Daga, E., & Groth, P. (2024). Data journeys: Explaining AI workflows through abstraction. Semantic Web, 15(4). https://doi.org/10.3233/sw-233407
Karabulut, E., Pileggi, S. F., Groth, P., & Degeler, V. (2024). Ontologies in Digital Twins: A Systematic Literature Review. Future Generation Computer Systems, 153, 442-456. https://doi.org/10.1016/j.future.2023.12.013[details]
Karabulut, E., Pileggi, S., Groth, P. & Degeler, V. (21-7-2023). Data and Statistics for the SLR entitled "Ontologies in Digital Twins: A Systematic Literature Review". Zenodo. https://doi.org/10.5281/zenodo.8172341
Soiland-Reyes, S., Goble, C., & Groth, P. (2024). Evaluating FAIR Digital Object and Linked Data as distributed object systems. PeerJ Computer Science, 10, Article e1781. https://doi.org/10.7717/PEERJ-CS.1781[details]
Allen, B. P., Stork, L., & Groth, P. (2023). Knowledge Engineering using Large Language Models. Transactions on Graph Data and Knowledge, 1(1), Article 3. https://doi.org/10.4230/TGDK.1.1.3[details]
Cong, T., Sun, Z., Groth, P., Jagadish, H., & Hulsebos, M. (2023). Introducing the Observatory Library for End-to-End Table Embedding Inference. In NeurIPS 2023 Second Table Representation Learning Workshop Neural Information Processing Systems Foundation. https://openreview.net/forum?id=JIrTIMI5Yd
Daza, D., Alivanistos, D., Mitra, P., Pijnenburg, T., Cochez, M., & Groth, P. (2023). BioBLP: a modular framework for learning on multimodal biomedical knowledge graphs. Journal of Biomedical Semantics, 14, Article 20. https://doi.org/10.1186/s13326-023-00301-y[details]
Dinh, T. A., den Boef, J., Cornelisse, J., & Groth, P. (2023). E2EG: End-to-End Node Classification Using Graph Topology and Text-based Node Attributes. In J. Wang, Y. He, T. N. Dinh, C. Grant, M. Qiu, & W. Pedrycz (Eds.), 23rd IEEE International Conference on Data Mining Workshops: 1-4 December 2023, Shanghai, China : proceedings (pp. 1084-1091). (ICDMW; Vol. 2023). IEEE Computer Society. https://doi.org/10.1109/ICDMW60847.2023.00142[details]
Grafberger, S., Groth, P., & Schelter, S. (2023). Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines. Proceedings of the ACM on Management of Data, 1(2), Article 128. https://doi.org/10.1145/3589273[details]
Grafberger, S., Groth, P., & Schelter, S. (2023). Provenance Tracking for End-to-End Machine Learning Pipelines. In The ACM Web Conference 2023: Companion of the World Wide Web Conference WWW 2023 : April 30-May 4, 2023, Austin, Texas, USA (pp. 1512). Association for Computing Machinery. https://doi.org/10.1145/3543873.3587557[details]
Gregory, K., Groth, P., Scharnhorst, A., & Wyatt, S. (2023). The Mysterious User of Research Data: Knitting Together Science and Technology Studies with Information and Computer Science. In K. Bijsterveld, & A. Swinnen (Eds.), Interdisciplinarity in the Scholarly Life Cycle: Learning by Example in Humanities and Social Science Research (pp. 191-211). Palgrave Macmillan. https://doi.org/10.1007/978-3-031-11108-2_11[details]
Hulsebos, M., Demiralp, Ç., & Groth, P. (2023). GitTables: A Large-Scale Corpus of Relational Tables. Proceedings of the ACM on Management of Data, 1(1), Article 30. https://doi.org/10.1145/3588710[details]
Jullien, S., Ariannezhad, M., Groth, P., & Rijke, M. D. (2023). A Simulation Environment and Reinforcement Learning Method for Waste Reduction. Transactions on Machine Learning Research, (4), Article 769. https://openreview.net/forum?id=KSvr8A62MD[details]
