Logisch und Physikalisch Optimierte Semantic Web Datenbank-Engine (LUPOSDATE)
Funded by:
- DFG
Runtime:
- 2007 - 2011
Project Coordinator:
Research Associate:
Motivation
The vision of the Semantic Web compared to conventional database management systems and web applications is to incorporate the meaning of the symbol into the machine processing of symbols so that error rates from incorrectly mapped data and services can be reduced when data and services are automatically integrated . There are currently significant efforts in the World Wide Web Consortium (W3C), in industry and in research, to further develop the Semantic Web, both in terms of the specifications of essential formats and languages as well as the underlying technologies and products.
Goals and Procedure
Semantic Web applications often still have major performance problems because logical and physical optimizations for Semantic Web data and queries have not yet been sufficiently researched and applied in productive systems. Furthermore, the concept of ontology in connection with database technologies has not yet been sufficiently researched.
Innovation and Prospects
The aim of this project is to research logical and physical optimizations for Semantic Web data and languages with regard to the concrete specifics of Semantic Web data and languages, so that the performance of Semantic Web applications is improved. In particular, the concept of ontology and its implications for the optimized evaluation of Semantic Web queries will be examined in more detail.
Project Partners
- Institute of Information Systems (IFIS), University of Lübeck
Link to Project Details
Publications
2025
A scientometric analysis of reviews on the Internet of Things, The Journal of Supercomputing , vol. 81, no. 6, Apr. 2025. Springer Science and Business Media LLC.
| File: | s11227-025-07230-w |
Impact of Chatbots on User Experience and Data Quality on Citizen Science Platforms, Computers , vol. 14, no. 1, Jan. 2025.
| File: | computers14010021 |
Ai-supported analysis and classification of digitized botanical collections, in 11th International Conference on Machine Learning, Optimization, and Data Science (LOD), Tuscany, Italy , 2025.
Automated Archival Descriptions with Federated Intelligence of LLMs, in The 36th International Conference on Database and Expert Systems Applications (DEXA), Bangkok, Thailand , 2025.
| File: | 978-3-032-02049-9_4 |
EcoRAG: A Multi-hop Economic QA Benchmark for Retrieval Augmented Generation Using Knowledge Graphs, in Natural Language Processing and Information Systems (NLDB), Kanazawa, Japan , 2025. pp. 163–173.
| File: | 978-3-031-97144-0_15 |
GraphTrace: A Modular Retrieval Framework Combining Knowledge Graphs and Large Language Models for Multi-Hop Question Answering, Computers , vol. 14, no. 9, 2025. MDPI AG.
| File: | computers14090382 |
Opportunities and Challenges for Data Quality in the Era of Quantum Computing, arXiv , vol. 2512.00870, 2025.
| File: | arxiv.2512.00870 |
OptiMA: A Transaction-Based Framework with Throughput Optimization for Very Complex Multi-Agent Systems, arXiv , vol. 2511.03761, 2025.
| File: | arxiv.2511.03761 |
Proceedings of the International Health Informatics Conference: IHIC 2023., .... Springer Nature Singapore, 2025.
| DOI: | 10.1007/978-981-97-7190-5 |
| ISBN: | 9789819771905 |
| File: | 978-981-97-7190-5 |
"QC4DB: Beschleunigung von relationalen Datenbankmanagementsystemen durch Quantenrechner Teilvorhaben: Datenbank Optimierungen (DBOpt)" Hannover : Technische Informationsbibliothek, 2025.
| File: | 24530 |
QCardEst/QCardCorr: Quantum Cardinality Estimation and Correction, arXiv , vol. 2509.08817, 2025.
| File: | ARXIV.2509.08817 |
Quantum-Enhanced Transaction Scheduling with Reduced Complexity via Solving QUBO Iteratively using a Locking Mechanism, in 2nd International Workshop on Quantum Computing and Quantum-Inspired Technology for Data-Intensive Systems and Applications (Q-Data), Berlin, Germany , 2025.
| File: | 3736393.3736701 |
Utilizing Quantum Computing to Improve the Quality of Data, in The 29th European Conference on Advances in Databases and Information Systems (ADBIS), Tampere, Finland , 2025.
| File: | 978-3-032-05281-0_19 |
Weather forecasting using quantum-based LSTM: A comparative analysis, Results in Engineering , vol. 28, 2025. Elsevier BV.
| File: | j.rineng.2025.107995 |
2024
On the Potential of Sustainable Software Solutions in Smart Manufacturing Environments, in Semantic Intelligence , Springer Nature Singapore, Dec.2024, pp. 25–32.
| DOI: | 10.1007/978-981-97-7356-5_3 |
| File: | 978-981-97-7356-5_3 |
Are Large Language Models the New Interface for Data Pipelines?, in Proceedings of the International Workshop on Big Data in Emergent Distributed Environments, Santiago, Chile , Association for Computing Machinery, 2024.
| File: | 3663741.3664785 |
Research Trends for the Interplay between Large Language Models and Knowledge Graphs, in VLDB 2024 Workshop: The International Workshop on Data Management Opportunities in Unifying Large Language Models + Knowledge Graphs (LLM+KG), Guangzhou, China , 2024.
| File: |
Applied Machine Learning and Data Analytics: 6th International Conference, AMLDA 2023, Lübeck, Germany, November 9–10, 2023, Revised Selected Papers., .... Springer Nature Switzerland, 2024.
| ISBN: | 9783031554865 |
| File: | 978-3-031-55486-5 |
Workshop Summary of the Second International Workshop on Quantum Data Science and Management (QDSM), in VLDB 2024 Workshop: The Second International Workshop on Quantum Data Science and Management (QDSM’24) , 2024.
| File: |
Video Shot-boundary detection: Issues, challenges and solutions, Artificial Intelligence Review , vol. 57, no. 4, 2024.
| File: | s10462-024-10742-1 |
Towards Generating High-Quality Knowledge Graphs by Leveraging Large Language Models, in The 29th Annual International Conference on Natural Language \& Information Systems (NLDB 2024), Turin, Italy , 2024.
| File: | 978-3-031-70239-6_31 |
There Are Infinite Ways to Formulate Code: How to Mitigate the Resulting Problems for Better Software Vulnerability Detection, Information , vol. 15, no. 4, 2024.
| File: | info15040216 |
The Way Forward with AI-Complete Problems, New Generation Computing , 2024.
| File: | s00354-024-00251-8 |
Assessing the Impact of Government Policies on Covid-19 Spread: A Machine Learning Approach, in 10th International Conference on Machine Learning, Optimization, and Data Science (LOD), Tuscany, Italy , 2024.
Semantic Intelligence, Sarika Jain and Sven Groppe and Bharat K. Bhargava, Eds. Springer Nature Singapore, 2024, pp. 25–32.
| DOI: | 10.1007/978-981-97-7356-5_3 |
| ISBN: | 9789819773565 |
| File: | 978-981-97-7356-5_3 |
| Bibtex: | @book{SemanticIntelligence2023,
title = {Semantic Intelligence},
editor = {Sarika Jain and Sven Groppe and Bharat K. Bhargava},
year = {2023},
publisher = {Springer Nature Singapore},
url = {https://doi.org/10.1007/978-981-19-7126-6}
} |

