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Katja Hose

Univ.Prof. Dr.-Ing.

Research Areas

  • Ontologies, Information Integration, Semantic Web, Linked Data, Open Data, Knowledge Graphs, Data Management, Data Extraction and Integration, Big Data, Databases, Information and Knowledge Engineering, Query Optimization, Data Engineering, Graph Data Management, Knowledge Management, Property Graphs, Data Quality, Distributed database systems, Data Analytics, Data Warehousing, Data Integration, Knowledge-Based Systems, Web-based Databases, Knowledge Graph Management Systems, Artificial Intelligence, Database Systems, Scalable Systems
Katja Hose

About

Katja Hose joined TU Wien as Full Professor in 2023, after more than ten years at Aalborg University, Denmark, where she held positions as Assistant Professor, Associate Professor, and Full Professor. She obtained her Ph.D. in Computer Science from Ilmenau University of Technology, Germany, and was a postdoctoral researcher at the Max Planck Institute for Informatics. She is

Katja Hose has served on program committees of more than 100 international conferences, regularly in senior roles such as Program Chair, Track Chair, Senior PC Memberships, and contributes to the field through editorial board memberships at leading journals. She is regularly invited to serve on evaluation panels and advisory boards. Highlights include:

Her recent research interests focus on graph data management and knowledge graphs (query optimization, data integration, quality, analytics, etc.), knowledge-driven AI (agentic AI, LLMs, etc.), and interdisciplinary data science.

Roles

  • Head of Research Unit
    Data Management, E194-07
  • Full Professor
    Data Management, E194-07
  • Faculty Council
    Principal Member
  • Curriculum Commission for Informatics
    Principal Member
  • Curriculum Commission for Business Informatics
    Substitute Member
  • Curriculum Coordinator
    Master / Area / Data Management

Contact

2026W

2027S

 

