Katja Hose
Univ.Prof.in Dr.-Ing.in Dipl.-Inf.in
Research Focus
- Information Systems Engineering: 30%
- Logic and Computation: 70%
Research Areas
- Information and Knowledge Engineering, Ontologies, Data Engineering, Web data extraction and integration, Information Integration, Knowledge Management, Semantic Web, Data Quality, Distributed database systems, Data Warehousing, Data Integration, Linked Data, Open Data, Knowledge-Based Systems, Web-based Databases, Knowledge Graphs, Knowledge Graph Management Systems, Data Management, Artificial Intelligence, Data Extraction and Integration, Big Data, Database Systems, Databases, Scalable Systems
About
My current research is rooted in data management and knowledge engineering and and spans theory, algorithms, and applications of Data Science including graph databases, knowledge graphs, querying, analytics, and machine learning.
In the past couple of years, I have gained extensive experience in interdisciplinary data science in collaborations with colleagues from bioscience, medicine, and environmental assessment.
Roles
-
Full Professor
Databases and Artificial Intelligence, E192-02 -
Curriculum Coordinator
Master / Area / Data Management -
Faculty Council
Principal Member -
Curriculum Commission for Informatics
Substitute Member
Courses
2024W
- Bachelor Thesis / 184.691 / PR
- Business Intelligence / 188.429 / VU
- Doctoral & Master Students Seminar / 181.223 / SE
- Introduction to Semantic Systems / 188.399 / VU
- Project in Computer Science 1 / 192.021 / PR
- Project in Computer Science 2 / 192.022 / PR
- Scientific Research and Writing / 193.052 / SE
- Seminar for Master Students in Software Engineering & Internet Computing / 180.777 / SE
- Seminar in Theoretical Computer Science / 192.064 / SE
Projects
-
Health virtual twins for the personalised management of stroke related to atrial fibrillation
2024 – 2028 / European Commission
Publications: 205805 / 205430 / 205728
Publications
2024
-
AIDE: Antithetical, Intent-based, and Diverse Example-Based Explanations
/
Nematov, I., Sacharidis, D., Sagi, T., & Hose, K. (2024). AIDE: Antithetical, Intent-based, and Diverse Example-Based Explanations. arXiv. https://doi.org/10.34726/8224
Download: AIDE: Antithetical, Intent-based, and Diverse Example-Based Explanations (4.02 MB) -
Data-driven PC-chair-in-the-loop Formation of Program Committees: An EDBT 2023 Experience
/
Saha Bhowmick, S., & Hose, K. (2024). Data-driven PC-chair-in-the-loop Formation of Program Committees: An EDBT 2023 Experience. SIGMOD RECORD, 53(2), 68–74. https://doi.org/10.1145/3685980.3685998
Project: TARGET (2024–2028) -
Semantic Web: Past, Present, and Future
/
Scherp, A., Groener, G., Skoda, P., Hose, K., & Vidal, M.-E. (2024). Semantic Web: Past, Present, and Future. Transactions on Graph Data and Knowledge, 2(1), 3:1-3:37. https://doi.org/10.4230/TGDK.2.1.3
Download: Semantic Web: Past, Present, and Future (1.52 MB)
Project: TARGET (2024–2028) -
Nanomotif: Identification and Exploitation of DNA Methylation Motifs in Metagenomes using Oxford Nanopore Sequencing
/
Heidelbach, S., Mølvang Dall, S., Bøjer, J. S., Nissen, J., van der Maas, L. N. L., Sereika, M., Kirkegaard, R. H., Jensen, S. I., Kousgaard, S. J., Thorlacius-Ussing, O., Hose, K., Nielsen, T. D., & Albertsen, M. (2024). Nanomotif: Identification and Exploitation of DNA Methylation Motifs in Metagenomes using Oxford Nanopore Sequencing. bioRxiv. https://doi.org/10.34726/8211
Download: Nanomotif: Identification and Exploitation of DNA Methylation Motifs in Metagenomes using Oxford Nanopore Sequencing (10.9 MB)
Project: TARGET (2024–2028) -
Utilizing Phonetic Similarity for Cross-source and Cross-language Toponym Matching - a Benchmark and Prototype
/
Sagi, T., Zaga, M., Rusinek, S., Fekete, M. R., Bjerva, J., & Hose, K. (2024). Utilizing Phonetic Similarity for Cross-source and Cross-language Toponym Matching - a Benchmark and Prototype. Research Square (United States). https://doi.org/10.34726/7539
