Data Linking Infrastructure – Foundations and Architecture
Funded by DFG
Runtime: 01.01.2019 - 31.12.2025
Principal Investigator:
- Ralf Möller (Universität Hamburg)
Research Associates:
- Thomas Asselborn, M.Sc. (Universität Hamburg)
- Dr. Marcel Gehrke, M.Sc. (Universität Hamburg)
- Dr. Sylvia Melzer, Dipl.-Ing. (University of Lübeck)
- Simon Schiff, M.Sc. (University of Lübeck)
Project Description
A data linking infrastructure is envisioned to support humanities scholars from all research fields of the Cluster of Excellence "Understanding Written Artefacts” such that various kinds of data can be easily and systematically combined to foster scientific progress. On the one hand, there are images and videos of written artefacts, in some cases associated with text data making parts of image (or video) content explicit, e.g., using optical character recognition techniques. On the other hand, different kinds of chemistry and materials science data are collected to further describe written artefacts under investigation, almost always in combination with descriptive temporal and spatial data. Data of this kind must be made available to humanities scientists such that they are best supported in their scientific work. Publications from humanities projects will refer to artefact data of the kind described above, and, after a while, artefact data are referenced in quite some number of natural language publications resulting from scientific work in humanities projects, e.g., journal articles, conference papers, and PhD theses. Publications are provided as documents, which are represented, e.g., as PDF data. Further natural language data comes from existing humanities research databases. All data can be described in an appropriate way using suitable metadata formalisms (date of creation, author, etc.). In addition, and different from metadata, all kinds of base data (also called raw data) might be extended with derived data, with which certain features are made explicit (e.g., for supporting visualization, for information retrieval, or for other research efforts).
Link to Project Details
https://www.csmc.uni-hamburg.de/research/cluster-projects/field-f/rff01.html
Activities
Editorial
- S. Melzer, J. Gippert, S. Thiemann, H. Peukert: Proceedings of the Workshop on Humanities-Centred Artificial Intelligence (CHAI 2021), CEUR Workshop Proceedings, 2022 (proceedings)
- S. Melzer, S. Thiemann, H. Peukert: Proceedings of the Workshop on Humanities-Centred Artificial Intelligence (CHAI 2022), CEUR Workshop Proceedings, 2022 (proceedings)
- S. Melzer, H. Peukert, S. Thiemann: Proceedings of the Workshop on Humanities-Centred Artificial Intelligence (CHAI 2023), CEUR Workshop Proceedings, 2023 (proceedings)
Organisation
- R. Möller, S. Melzer: Data Linking Study Day 2021, Universität Hamburg, online, 15.06.2021, Organisator
- S. Melzer: 44th German Conference on Artificial Intelligence, September 27-October 1, 2021, Berlin, Germany (KI2021), Junior Research Chair (abstracts)
- S. Melzer, S. Thiemann, J. Gippert: Humanities-Centred Artificial Intelligence (CHAI), 44th German Conference on Artificial Intelligence, September 27-October 1, 2021, Berlin, Germany (KI2021), Workshop Organisator and Chair (proceedings, abstracts)
- S. Melzer, S. Thiemann, H. Peukert: 2nd Workshop on Humanities-Centred Artificial Intelligence (CHAI), 45th German Conference on Artificial Intelligence, September 19-September 23, 2022, Trier, Germany (KI2022), Workshop Organisator
- R. Möller, S. Melzer: Doctoral Symposium, 25th International Symposium on Formal Methods (FM 2023), 06.03.2023, Lübeck, PC member and mentor
- S. Melzer, H. Hu-von Hinüber: Data Linking Workshop 2023: Computer Vision and Natural Language Processing – Challenges in the Humanities, 27.-28. June 2023, Hamburg, Germany, Workshop Organisator and Chair
- S. Melzer, S. Thiemann, H. Peukert: 3rd Workshop on Humanities-Centred Artificial Intelligence (CHAI), 46th German Conference on Artificial Intelligence, September 26, 2023, Berlin, Germany (KI2023), Workshop Organisator
Publications
2020
Combining Holistic and Complementary Document Representations for Information Retrieval, in Proceedings of the 34rd International Florida Artificial Intelligence Research Society Conference (FLAIRS 2021) , North Miami Beach, Florida, USA: {AAAI} Press, 2020.
Bounded-Memory Criteria for Streams with Application Time, in Proceedings of the 33rd International Florida Artificial Intelligence Research Society Conference {(FLAIRS-20)} , North Miami Beach, Florida, USA: {AAAI} Press, 2020. pp. 148--153.