2026

  • DataKernelBench: Can LLMs Optimize Database Queries on GPUs? / Kumar, G. K., Perlitz, Y., Lammie, C., Giovannini, A., & Hose, K. (2026). DataKernelBench: Can LLMs Optimize Database Queries on GPUs? arXiv. https://doi.org/10.48550/ARXIV.2608.25061
    Project: ARMADA (2025–2029)
  • Computing Why-Provenance for Property Graph Queries / Ganepola, K., Jakubowski, M., & Hose, K. (2026). Computing Why-Provenance for Property Graph Queries. Proceedings of the VLDB Endowment, 19(11), 3552–3564. https://doi.org/10.14778/3836663.3836708
    Download: PDF (2.49 MB)
    Projects: DeConquer (2023–2027) / KnowledgeGraph (2020–2028)
  • A Community Survey on {SHACL} and ShEx: Briding Gaps in RDF Validation / Jakubowski, M., Tomaszuk, D., & Hose, K. (2026). A Community Survey on {SHACL} and ShEx: Briding Gaps in RDF Validation. arXiv. https://doi.org/10.48550/ARXIV.2606.03502
  • MetriKG: Profiling Static and Evolving Knowledge Graphs / Günes, H. H., Jovanovik, M., & Hose, K. (2026). MetriKG: Profiling Static and Evolving Knowledge Graphs. In H. Hacid & Y. Maarek (Eds.), WWW Companion ’26: Companion Proceedings of the ACM Web Conference 2026 (pp. 200–203). Association for Computing Machinery. https://doi.org/10.1145/3774905.3793136
    Download: PDF (1.35 MB)
    Projects: DORSET (2026–2029) / TARGET (2024–2028)
  • Expressive Querying and Scalable Management of Large RDF Archives / Pelgrin, O., Taelman, R., Galárraga, L., & Hose, K. (2026). Expressive Querying and Scalable Management of Large RDF Archives. Semantic Web, 17(3). https://doi.org/10.1177/22104968261431405
  • Towards LLM-KG Symbiosis for Reducing Factual Hallucinations / Dolci, T., Jovanovik, M., & Hose, K. (2026). Towards LLM-KG Symbiosis for Reducing Factual Hallucinations. In A. Krause & J. F. Pimentel (Eds.), EDBT/ICDT 2026 Workshops : Proceedings of the Workshops of the EDBT/ICDT 2026 Joint Conference co-located with the EDBT/ICDT 2026 Joint Conference. CEUR-WS.org. https://doi.org/10.34726/12041
    Download: PDF (1.02 MB)
    Project: ARMADA (2025–2029)
  • RDFGraphGen: An RDF Graph Generator Based on SHACL Shapes / Jovanovik, M., Vecovska, M., Jakubowski, M., & Hose, K. (2026). RDFGraphGen: An RDF Graph Generator Based on SHACL Shapes. In Knowledge Graphs : 14th International Joint Conference, IJCKG 2025, Heraklion, Crete, Greece, October 15–17, 2025, Proceedings (pp. 111–125). Springer. https://doi.org/10.1007/978-981-95-5009-8_8
    Project: TARGET (2024–2028)
  • Amalgam: Hybrid LLM-PGM Synthesis Algorithm for Accuracy and Realism / Kapenekakis, A., Thomsen, B., Hose, K., & Albano, M. (2026). Amalgam: Hybrid LLM-PGM Synthesis Algorithm for Accuracy and Realism. arXiv. https://doi.org/10.48550/ARXIV.2603.27254
  • Graph-Native Normalization / Schrott, J., Jakubowski, M., & Hose, K. (2026). Graph-Native Normalization. arXiv. https://doi.org/10.48550/arXiv.2603.02995
  • Reducing LLM Hallucinations with Knowledge Graphs: A Survey / Dolci, T., Jovanovik, M., & Hose, K. (2026). Reducing LLM Hallucinations with Knowledge Graphs: A Survey. HAL (open archive). https://doi.org/10.34726/12684
    Download: PDF (4.11 MB)
    Project: ARMADA (2025–2029)
  • Source Attribution in Retrieval-Augmented Generation / Nematov, I., Kalai, T., Kuzmenko, E., Fugagnoli, G., Sacharidis, D., Hose, K., & Sagi, T. (2026). Source Attribution in Retrieval-Augmented Generation. In I. Koprinska, J. Mendes-Moreiram, & P. Branco (Eds.), Machine Learning and Principles and Practice of Knowledge Discovery in Databases : International Workshops of ECML PKDD 2025, Porto, Portugal, September 15–19, 2025, Revised Selected Papers, Part II (pp. 317–332). Springer. https://doi.org/10.1007/978-3-032-19099-4_23
  • Jazero: A Semantic Table Search System / Christensen, M. P., Lissandrini, M., & Hose, K. (2026). Jazero: A Semantic Table Search System. In 2026 IEEE 42nd International Conference on Data Engineering (ICDE) (pp. 4151–4154). IEEE. https://doi.org/10.1109/ICDE65706.2026.00314
  • An End-To-End Re-Evaluation of Table Entity-Linkers / Christensen, M. P., Lissandrini, M., & Hose, K. (2026). An End-To-End Re-Evaluation of Table Entity-Linkers. In 2026 IEEE 42nd International Conference on Data Engineering (ICDE) (pp. 1703–1716). IEEE. https://doi.org/10.1109/ICDE65706.2026.00130
  • How Human-Centric Are Our Graph Data Abstractions? / Bonifati, A., Dimou, A., Dumbrava, S., Fletcher, G., Hose, K., Konstantinidis, G., Labra-Gayo, J. E., Martens, W., Pardal, N., Peterfreund, L., Thornton, K., Vidal, M.-E., & Voigt, H. (2026). How Human-Centric Are Our Graph Data Abstractions? Transactions on Graph Data and Knowledge, 4(2), 2:1-2:31. https://doi.org/10.4230/TGDK.4.2.2
  • Native Provenance Computation for Federated and Non-Federated SPARQL Queries / Asma, Z., Hernández Castillo, D. A., Galárraga, L., Flouris, G., Fundulaki, I., & Hose, K. (2026). Native Provenance Computation for Federated and Non-Federated SPARQL Queries. Transactions on Graph Data and Knowledge, 4(1), 4:1-4:43. https://doi.org/10.4230/TGDK.4.1.4