Download: Utilizing Phonetic Similarity for Cross-source and Cross-language Toponym Matching - a Benchmark and Prototype (505 KB)
Project: TARGET (2024–2028) -
Mining Validating Shapes for Large Knowledge Graphs via Dynamic Reservoir Sampling
/
Lissandrini, M., Rabbani, K., & Hose, K. (2024). Mining Validating Shapes for Large Knowledge Graphs via Dynamic Reservoir Sampling. In M. Atzori, P. CIACCIA, M. Ceci, F. Mandreoli, D. Malerba, & M. SANGUINETTI (Eds.), Proceedings of the 32nd Symposium on Advanced Database Systems (SEBD 2024) (pp. 25–34). https://doi.org/10.34726/8213
Download: Mining Validating Shapes for Large Knowledge Graphs via Dynamic Reservoir Sampling (1.52 MB)
Project: TARGET (2024–2028) -
Integrating Multi-Modal Spatial Data using Knowledge Graphs – a Case Study of Microflora Danica
/
Corfixen, M., Heede, T., Sagi, T., Albertsen, M., Nielsen, T. D., & Hose, K. (2024). Integrating Multi-Modal Spatial Data using Knowledge Graphs – a Case Study of Microflora Danica. In A. Hasnain, A. C. Morales Tirado, M. Dumontier, & D. Rebholz-Schuhmann (Eds.), Proceedings of the 7th Workshop on Semantic Web solutions for large-scale biomedical data analytics co-located with The ESWC 2024: Extended Semantic Web Conference (ESWC 2024). https://doi.org/10.34726/8099
Download: Integrating Multi-Modal Spatial Data using Knowledge Graphs – a Case Study of Microflora Danica (3.19 MB)
Project: TARGET (2024–2028) -
Hypergraphs with Attention on Reviews for Explainable Recommendation
/
Jendal, T. E., Le, T.-H., Lauw, H. W., Lissandrini, M., Dolog, P., & Hose, K. (2024). Hypergraphs with Attention on Reviews for Explainable Recommendation. In Advances in Information Retrieval (pp. 230–246). Springer, Cham. https://doi.org/10.1007/978-3-031-56027-9_14
Project: TARGET (2024–2028) -
KGLiDS: A Platform for Semantic Abstraction, Linking, and Automation of Data Science
/
Helali, M., Monjazeb, N., Vashisth, S., Carrier, P., Helal, A., Cavalcante, A., Ammar, K., Hose, K., & Mansour, E. (2024). KGLiDS: A Platform for Semantic Abstraction, Linking, and Automation of Data Science. In 2024 IEEE 40th International Conference on Data Engineering (ICDE) (pp. 179–192). IEEE. https://doi.org/10.1109/ICDE60146.2024.00021
Project: TARGET (2024–2028) -
moduli: A Disaggregated Data Management Architecture for Data-Intensive Workflows
/
Ceravolo, P., Catarci, T., Console, M., Cudre-Mauroux, P., Groppe, S., Hose, K., Pokorný, J., Romero, O., & Wrembel, R. (2024). moduli: A Disaggregated Data Management Architecture for Data-Intensive Workflows. ACM SIGWEB Newsletter : The Newsletter of ACM’s Special Interest Group on Hypertext and Hypermedia, 2024(Winter), 1–16. https://doi.org/10.1145/3643603.3643607
Project: TARGET (2024–2028)
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
- 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
- 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
-
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) - 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
- 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
-
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) -
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) -
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)
2018
- Advances in Database Technology — EDBT 2018 / Böhlen, M., Pichler, R., May, N., Rahm, E., Wu, S.-H., & Hose, K. (Eds.). (2018). Advances in Database Technology — EDBT 2018. EDBT 2018. https://doi.org/10.5441/002/edbt.2018.01
Supervisions
-
SHACL Shapes Extraction for Evolving Knowledge Graphs
/
Pürmayr, E. (2025). SHACL Shapes Extraction for Evolving Knowledge Graphs [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2025.120502
Download: PDF (2.24 MB)
Awards
-
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
And more…
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 .