File: | 18421 |
Bibtex: | ![]() @inproceedings{SchOe20a, Author = {Simon Schiff and Özgür Lütfü Özçep}, Booktitle = {Proceedings of the 33rd International Florida Artificial Intelligence Research Society Conference {(FLAIRS-20)}}, Title = {Bounded-Memory Criteria for Streams with Application Time}, Year = {2020} } |
AI-based Companion Services for Humanities, 2020.
AI-based Companion Services for Humanities, in AI methods for digital heritage, Workshop at 43rd German Conference on Artificial Intelligence , 2020.
2019
Efficient Multiple Query Answering in Switched Probabilistic Relational Models, in Proceedings of AI 2019: Advances in Artificial Intelligence (AI 2019) , Springer, Dec.2019. pp. 104--116.
DOI: | https://doi.org/10.1007/978-3-030-35288-2_9 |
ISBN: | 978-3-030-35288-2 |
Bibtex: | ![]() @inproceedings{GehBrMo19f, author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller}, title = {{Efficient Multiple Query Answering in Switched Probabilistic Relational Models}}, Booktitle = {Proceedings of {AI} 2019: Advances in Artificial Intelligence ({AI} 2019)}, series = {Lecture Notes in Computer Science}, volume = {11919}, pages = {104--116}, publisher = {Springer}, year = {2019}, doi = {https://doi.org/10.1007/978-3-030-35288-2_9}, isbn= {978-3-030-35288-2} } |
Approximate Query Answering in Complex Gaussian Mixture Models, in IEEE International Conference on Big Knowledge, (ICBK 2019), Beijing, China, November 10-11, 2019 , IEEE, Nov.2019. pp. 81--86.
File: | ICBK.2019.00019 |
Bibtex: | ![]() @inproceedings{HarGeMo19, title={{Approximate Query Answering in Complex Gaussian Mixture Models}}, author = {Mattis Hartwig and Marcel Gehrke and Ralf M\"oller}, booktitle = {{IEEE} International Conference on Big Knowledge, (ICBK 2019), Beijing, China, November 10-11, 2019}, year={2019}, pages={81--86}, publisher = {{IEEE}}, url = {https://doi.org/10.1109/ICBK.2019.00019}, publisher = {IEEE} } |
Which Patient to Treat Next? Probabilistic Stream-based Reasoning for Decision Support and Monitoring, in IEEE International Conference on Big Knowledge, (ICBK 2019), Beijing, China, November 10-11, 2019 , IEEE, Nov.2019. pp. 73--80.
DOI: | https://doi.org/10.1109/ICBK.2019.00018 |
Bibtex: | ![]() @inproceedings{GehSchBrMo19a, author = {Marcel Gehrke and Simon Schiff and Tanya Braun and Ralf M\"oller}, title={{Which Patient to Treat Next? Probabilistic Stream-based Reasoning for Decision Support and Monitoring}}, booktitle = {{IEEE} International Conference on Big Knowledge, (ICBK 2019), Beijing, China, November 10-11, 2019}, year = {2019}, pages = {73--80}, publisher = {IEEE}, doi={https://doi.org/10.1109/ICBK.2019.00018} } |
Inference in Statistical Relational AI, in Proceedings of the International Conference on Conceptual Structures 2019 , Springer, Jul.2019. pp. xvii--xix.
DOI: | https://doi.org/10.1007/978-3-030-23182-8 |
Bibtex: | ![]() @inproceedings{BraGe19a, author = {Tanya Braun and Marcel Gehrke}, title = {{Inference in Statistical Relational AI}}, Booktitle = {Proceedings of the International Conference on Conceptual Structures 2019}, year = {2019}, publisher = {Springer}, pages = {xvii--xix}, doi = {https://doi.org/10.1007/978-3-030-23182-8} } |
Lifted Temporal Most Probable Explanation, in Graph-Based Representation and Reasoning - 24th International Conference on Conceptual Structures (ICCS 2019) , Springer, Jul.2019. pp. 72--85.
DOI: | https://doi.org/10.1007/978-3-030-23182-8_6 |
ISBN: | 978-3-030-23182-8 |
Bibtex: | ![]() @inproceedings{GehBrMo19c, author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller}, title = {{Lifted Temporal Most Probable Explanation}}, booktitle = {Graph-Based Representation and Reasoning - 24th International Conference on Conceptual Structures (ICCS 2019)}, series = {Lecture Notes in Computer Science}, volume = {11530}, pages = {72--85}, publisher = {Springer}, year = {2019}, doi = {https://doi.org/10.1007/978-3-030-23182-8_6}, isbn={978-3-030-23182-8} } |
Uncertain Evidence for Probabilistic Relational Models, in Proceedings of the 32nd Canadian Conference on Artificial Intelligence, Canadian AI 2019 , Springer, 052019. pp. 80--93.