2025

2024

2023

  • How does knowledge evolve in open knowledge graphs? / Polleres, A., Pernisch, R., Bonifati, A., Dell’Aglio, D., Dobriy, D., Dumbrava, S., Etcheverry, L., Ferranti, N., Hose, K., Jiménez-Ruiz, E., Lissandrini, M., Scherp, A., Tommasini, R., & Wachs, J. (2023). How does knowledge evolve in open knowledge graphs? Transactions on Graph Data and Knowledge, 1(1), 11:1-11:59. https://doi.org/10.4230/TGDK.1.1.11
    Download: PDF (4.16 MB)
  • Optimizing SPARQL queries over decentralized knowledge graphs / Aebeloe, C., Montoya, G., & Hose, K. (2023). Optimizing SPARQL queries over decentralized knowledge graphs. Semantic Web, 14(6), 1121–1165. https://doi.org/10.3233/SW-233438
    Download: PDF (2.07 MB)
  • Tunable Query Optimizer for Web APIs and User Preferences / Zeimetz, T., Hose, K., & Schenkel, R. (2023). Tunable Query Optimizer for Web APIs and User Preferences. In B. Venable, D. Garijoa, & B. Jalaian (Eds.), Proceedings of the 12th Knowledge Capture Conference 2023 (pp. 92–100). Association for Computing Machinery (ACM). https://doi.org/10.1145/3587259.3627542
  • StarBench: Benchmarking RDF-star Triplestores / Abouda, G., Aebeloe, C., Dell’Aglio, D., Keen, A., & Hose, K. (2023). StarBench: Benchmarking RDF-star Triplestores. In M. U. Saleem, A.-C. Ngonga Ngomo, D. Graux, F. Orlandi, E. Niazmand, G. Ydler, & M.-E. Vidal (Eds.), Joint Proceedings of the QuWeDa and MEPDaW 2023: 7th Workshop on Storing, Querying and Benchmarking Knowledge Graphs and 9th Workshop on Managing the Evolution and Preservation of the Data Web (QuWeDa-MEPDaW 2023) (pp. 34–49). CEUR-WS.org. https://doi.org/10.34726/5399
    Download: PDF (1.05 MB)
  • GInRec: A Gated Architecture for Inductive Recommendation using Knowledge Graphs / Jendal, T., Lissandrini, M., Dolog, P., & Hose, K. (2023). GInRec: A Gated Architecture for Inductive Recommendation using Knowledge Graphs. In V. W. Anelli, P. Basile, G. De Melo, F. Donini, A. Ferrara, C. Musto, F. Narducci, A. Ragone, & M. Zanker (Eds.), Proceedings of the Fifth Knowledge-aware and Conversational Recommender Systems Workshop co-located with 17th ACM Conference on Recommender Systems (RecSys 2023) (pp. 80–89). CEUR-WS.org. https://doi.org/10.34726/5395
    Download: PDF (557 KB)
  • GLENDA: Querying RDF Archives with Full SPARQL / Pelgrin, O., Taelman, R., Galárraga, L., & Hose, K. (2023). GLENDA: Querying RDF Archives with Full SPARQL. In The Semantic Web: ESWC 2023 Satellite Events (pp. 75–80). Springer. https://doi.org/10.34726/5411
    Download: PDF (502 KB)
  • Metagenomic Binning using Connectivity-constrained Variational Autoencoders / Lamurias, A., Tibo, A., Hose, K., Albertsen, M., & Nielsen, T. D. (2023). Metagenomic Binning using Connectivity-constrained Variational Autoencoders. In Proceedings of the 40th International Conference on Machine Learning. 40th International Conference on Machine Learning (ICML 2023), Honolulu, United States of America (the).
  • Patient Event Sequences for Predicting Hospitalization Length of Stay / Hansen, E. R., Nielsen, T. D., Mulvad, T., Strausholm, M. N., Sagi, T., & Hose, K. (2023). Patient Event Sequences for Predicting Hospitalization Length of Stay. In J. M. Juarez, M. Marcos, G. Stiglic, & A. Tucker (Eds.), Artificial Intelligence in Medicine : 21st International Conference on Artificial Intelligence in Medicine, AIME 2023, Portorož, Slovenia, June 12–15, 2023, Proceedings (pp. 51–56). Springer. https://doi.org/10.1007/978-3-031-34344-5_7
  • SHACTOR: Improving the Quality of Large-Scale Knowledge Graphs with Validating Shapes / Rabbani, K., Lissandrini, M., & Hose, K. (2023). SHACTOR: Improving the Quality of Large-Scale Knowledge Graphs with Validating Shapes. In Companion of the 2023 International Conference on Management of Data (pp. 151–154). https://doi.org/10.1145/3555041.3589723
  • Recommending tasks based on search queries and missions / Garigliotti, D., Balog, K., Hose, K., & Bjerva, J. (2023). Recommending tasks based on search queries and missions. Natural Language Engineering, 1–25. https://doi.org/10.1017/S1351324923000219
  • Visualizing How-Provenance Explanations for SPARQL Queries / Galárraga, L., Hernández, D., Katim, A., & Hose, K. (2023). Visualizing How-Provenance Explanations for SPARQL Queries. In WWW ’23 Companion: Companion Proceedings of the ACM Web Conference 2023 (pp. 212–216). Association for Computing Machinery. https://doi.org/10.1145/3543873.3587350