Karabulut, E., Degeler, V., & Groth, P. (2023). Semantic Association Rule Learning from Time Series Data and Knowledge Graphs. In A. Waaler, E. Kharlamov, B. Zhou, A. Soylu, D. Kyritsis, D. Roman, O. Savkovic, & S. Staab (Eds.), Proceedings of the Second International Workshop on Semantic Industrial Information Modelling (SemIIM 2023) : co-located with the 22nd International Semantic Web Conference (ISWC 2023) : Greece, Athens, 7 November 2023 Article 3 (CEUR workshop proceedings; Vol. 3647). CEUR-WS. https://doi.org/10.48550/arXiv.2310.07348[details]
Li, X., Hughes, A., Llugiqi, M., Polat, F., Groth, P., & Ekaputra, F. J. (2023). Knowledge-centric Prompt Composition for Knowledge Base Construction from Pre-trained Language Models. In S. Razniewski, J.-C. Kalo, S. Singhania, & J. Z. Pan (Eds.), Joint proceedings of the 1st workshop on Knowledge Base Construction from Pre-Trained Language Models (KBC-LM) and the 2nd challenge on Language Models for Knowledge Base Construction (LM-KBC): co-located with the 22nd International Semantic Web Conference (ISWC 2023) : Athens, Greece, November 6, 2023 Article 3 (CEUR Workshop Proceedings; Vol. 3577). CEUR-WS. https://ceur-ws.org/Vol-3577/paper3.pdf[details]
Li, X., Polat, F., & Groth, P. (2023). Do Instruction-tuned Large Language Models Help with Relation Extraction? In S. Razniewski, J.-C. Kalo, S. Singhania, & J. Z. Pan (Eds.), Joint proceedings of the 1st workshop on Knowledge Base Construction from Pre-Trained Language Models (KBC-LM) and the 2nd challenge on Language Models for Knowledge Base Construction (LM-KBC): co-located with the 22nd International Semantic Web Conference (ISWC 2023) : Athens, Greece, November 6, 2023 Article 15 (CEUR Workshop Proceedings; Vol. 3577). CEUR-WS. https://ceur-ws.org/Vol-3577/paper15.pdf[details]
Nevin, J., Groth, P., & Lees, M. (2023). An approach for analysing the impact of data integration on complex network diffusion models. Journal of complex networks, 11(4), Article cnad025. https://doi.org/10.1093/comnet/cnad025[details]
Nevin, J., Lees, M. & Groth, P. (2022). NIDMod - Network Integration and Diffusion Modeller. GitHub. https://github.com/jim-g-n/nidmod
Nevin, J., Groth, P., & Lees, M. (2023). Data Integration Landscapes: The Case for Non-optimal Solutions in Network Diffusion Models. In J. Mikyška, C. de Mulatier, M. Paszynski, V. V. Krzhizhanovskaya, J. J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science – ICCS 2023: 23rd International Conference, Prague, Czech Republic, July 3–5, 2023 : proceedings (Vol. I, pp. 494-508). (Lecture Notes in Computer Science; Vol. 14073). Springer. https://doi.org/10.1007/978-3-031-35995-8_35[details]
Polat, F., Tiddi, I., Groth, P., & Vossen, P. (2023). Improving Graph-to-Text Generation Using Cycle Training. In S. Carvalho, A. F. Khan, A. Ostroški Anić, B. Spahiu, J. Gracia, J. P. McCrae, D. Gromann, B. Heinisch, & A. Salgado (Eds.), Language, data and knowledge 2023: LDK 2023 : proceedings of the 4th Conference on Language, Data and Knowledge : 12-15 September 2023, Vienna, Austria (pp. 256-261). NOVA CLUNL. https://doi.org/10.34619/srmk-injj[details]
Simperl, E., Groth, P., Staab, S., Sabou, M., Blomqvist, E., & Allen, B. (2023). Knowledge Engineering with Language Models and Neural Methods. Dagstuhl Reports, 12(9), 93-96.