DOI: | https://doi.org/10.1007/978-3-030-18305-9_7 |
ISBN: | 978-3-030-18305-9 |
Bibtex: | ![]() @inproceedings{GehBrMo19e, author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller}, title = {{Uncertain Evidence for Probabilistic Relational Models}}, booktitle = {Proceedings of the 32nd Canadian Conference on Artificial Intelligence, Canadian AI 2019}, series = {Lecture Notes in Computer Science}, volume = {11489}, pages = {80--93}, publisher = {Springer}, isbn={978-3-030-18305-9}, year = {2019}, publisher = {Springer}, doi = {https://doi.org/10.1007/978-3-030-18305-9_7}, } |
Relational Forward Backward Algorithm for Multiple Queries, in Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference, Sarasota, Florida, USA, May 19-22 , AAAI Press, May2019. pp. 464--469.
File: | 18230 |
Bibtex: | ![]() @inproceedings{GehBrMo19a, author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller}, title = {{Relational Forward Backward Algorithm for Multiple Queries}}, booktitle = {Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference, Sarasota, Florida, USA, May 19-22}, pages = {464--469}, publisher = {{AAAI} Press}, year = {2019}, url = {https://aaai.org/ocs/index.php/FLAIRS/FLAIRS19/paper/view/18230} } |
Lifted Temporal Maximum Expected Utility, in Proceedings of the 32nd Canadian Conference on Artificial Intelligence (Canadian AI 2019), Kingston, ON, Canada, May 28-31, 2019 , Springer, May2019. pp. 380--386.
DOI: | https://doi.org/10.1007/978-3-030-18305-9_33 |
ISBN: | 978-3-030-18305-9 |
Bibtex: | ![]() @inproceedings{GehBrMo19d, author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller}, title = {{Lifted Temporal Maximum Expected Utility}}, booktitle = {Proceedings of the 32nd Canadian Conference on Artificial Intelligence (Canadian AI 2019), Kingston, ON, Canada, May 28-31, 2019}, series = {Lecture Notes in Computer Science}, volume = {11489}, pages = {380--386}, publisher = {Springer}, year = {2019}, doi = {https://doi.org/10.1007/978-3-030-18305-9_33}, isbn={978-3-030-18305-9} } |
Ontology-Based Data Access to Big Data, Open J. Databases , vol. 6, no. 1, pp. 21--32, 2019.
File: | OJDB\_2019v6i1n03\_Schiff.html |
Bibtex: | ![]() @article{SchiffMO19, author = {Simon Schiff and Ralf M{\"{o}}ller and {\"{O}}zg{\"{u}}r L. {\"{O}}z{\c{c}}ep}, title = {Ontology-Based Data Access to Big Data}, journal = {Open J. Databases}, volume = {6}, number = {1}, pages = {21--32}, year = {2019}, url = {https://www.ronpub.com/ojdb/OJDB\_2019v6i1n03\_Schiff.html} } |
Lifted Maximum Expected Utility, in Artificial Intelligence in Health , Springer International Publishing, 2019. pp. 131--141.
DOI: | https://doi.org/10.1007/978-3-030-12738-1_10 |
ISBN: | 978-3-030-12738-1 |
Bibtex: | ![]() @inproceedings{GehBrMo19b, Author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller and Alexander Waschkau and Christoph Strumann and Jost Steinhäuser}, Title = {{Lifted Maximum Expected Utility}}, booktitle = {Artificial Intelligence in Health}, pages={131--141}, year = {2019}, isbn={978-3-030-12738-1}, doi={https://doi.org/10.1007/978-3-030-12738-1_10}, publisher = {Springer International Publishing} } |
2018
Answering Multiple Conjunctive Queries with the Lifted Dynamic Junction Tree Algorithm, in Proceedings of the AI 2018: Advances in Artificial Intelligence , Springer, Dec.2018. pp. 543--555.
DOI: | https://doi.org/10.1007/978-3-030-03991-2_50 |
ISBN: | 978-3-030-03991-2 |
Bibtex: | ![]() @inproceedings{GehBrMo18d, author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller}, title = {{Answering Multiple Conjunctive Queries with the Lifted Dynamic Junction Tree Algorithm}}, booktitle = {Proceedings of the AI 2018: Advances in Artificial Intelligence}, year = {2018}, pages={543--555}, publisher={Springer}, isbn={978-3-030-03991-2}, doi = {https://doi.org/10.1007/978-3-030-03991-2_50} } |
Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm, in Proceedings of the AI 2018: Advances in Artificial Intelligence , Springer, Dec.2018. pp. 556--562.
