospatial analytics across various domains. This paper explores the use of topologically enriched GeoKGs, built on an explicit representation of S2 Geometry alongside precomputed topological relations, for constructing efficient geospatial analysis workflows within and across knowledge graphs (KGs). Using the SAWGraph knowledge graph as a case study focused on enviromental contamination by PFAS, we demonstrate how this framework supports fundamental GIS operations - such as spatial filtering, proximity analysis, overlay operations and network analysis - in a GeoKG setting while allowing for the easy linking of these operations with one another and with semantic filters. This enables the efficient execution of complex geospatial analyses as semantically-explicit queries and enhances the usability of geospatial data across graphs. Additionally, the framework eliminates the need for explicit support for GeoSPARQL’s topological operations in the utilized graph databases and better integrates spatial knowledge into the overall semantic inference process supported by RDFS and OWL ontologies.
Cite as

Katrina Schweikert, David K. Kedrowski, Shirly Stephen, and Torsten Hahmann. Precomputed Topological Relations for Integrated Geospatial Analysis Across Knowledge Graphs. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 4:1-4:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{schweikert_et_al:LIPIcs.GIScience.2025.4,
  author =	{Schweikert, Katrina and Kedrowski, David K. and Stephen, Shirly and Hahmann, Torsten},
  title =	{{Precomputed Topological Relations for Integrated Geospatial Analysis Across Knowledge Graphs}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{4:1--4:22},
  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.2025.4},
  URN =		{urn:nbn:de:0030-drops-238332},
  doi =		{10.4230/LIPIcs.GIScience.2025.4},
  annote =	{Keywords: knowledge graph, GeoKG, spatial analysis, ontology, SPARQL, GeoSPARQL, discrete global grid system, S2 geometry, GeoAI, PFAS}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.5
Analysis of Points of Interests Recommended for Leisure Walk Descriptions

Authors: Ehsan Hamzei, Thi Minh Hoai Bui, Martin Tomko, and Stephan Winter

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

Abstract
Leisure walking is a physical activity where locomotion through a natural or even urban environment is the goal in itself, e.g., in pursuit of health and wellbeing. In contrast to destination-oriented walks that are focused on navigation efficiency (i.e., shortest or simplest walk from source to destination), leisure walks emphasize experiencing the environment, engaging in activities, and discovering places that may be off route, or intermediate destinations en-route, summarily called points of interest (POIs). POIs are key for recommending leisure walks, yet a detailed analysis of POIs in the context of leisure walking is missing in the literature. This study extracts and annotates POIs of leisure walking recommendations available in WalkingMaps.com.au, creating an annotated dataset to address this research gap and provide a first analysis of leisure walking descriptions. We classify POIs using the verbal description provided in the dataset, match them with data available in OpenStreetMap (OSM), and compare the POIs with nearby alternatives in OSM. Our analysis reveals thematic and spatial patterns in POI selection, offering a machine learning approach to model POI choices for leisure walks. We further evaluate the availability of rich data in OSM for future automated leisure walking recommendation. This study contributes to automated systems for recommending leisure walks, tailoring suggestions based on available information in the spatial open data, and presents an annotated dataset to facilitate future research in this field.
Cite as

Ehsan Hamzei, Thi Minh Hoai Bui, Martin Tomko, and Stephan Winter. Analysis of Points of Interests Recommended for Leisure Walk Descriptions. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 5:1-5:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{hamzei_et_al:LIPIcs.GIScience.2025.5,
  author =	{Hamzei, Ehsan and Bui, Thi Minh Hoai and Tomko, Martin and Winter, Stephan},
  title =	{{Analysis of Points of Interests Recommended for Leisure Walk Descriptions}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{5:1--5:16},
  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.2025.5},
  URN =		{urn:nbn:de:0030-drops-238341},
  doi =		{10.4230/LIPIcs.GIScience.2025.5},
  annote =	{Keywords: leisure walks, points of interest, places, platial information}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.3
Enriching Location Representation with Detailed Semantic Information