Tamašauskaitė, G., & Groth, P. (2023). Defining a Knowledge Graph Development Process Through a Systematic Review. ACM Transactions on Software Engineering and Methodology, 32(1), Article 27. Advance online publication. https://doi.org/10.1145/3522586[details]
Carriero, V. A., Groth, P., & Presutti, V. (2022). Towards improving Wikidata reuse with emerging patterns. In L.-A. Kaffee, S. Razniewski, G. Amaral, & K. S. Alghamdi (Eds.), Proceedings of the 3rd Wikidata Workshop 2022 : co-located with the 21st International Semantic Web Conference (ISWC2022) : Virtual Event, Hangzhou, China, October 2022 Article 2 (CEUR Workshop Proceedings; Vol. 3262). CEUR-WS. https://ceur-ws.org/Vol-3262/paper2.pdf[details]
Daza, D., Cochez, M., & Groth, P. (2022). SlotGAN: Detecting Mentions in Text via Adversarial Distant Learning. In A. Vlachos, P. Agrawal, A. Martins, G. Lampouras, & C. Lyu (Eds.), Sixth Workshop on Structured Prediction for NLP: Proceedings of the Workshop : SPNLP 2022 : May 27, 2022 (pp. 32-39). Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.spnlp-1.4[details]
Grafberger, S., Groth, P., & Schelter, S. (2022). Towards data-centric what-if analysis for native machine learning pipelines. In Proceedings of the Sixth Workshop on Data Management for End-to-End Machine Learning: in conjunction with the 2022 ACM SIGMOD/PODS Conference, Philadelphia, PA, USA Article 3 Association for Computing Machinery. https://doi.org/10.1145/3533028.3533303[details]
Groth, P., Vidal, M-E., Suchanek, F., Szekely, P., Kapanipathi, P., Pesquita, C., Skaf-Molli, H., & Tamper, M. (Eds.) (2022). The Semantic Web: 19th International Conference, ESWC 2022, Hersonissos, Crete, Greece, May 29–June 2, 2022 : proceedings. (Lecture Notes in Computer Science; Vol. 13261). Springer. https://doi.org/10.1007/978-3-031-06981-9[details]
Harper, C. A., Daniel, R., & Groth, P. (2022). Question Answering with Additive Restrictive Training (QuAART): Question Answering for the Rapid Development of New Knowledge Extraction Pipelines. In O. Corcho, L. Hollink, O. Kutz, N. Troquard, & F. J. Ekaputra (Eds.), Knowledge Engineering and Knowledge Management: 23rd International Conference, EKAW 2022, Bolzano, Italy, September 26–29, 2022 : proceedings (pp. 51-65). (Lecture Notes in Computer Science; Vol. 13514), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-031-17105-5_4[details]
Schröder, M., Staehlke, S., Groth, P., Nebe, J. B., Spors, S., & Krüger, F. (2022). Structure-based knowledge acquisition from electronic lab notebooks for research data provenance documentation. Journal of Biomedical Semantics, 13, Article 4. https://doi.org/10.1186/s13326-021-00257-x[details]
Soiland-Reyes, S., Sefton, P., Crosas, M., Castro, L. J., Coppens, F., Fernández, J. M., Garijo, D., Grüning, B., La Rosa, M., Leo, S., Ó Carragáin, E., Portier, M., Trisovic, A., RO-Crate Community, Groth, P., & Goble, C. (2022). Packaging research artefacts with RO-Crate. Data Science, 5(2), 97-138. Advance online publication. https://doi.org/10.3233/DS-210053[details]