  • OntoEval: an Automated Ontology Evaluation System / Antonio Zaitoun, Tomer Sagi, & Katja Hose. (2023). OntoEval: an Automated Ontology Evaluation System. In Y. Ding, J. Tang, & J. Sequeda (Eds.), WWW ’23 Companion: Companion Proceedings of the ACM Web Conference 2023 (pp. 82–85). Association for Computing Machinery. https://doi.org/10.1145/3543873.3587318
  • Automated Ontology Evaluation: Evaluating Coverage and Correctness using a Domain Corpus / Zaitoun, A., Sagi, T., & Hose, K. (2023). Automated Ontology Evaluation: Evaluating Coverage and Correctness using a Domain Corpus. In Y. Ding, J. Tang, & J. Sequeda (Eds.), WWW ’23 Companion: Companion Proceedings of the ACM Web Conference 2023 (pp. 1127–1137). Association for Computing Machinery. https://doi.org/10.1145/3543873.3587617
    Download: PDF (948 KB)
  • Do bridges dream of water pollutants? Towards DreamsKG, a knowledge graph to make digital access for sustainable environmental assessment come true / Garigliotti, D., Bjerva, J., Nielsen, F., Butzbach, A., Lyhne, I., Kørnøv, L., & Hose, K. (2023). Do bridges dream of water pollutants? Towards DreamsKG, a knowledge graph to make digital access for sustainable environmental assessment come true. In Y. Ding, J. Tang, & J. Sequeda (Eds.), WWW ’23 Companion: Companion Proceedings of the ACM Web Conference 2023 (pp. 724–730). ACM. https://doi.org/10.1145/3543873.3587590
  • Scientific Data Extraction from Oceanographic Papers / Veyhe, B. E., Sagi, T., & Hose, K. (2023). Scientific Data Extraction from Oceanographic Papers. In Y. Ding, J. Tang, J. Sequeda, C. Castillo, & G.-J. Houben (Eds.), WWW ’23 Companion: Companion Proceedings of the ACM Web Conference 2023 (pp. 800–804). Association for Computing Machinery. https://doi.org/10.1145/3543873.3587595
  • Joint Proceedings of the ESWC 2023 Workshops and Tutorials co-located with 20th European Semantic Web Conference (ESWC 2023) / Alam, M., Trojahn, C., Hertling, S., Pesquita, C., Aebeloe, C., Aras, H., Azzam, A., Cano, J., Domingue, J., Gottschalk, S., Hartig, O., Hose, K., Kirrane, S., Lisena, P., Osborne, F., Rohde, P. D., Steels, L., Taelman, R., Third, A., … Türker, A. (Eds.). (2023). Joint Proceedings of the ESWC 2023 Workshops and Tutorials co-located with 20th European Semantic Web Conference (ESWC 2023) (Vol. 3443). CEUR-WS.org. http://hdl.handle.net/20.500.12708/216198
  • Environmental impact assessment reports in Wikidata and a Wikibase / Nielsen, F. Å., Lyhne, I., Garigliotti, D., Butzbach, A., Ravn Boess, E., Hose, K., & Kørnøv, L. (2023). Environmental impact assessment reports in Wikidata and a Wikibase. In Joint Proceedings of the ESWC 2023 Workshops and Tutorials co-located with 20th European Semantic Web Conference (ESWC 2023) (pp. 1–8). CEUR-WS.org. https://doi.org/10.34726/5421
    Download: PDF (1.53 MB)
  • Knowledge Engineering in the Era of Artificial Intelligence / Hose, K. (2023). Knowledge Engineering in the Era of Artificial Intelligence. In A. Abelló, P. Vassiliadis, O. Romero, & R. Wrembel (Eds.), Advances in Databases and Information Systems : 27th European Conference, ADBIS 2023, Barcelona, Spain, September 4–7, 2023, Proceedings (pp. 3–15). Springer. https://doi.org/10.1007/978-3-031-42914-9_1
  • The Need for Better RDF Archiving Benchmarks / Pelgrin, O., Taelman, R., Galárraga, L., & Hose, K. (2023). The Need for Better RDF Archiving Benchmarks. In M. Saleem, A.-C. Ngonga Ngomo, D. Graux, F. Orlandi, E. Niazmand, G. Ydler, & M.-E. Vidal (Eds.), Joint Proceedings of the QuWeDa and MEPDaW 2023: 7th Workshop on Storing, Querying and Benchmarking Knowledge Graphs and 9th Workshop on Managing the Evolution and Preservation of the Data Web (QuWeDa-MEPDaW 2023) (pp. 50–54). https://doi.org/10.34726/5398
    Download: Paper (1010 KB)
  • Graph Neural Networks for Metagenomic Binning / Lamurias, A., Tibo, A., Hose, K., Albertsen, M., & Nielsen, T. D. (2023). Graph Neural Networks for Metagenomic Binning. In The 2023 ICML Workshop on Computational Biology. Accepted Submissions. 40th International Conference on Machine Learning (ICML 2023), Honolulu, United States of America (the). ICML compbio workshop. https://doi.org/10.34726/5406
    Download: PDF (441 KB)
  • Extraction of validating shapes from very large knowledge graphs / Rabbani, K., Lissandrini, M., & Hose, K. (2023). Extraction of validating shapes from very large knowledge graphs. Proceedings of the VLDB Endowment, 16(5), 1023–1032. https://doi.org/10.14778/3579075.3579078
    Download: Paper (1.84 MB)