Authors: Junyuan Liu, Xinglei Wang, and Tao Cheng

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

Abstract
Spatial representations that capture both structural and semantic characteristics of urban environments are essential for urban modeling. Traditional spatial embeddings often prioritize spatial proximity while underutilizing fine-grained contextual information from places. To address this limitation, we introduce CaLLiPer+, an extension of the CaLLiPer model that systematically integrates Point-of-Interest (POI) names alongside categorical labels within a multimodal contrastive learning framework. We evaluate its effectiveness on two downstream tasks - land use classification and socioeconomic status distribution mapping - demonstrating consistent performance gains of 4% to 11% over baseline methods. Additionally, we show that incorporating POI names enhances location retrieval, enabling models to capture complex urban concepts with greater precision. Ablation studies further reveal the complementary role of POI names and the advantages of leveraging pretrained text encoders for spatial representations. Overall, our findings highlight the potential of integrating fine-grained semantic attributes and multimodal learning techniques to advance the development of urban foundation models.
Cite as

Junyuan Liu, Xinglei Wang, and Tao Cheng. Enriching Location Representation with Detailed Semantic Information. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 3:1-3:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{liu_et_al:LIPIcs.GIScience.2025.3,
  author =	{Liu, Junyuan and Wang, Xinglei and Cheng, Tao},
  title =	{{Enriching Location Representation with Detailed Semantic Information}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{3:1--3:15},
  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.2025.3},
  URN =		{urn:nbn:de:0030-drops-238322},
  doi =		{10.4230/LIPIcs.GIScience.2025.3},
  annote =	{Keywords: Location Embedding, Contrastive Learning, Pretrained Model}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.8
BERT4Traj: Transformer-Based Trajectory Reconstruction for Sparse Mobility Data

Authors: Hao Yang, Angela Yao, Christopher C. Whalen, and Gengchen Mai

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

Abstract
Understanding human mobility is essential for applications in public health, transportation, and urban planning. However, mobility data often suffers from sparsity due to limitations in data collection methods, such as infrequent GPS sampling or call detail record (CDR) data that only capture locations during communication events. To address this challenge, we propose BERT4Traj, a transformer-based model that reconstructs complete mobility trajectories by predicting hidden visits in sparse movement sequences. Inspired by BERT’s masked language modeling objective and self-attention mechanisms, BERT4Traj leverages spatial embeddings, temporal embeddings, and contextual background features such as demographics and anchor points. We evaluate BERT4Traj on real-world CDR and GPS datasets collected in Kampala, Uganda, demonstrating that our approach significantly outperforms traditional models such as Markov Chains, KNN, RNNs, and LSTMs. Our results show that BERT4Traj effectively reconstructs detailed and continuous mobility trajectories, enhancing insights into human movement patterns.
Cite as

Hao Yang, Angela Yao, Christopher C. Whalen, and Gengchen Mai. BERT4Traj: Transformer-Based Trajectory Reconstruction for Sparse Mobility Data. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 8:1-8:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{yang_et_al:LIPIcs.GIScience.2025.8,
  author =	{Yang, Hao and Yao, Angela and Whalen, Christopher C. and Mai, Gengchen},
  title =	{{BERT4Traj: Transformer-Based Trajectory Reconstruction for Sparse Mobility Data}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{8:1--8:9},
  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.2025.8},
  URN =		{urn:nbn:de:0030-drops-238373},
  doi =		{10.4230/LIPIcs.GIScience.2025.8},
  annote =	{Keywords: Human Mobility, Trajectory Reconstruction, Deep Learning, CDR, GPS}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.13
Assessing Map Reproducibility with Visual Question-Answering: An Empirical Evaluation