Alam, M., Groth, P., de Boer, V., Pellegrini, T., Pandit, H. J., Montiel, E., Rodríguez Doncel, V., McGillivray, B., & Meroño-Peñuela, A. (Eds.) (2021). Further with Knowledge Graphs: proceedings of the 17th International Conference on Semantic Systems, 6-9 September 2021, Amsterdam, The Netherlands. (Studies on the Semantic Web; Vol. 53). IOS Press. https://doi.org/10.3233/SSW53[details]
Daza, D., Cochez, M., & Groth, P. (2021). Inductive entity representations from text via link prediction. In The Web Conference 2021: proceedings of the World Wide Web Conference WWW 2021 : April 19-23, 2021, Ljubljana, Slovenia (pp. 798-808). Association for Computing Machinery. https://doi.org/10.1145/3442381.3450141[details]
Harper, C. A., Cox, J., Kohler, C., Scerri, A., Daniel, R., & Groth, P. (2021). SemEval-2021 Task 8: MeasEval -- Extracting Counts and Measurements and their Related Contexts. In A. Palmer, N. Schneider, N. Schluter, G. Emerson, A. Herbelot, & X. Zhu (Eds.), The 15th International Workshop on Semantic Evaluation (SemEval-2021): proceedings of the workshop : August 5-6, 2021, Bangkok, Thailand (online) (pp. 306-316). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.semeval-1.38[details]
Hendriks, B., Groth, P., & van Erp, M. (2021). Recognizing and Linking Entities in Old Dutch Text: A Case Study on VOC Notary Records. In A. Weber, M. Heerlien, E. Gassó Miracle, & K. Wolstencroft (Eds.), Proceedings of the International Conference Collect and Connect: Archives and Collections in a Digital Age: Leiden, the Netherlands, November 23-24, 2020 (pp. 25-36). (CEUR Workshop Proceedings; Vol. 2810). CEUR-WS. http://ceur-ws.org/Vol-2810/paper3.pdf[details]
Lamprecht, A.-L., Palmblad, M., Ison, J., Schwämmle, V., Al Manir, M. S., Altintas, I., Baker, C. J. O., Ben Hadj Amor, A., Capella-Gutierrez, S., Charonyktakis, P., Crusoe, M. R., Gil, Y., Goble, C., Griffin, T. J., Groth, P., Ienasescu, H., Jagtap, P., Kalaš, M., Kasalica, V., ... Wolstencroft, K. (2021). Perspectives on automated composition of workflows in the life sciences. F1000Research, 10, Article 897. https://doi.org/10.12688/f1000research.54159.1[details]
Li, X., Magliacane, S., & Groth, P. (2021). The Challenges of Cross-Document Coreference Resolution in Email. In K-CAP '21: Proceedings of the 11th Knowledge Capture Conference : December 2-3, 2021 : virtual event, USA (pp. 273-276). Association for Computing Machinery. https://doi.org/10.1145/3460210.3493573[details]
Shroff, N., Vandenbussche, P.-Y., Moore, V., & Groth, P. (2021). Supporting ontology maintenance with contextual word embeddings and maximum mean discrepancy. In S. Ben Abbès, R. Hantach, P. Calvez, D. Buscaldi, D. Dessì, M. Dragoni, D. Reforgiato Recupero, & H. Sack (Eds.), Joint Proceedings of the 2nd International Workshop on Deep Learning meets Ontologies and Natural Language Processing (DeepOntoNLP 2021) & 6th International Workshop on Explainable Sentiment Mining and Emotion Detection (X-SENTIMENT 2021): co-located with co-located with 18th Extended Semantic Web Conference 2021 : Hersonissos, Greece, June 6th - 7th, 2021 (moved online) (pp. 11-19). (CEUR Workshop Proceedings; Vol. 2918). CEUR-WS. http://ceur-ws.org/Vol-2918/paper2.pdf[details]