2018

 

  • Distinguished Associate Editor Award
    2026 / VLDB Journal / USA / Website
  • Distinguished Associate Editor Award
    2026 / PVLDB/VLDB 2026 / USA / Website
  • Best Paper Award
    2025 / European Conference on Advances in Databases and Information Systems (ADBIS) 2025 / Finland / Website
  • Distinguished Associate Editor Award
    2025 / PVLDB/VLDB 2025 / UK / Website
  • ACM Senior Membership
    2025 / ACM / USA / Website
  • Distinguished Meta-Reviewer Award
    2025 / EDBT/ICDT 2025 Joint Conference / Spain / Website
  • Manfred Paul Award - Extraction of Validating Shapes from very large Knowledge Graphs (VLDB 2023)
    2024 / International Federation for Information Processing (IFIP) / Germany / Website
  • Best Demo Award - GLENDA: Querying over RDF Archives with SPARQL
    2023 / European Semantic Web Conference (ESWC) 2023 / Greece / Website
  • Best Paper Award - Automated Ontology Evaluation: Evaluating Coverage and Correctness using a Domain Corpus
    2023 / International Workshop on Natural Language Processing for Knowledge Graph Creation (NLP4KGC) 2023 / USA / Website

Soon, this page will include additional information such as reference projects, activities as journal reviewer and editor, memberships in councils and committees, and other research activities.

Until then, please visit Katja Hose’s research profile in TISS .