Authors: Eftychia Koukouraki, Auriol Degbelo, and Christian Kray

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

Abstract
Reproducibility is a key principle of the modern scientific method. Maps, as an important means of communicating scientific results in GIScience and across disciplines, should be reproducible. Currently, map reproducibility assessment is done manually, which makes the assessment process tedious and time-consuming, ultimately limiting its efficiency. Hence, this work explores the extent to which Visual Question-Answering (VQA) can be used to automate some tasks relevant to map reproducibility assessment. We selected five state-of-the-art vision language models (VLMs) and followed a three-step approach to evaluate their ability to discriminate between maps and other images, interpret map content, and compare two map images using VQA. Our results show that current VLMs already possess map-reading capabilities and demonstrate understanding of spatial concepts, such as cardinal directions, geographic scope, and legend interpretation. Our paper demonstrates the potential of using VQA to support reproducibility assessment and highlights the outstanding issues that need to be addressed to achieve accurate, trustworthy map descriptions, thereby reducing the time and effort required by human evaluators.
Cite as

Eftychia Koukouraki, Auriol Degbelo, and Christian Kray. Assessing Map Reproducibility with Visual Question-Answering: An Empirical Evaluation. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 13:1-13:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{koukouraki_et_al:LIPIcs.GIScience.2025.13,
  author =	{Koukouraki, Eftychia and Degbelo, Auriol and Kray, Christian},
  title =	{{Assessing Map Reproducibility with Visual Question-Answering: An Empirical Evaluation}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{13:1--13:12},
  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.2025.13},
  URN =		{urn:nbn:de:0030-drops-238426},
  doi =		{10.4230/LIPIcs.GIScience.2025.13},
  annote =	{Keywords: map comparison, computational reproducibility, visual question answering, large language models, GeoAI}
}
Document
Research
DOI: 10.4230/TGDK.3.1.4
CoaKG: A Contextualized Knowledge Graph Approach for Exploratory Search and Decision Making

Authors: Veronica dos Santos, Daniel Schwabe, Altigran Soares da Silva, and Sérgio Lifschitz

Published in: TGDK, Volume 3, Issue 1 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 1

Abstract
In decision-making scenarios, an information need arises due to a knowledge gap when a decision-maker needs more knowledge to make a decision. Users may take the initiative to acquire knowledge to fill this gap through exploratory search approaches using Knowledge Graphs (KGs) as information sources, but their queries can be incomplete, inaccurate, and ambiguous. Although KGs have great potential for exploratory search, they are incomplete by nature. Besides, for both Crowd-sourced KGs and KGs constructed by integrating several different information sources of varying quality to be effectively consumed, there is a need for a Trust Layer. Our research aims to enrich and allow querying KGs to support context-aware exploration in decision-making scenarios. We propose a layered architecture for Context Augmented Knowledge Graphs-based Decision Support Systems with a Knowledge Layer that operates under a Dual Open World Assumption (DOWA). Under DOWA, the evaluation of the truthfulness of the information obtained from KGs depends on the context of its claims and the tasks carried out or intended (purpose). The Knowledge Layer comprises a Context Augmented KG (CoaKG) and a CoaKG Query Engine. The CoaKG contains contextual mappings to identify explicit context and rules to infer implicit context. The CoaKG Query Engine is designed as a query-answering approach that retrieves all contextualized answers from the CoaKG. A Proof of Concept (PoC) based on Wikidata was developed to evaluate the effectiveness of the Knowledge Layer.
Cite as

Veronica dos Santos, Daniel Schwabe, Altigran Soares da Silva, and Sérgio Lifschitz. CoaKG: A Contextualized Knowledge Graph Approach for Exploratory Search and Decision Making. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 1, pp. 4:1-4:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{dossantos_et_al:TGDK.3.1.4,
  author =	{dos Santos, Veronica and Schwabe, Daniel and da Silva, Altigran Soares and Lifschitz, S\'{e}rgio},
  title =	{{CoaKG: A Contextualized Knowledge Graph Approach for Exploratory Search and Decision Making}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:27},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.1.4},
  URN =		{urn:nbn:de:0030-drops-236685},
  doi =		{10.4230/TGDK.3.1.4},
  annote =	{Keywords: Knowledge Graphs, Context Search, Decision Support}
}
Document
Resource Paper
DOI: 10.4230/TGDK.2.2.5
The Reasonable Ontology Templates Framework