Szarkowska, K., Moore, V., Vandenbussche, P.-Y., & Groth, P. (2021). Quality assessment of knowledge graph hierarchies using KG-BERT. In M. Alam, D. Buscaldi, M. Cochez, F. Osborne, D. Reforgiato Recupero, & H. Sack (Eds.), Proceedings of the Workshop on Deep Learning for Knowledge Graphs (DL4KG 2021): co-located with the 20th International Semantic Web Conference (ISWC 2021) : Virtual Conference, online, October 25, 2021 Article 1 (CEUR Workshop Proceedings; Vol. 3034). CEUR-WS. http://ceur-ws.org/Vol-3034/paper1.pdf[details]
West, R., Bhagat, S., Groth, P., Zitnik, M., Couto, F. M., Lisena, P., Meroño-Peñuela, A., Zhao, X., Fan, W., Yin, D., Tang, J., Shou, L., Gong, M., Pei, J., Geng, X., Zhou, X., Jiang, D., Ricaud, B., Aspert, N., ... Sephus, N. (2021). Summary of Tutorials at The Web Conference 2021. In The Web Conference 2021: companion of the World Wide Web Conference WWW 2021: April 19-23, 2021, Ljubljana, Slovenia (pp. 727–733). Association for Computing Machinery. https://doi.org/10.1145/3442442.3453701[details]
den Boef, J. B., Cornelisse, J., & Groth, P. (2021). GraphPOPE: Retaining structural graph information using position-aware node embeddings. In M. Alam, D. Buscaldi, M. Cochez, F. Osborne, D. Reforgiato Recupero, & H. Sack (Eds.), Proceedings of the Workshop on Deep Learning for Knowledge Graphs (DL4KG 2021): co-located with the 20th International Semantic Web Conference (ISWC 2021) : Virtual Conference, online, October 25, 2021 Article 3 (CEUR Workshop Proceedings; Vol. 3034). CEUR-WS. http://ceur-ws.org/Vol-3034/paper3.pdf[details]
Alam, M., Groth, P., Hitzler, P., Paulheim, H., Sack, H., & Tresp, V. (2020). CSSA'20: Workshop on Combining Symbolic and Sub-Symbolic Methods and their Applications. In CIKM '20: proceedings of the 29th ACM International Conference on Information & Knowledge Management : October 19-23, 2020, Virtual Event, Ireland (pp. 3523-3524). The Association for Computing Machinery. https://doi.org/10.1145/3340531.3414072[details]
Berger, M., Zavrel, J., & Groth, P. (2020). Effective distributed representations for academic expert search. In M. K. Chandrasekaran, A. de Waard, G. Feigenblat, D. Freitag, T. Ghosal, E. Hovy, P. Knoth, D. Konopnicki, P. Mayr, R. M. Patton, & M. Shmueli-Scheuer (Eds.), First Workshop on Scholarly Document Processing: EMNLP 2020 : proceedings of the workshop : November 19, 2020, Online (pp. 56-71). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.sdp-1.7[details]
Blomqvist, E., Groth, P., de Boer, V., Pellegrini, T., Alam, M., Käfer, T., Kieseberg, P., Kirrane, S., Meroño-Peñuela, A., & Pandit, H. J. (Eds.) (2020). Semantic Systems : In the Era of Knowledge Graphs: 16th International Conference on Semantic Systems, SEMANTiCS 2020, Amsterdam, The Netherlands, September 7-10, 2020 : proceedings. (Lecture Notes in Computer Science; Vol. 12378). Springer. https://doi.org/10.1007/978-3-030-59833-4[details]
Brate, R., Groth, P., & van Erp, M. (2020). Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels. In S. DeGaetano, A. Kazantseva, N. Reiter, & S. Szpakowicz (Eds.), The 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature: Co-located with the 28th International Conference on Computational Linguistics COLING’2020 : COLING 2020 : proceedings : December 12, 2020, Barcelona, Spain, (Online) (pp. 147-155). International Committee on Computational Linguistics. https://www.aclweb.org/anthology/2020.latechclfl-1.18[details]