DOI: | https://doi.org/10.1007/978-3-030-03991-2_51 |
ISBN: | 978-3-030-03991-2 |
File: | 1807.00744 |
Bibtex: | ![]() @inproceedings{GehBrMo18e, author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller}, title = {{Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm}}, booktitle = {Proceedings of the AI 2018: Advances in Artificial Intelligence}, year = {2018}, pages={556--562}, publisher = {Springer}, isbn={978-3-030-03991-2}, doi={https://doi.org/10.1007/978-3-030-03991-2_51} } |
Towards Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm, in Proceedings of KI 2018: Advances in Artificial Intelligence , Springer, Sep.2018. pp. 38--45.
DOI: | https://doi.org/10.1007/978-3-030-00111-7_4 |
ISBN: | 978-3-030-00111-7 |
Bibtex: | ![]() @inproceedings{GehBrMo18c, author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller}, title = {{Towards Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm}}, booktitle = {Proceedings of {KI} 2018: Advances in Artificial Intelligence}, year = {2018}, pages={38--45}, publisher = {Springer}, doi = {https://doi.org/10.1007/978-3-030-00111-7_4}, isbn={978-3-030-00111-7} } |
Answering Hindsight Queries with Lifted Dynamic Junction Trees, in 8th International Workshop on Statistical Relational AI at the 27th International Joint Conference on Artificial Intelligence , 072018.
File: | 1807.01586 |
Bibtex: | ![]() @inproceedings{GehBrMo18b, author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller}, title = {{Answering Hindsight Queries with Lifted Dynamic Junction Trees}}, booktitle = {8th International Workshop on Statistical Relational AI at the 27th International Joint Conference on Artificial Intelligence}, year = {2018}, url = {https://arxiv.org/abs/1807.01586} } |
Towards Lifted Maximum Expected Utility, in Proceedings of the First Joint Workshop on Artificial Intelligence in Health in Conjunction with the 27th IJCAI, the 23rd ECAI, the 17th AAMAS, and the 35th ICML , CEUR-WS.org, 072018. pp. 93--96.
File: | |
Bibtex: | ![]() @inproceedings{Gehrke2018TLMEU, Author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller and Alexander Waschkau and Christoph Strumann and Jost Steinhäuser}, Title = {{Towards Lifted Maximum Expected Utility}}, Year = {2018}, Booktitle={Proceedings of the First Joint Workshop on Artificial Intelligence in Health in Conjunction with the 27th IJCAI, the 23rd ECAI, the 17th AAMAS, and the 35th ICML}, series = {{CEUR} Workshop Proceedings}, volume = {2142}, year = {2018}, pages = {93--96}, publisher = {CEUR-WS.org}, url = {http://ceur-ws.org/Vol-2142/short8.pdf}} |
Lifted Dynamic Junction Tree Algorithm, in Proceedings of the International Conference on Conceptual Structures , Springer, 062018. pp. 55--69.
DOI: | https://doi.org/10.1007/978-3-319-91379-7_5 |
File: | Dateilink |
Bibtex: | ![]() @inproceedings{gehrke2018ldjt, author={Marcel Gehrke and Tanya Braun and Ralf M{\"o}ller}, title={{Lifted Dynamic Junction Tree Algorithm}}, booktitle={Proceedings of the International Conference on Conceptual Structures}, year={2018}, pages = {55--69} publisher={Springer}, doi = {https://doi.org/10.1007/978-3-319-91379-7_5} } |
Efficient Enriching of Synthesized Relational Patient Data with Time Series Data, Procedia Computer Science , vol. 141, pp. 531 - 538, 2018. Elsevier Science.
DOI: | https://doi.org/10.1016/j.procs.2018.10.130 |
Bibtex: | ![]() @article{SchGeMo18a, author = {Simon Schiff and Marcel Gehrke and Ralf M\"oller}, title = {{Efficient Enriching of Synthesized Relational Patient Data with Time Series Data}}, journal = {Procedia Computer Science}, volume = {141}, pages = {531 - 538}, year = {2018}, note = {The 8th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH-2018) / Affiliated Workshops}, issn = {1877-0509}, doi = {https://doi.org/10.1016/j.procs.2018.10.130}, publisher = {Elsevier Science} } |
Ontology-based Data Access to Big Data, Open Journal of Databases (OJDB) , vol. 6, pp. 21--32, 2018.
2014
Tag des Systems Engineering, Carl Hanser Verlag, 2014, pp. 279--288.