Authors: Martin Georg Skjæveland and Leif Harald Karlsen

Published in: TGDK, Volume 2, Issue 2 (2024): Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 2, Issue 2

Abstract
Reasonable Ontology Templates (OTTR) is a templating language for representing and instantiating patterns. It is based on simple and generic, but powerful, mechanisms such as recursive macro expansion, term substitution and type systems, and is designed particularly for building and maintaining RDF knowledge graphs and OWL ontologies. In this resource paper, we present the formal specifications that define the OTTR framework. This includes the fundamentals of the OTTR language and the adaptions to make it fit with standard semantic web languages, and two serialization formats developed for semantic web practitioners. We also present the OTTR framework’s support for documenting, publishing and managing template libraries, and for tools for practical bulk instantiation of templates from tabular data and queryable data sources. The functionality of the OTTR framework is available for use through Lutra, an open-source reference implementation, and other independent implementations. We report on the use and impact of OTTR by presenting selected industrial use cases. Finally, we reflect on some design considerations of the language and framework and present ideas for future work.
Cite as

Martin Georg Skjæveland and Leif Harald Karlsen. The Reasonable Ontology Templates Framework. In Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 2, pp. 5:1-5:54, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{skjaeveland_et_al:TGDK.2.2.5,
  author =	{Skj{\ae}veland, Martin Georg and Karlsen, Leif Harald},
  title =	{{The Reasonable Ontology Templates Framework}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{5:1--5:54},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.2.5},
  URN =		{urn:nbn:de:0030-drops-225896},
  doi =		{10.4230/TGDK.2.2.5},
  annote =	{Keywords: Ontology engineering, Ontology design patterns, Template mechanism, Macros}
}
Document
DOI: 10.4230/LIPIcs.COSIT.2024.9
Probing the Information Theoretical Roots of Spatial Dependence Measures

Authors: Zhangyu Wang, Krzysztof Janowicz, Gengchen Mai, and Ivan Majic

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
Intuitively, there is a relation between measures of spatial dependence and information theoretical measures of entropy. For instance, we can provide an intuition of why spatial data is special by stating that, on average, spatial data samples contain less than expected information. Similarly, spatial data, e.g., remotely sensed imagery, that is easy to compress is also likely to show significant spatial autocorrelation. Formulating our (highly specific) core concepts of spatial information theory in the widely used language of information theory opens new perspectives on their differences and similarities and also fosters cross-disciplinary collaboration, e.g., with the broader AI/ML communities. Interestingly, however, this intuitive relation is challenging to formalize and generalize, leading prior work to rely mostly on experimental results, e.g., for describing landscape patterns. In this work, we will explore the information theoretical roots of spatial autocorrelation, more specifically Moran’s I, through the lens of self-information (also known as surprisal) and provide both formal proofs and experiments.
Cite as

Zhangyu Wang, Krzysztof Janowicz, Gengchen Mai, and Ivan Majic. Probing the Information Theoretical Roots of Spatial Dependence Measures. In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 9:1-9:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{wang_et_al:LIPIcs.COSIT.2024.9,
  author =	{Wang, Zhangyu and Janowicz, Krzysztof and Mai, Gengchen and Majic, Ivan},
  title =	{{Probing the Information Theoretical Roots of Spatial Dependence Measures}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{9:1--9:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.9},
  URN =		{urn:nbn:de:0030-drops-208247},
  doi =		{10.4230/LIPIcs.COSIT.2024.9},
  annote =	{Keywords: Spatial Autocorrelation, Moran’s I, Information Theory, Surprisal, Self-Information}
}
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