Brate, R., Groth, P. & van Erp, M. (2020). Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels. Zenodo. https://doi.org/10.5281/zenodo.4199996
Chapman, A., Simperl, E., Koesten, L., Konstantinidis, G., Ibáñez, L-D., Kacprzak, E., & Groth, P. (2020). Dataset search: a survey. The VLDB Journal, 29(1), 251-272. Advance online publication. https://doi.org/10.1007/s00778-019-00564-x[details]
Gregory, K. M., Cousijn, H., Groth, P., Scharnhorst, A., & Wyatt, S. (2020). Understanding data search as a socio-technical practice. Journal of Information Science, 46(4), 459-475. https://doi.org/10.1177/0165551519837182[details]
Gregory, K., Groth, P., Scharnhorst, A., & Wyatt, S. (2020). Lost or Found? Discovering Data Needed for Research. Harvard Data Science Review, 2(2.2). https://doi.org/10.1162/99608f92.e38165eb[details]
Groth, P., Cousijn, H., Clark, T., & Goble, C. (2020). FAIR Data Reuse – the Path through Data Citation. Data Intelligence, 2(1-2), 78-86. https://doi.org/10.1162/dint_a_00030[details]
Stamatogiannakis, M., Bos, H., & Groth, P. (2020). PANDAcap: A framework for streamlining collection of full-system traces. In EuroSec 2020: proceedings of the 13th European Workshop on Systems Security : April 27, 2020, Heraklion, Crete, Greece (pp. 1-6). The Association for Computing Machinery. https://doi.org/10.1145/3380786.3391396[details]
van Erp, M., & Groth, P. (2020). Towards Entity Spaces. In N. Calzolari, F. Béchet, P. Blache, K. Choukri, C. Cieri, T. Declerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, & S. Piperidis (Eds.), LREC 2020: Twelfth International Conference on Language Resources and Evaluation : May 11-16, 2020, Palais du Pharo, Marseille, France : conference proceedings (pp. 2129-2137). The European Language Resources Association. https://www.aclweb.org/anthology/2020.lrec-1.261[details]
Gregory, K., Groth, P., Cousijn, H., Scharnhorst, A., & Wyatt, S. (2019). Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines. Journal of the Association for Information Science and Technology, 70(5), 419-432. https://doi.org/10.1002/asi.24165[details]
Groth, P., Scerri, A., Daniel, R., & Allen, B. P. (2019). End-to-end learning for answering structured queries directly over text. In M. Alam, D. Buscaldi, M. Cochez, F. Osborne, D. Reforgiato Recupero, & H. Sack (Eds.), Proceedings of the Workshop on Deep Learning for Knowledge Graphs (DL4KG2019): co-located with the 16th Extended Semantic Web Conference 2019 (ESWC 2019) : Portoroz, Slovenia, June 2, 2019 (pp. 57-70). (CEUR Workshop Proceedings; Vol. 2377). CEUR-WS. http://ceur-ws.org/Vol-2377/paper_7.pdf[details]
Groth, P., Koesten, L., Mayr, P., de Rijke, M., & Simperl, E. (2018). DATA:SEARCH'18 - Searching Data on the Web: Preface. In L. Dietz, L. Koesten, & S. Verberne (Eds.), Joint Proceedings of the First International Workshop on Professional Search (ProfS2018); the Second Workshop on Knowledge Graphs and Semantics for Text Retrieval, Analysis, and Understanding (KG4IR); and the International Workshop on Data Search (DATA:SEARCH’18): co-located with (ACM SIGIR 2018) : Ann Arbor, Michigan, USA, July 12, 2018 (pp. 65-66). (CEUR Workshop Proceedings; Vol. 2127). CEUR-WS. http://ceur-ws.org/Vol-2127/preface-datasearch.pdf[details]
Groth, P., Koesten, L., Mayr, P., de Rijke, M., & Simperl, E. (2018). DATA:SEARCH'18 - Searching data on the web. In SIGIR #41 proceedings: Ann Arbor, Michigan, USA, 08-12, July 2018 (pp. 1419-1422). Association for Computing Machinery. https://doi.org/10.1145/3209978.3210195[details]
Hoekstra, R., & Groth, P. (2015). PROV-O-Viz - Understanding the Role of Activities in Provenance. In B. Ludäscher, & B. Plale (Eds.), Provenance and Annotation of Data and Processes: 5th International Provenance and Annotation Workshop, IPAW 2014, Cologne, Germany, June 9-13, 2014 : revised selected papers (pp. 215-220). (Lecture Notes in Computer Science; Vol. 8628). Springer. https://doi.org/10.1007/978-3-319-16462-5_18[details]
Wibisono, A., Bloem, P., de Vries, G. K. D., Groth, P., Belloum, A., & Bubak, M. (2015). Generating scientific documentation for computational experiments using provenance. In B. Ludäscher, & B. Plale (Eds.), Provenance and Annotation of Data and Processes: 5th International Provenance and Annotation Workshop, IPAW 2014, Cologne, Germany, June 9-13, 2014 : revised selected papers (pp. 168-179). (Lecture Notes in Computer Science; Vol. 8628). Springer. https://doi.org/10.1007/978-3-319-16462-5_13[details]
2014
Beek, W., Groth, P., Schlobach, S., & Hoekstra, R. (2014). A Web Observatory for the Machine Processability of Structured Data on the Web. In WebSci'14: proceedings of the 2014 ACM Web Science Conference: June 23-26, 2014, Bloomington, IN, USA (pp. 249-250). Association for Computing Machinery. https://doi.org/10.1145/2615569.2615654[details]
Hoekstra, R., Groth, P., & Charlaganov, M. (2014). Linkitup: Semantic Publishing of Research Data. In V. Presutti, M. Stankovic, E. Cambria, I. Cantador, A. Di Iorio, T. Di Noia, C. Lange, D. R. Recupero, & A. Tordai (Eds.), Semantic Web Evaluation Challenge: SemWebEval 2014 at ESWC 2014, Anissaras, Crete, Greece, May 25-29, 2014: revised selected papers (pp. 95-100). (Communications in Computer and Information Science; Vol. 475). Springer. https://doi.org/10.1007/978-3-319-12024-9_12[details]
Grafberger, S., Guha, S., Groth, P., & Schelter, S. (2023). Mlwhatif: What If You Could Stop Re-Implementing Your Machine Learning Pipeline Analyses over and Over? Proceedings of the VLDB Endowment, 16(12), 4002–4005. https://doi.org/10.14778/3611540.3611606[details]
Groth, P. (Ed.), Simperl, E. (Ed.), van Erp, M. (Ed.), & Vrandečić, D. (2023). Knowledge Graphs and their Role in the Knowledge Engineering of the 21st Century. Dagstuhl Reports, 12(9), 60-120. https://doi.org/10.4230/DagRep.12.9.60[details]
Soiland-Reyes, S., Castro, L. J., Garijo, D., Portier, M., Goble, C., & Groth, P. (2022). Updating Linked Data practices for FAIR Digital Object principles. Research Ideas and Outcomes, 8, Article e94501. https://doi.org/10.3897/rio.8.e94501
Soiland-Reyes, S., Sefton, P., Castro, L. J., Coppens, F., Garijo, D., Leo, S., Portier, M., & Groth, P. (2022). Creating lightweight FAIR Digital Objects with RO-Crate. Research Ideas and Outcomes, 8, Article e93937. https://doi.org/10.3897/rio.8.e93937
Antoniou, G., Groth, P., van Harmelen, F., & Hoekstra, R. (2012). A Semantic Web Primer. (3rd ed.) (Cooperative information systems). MIT Press. [details]
2022
Groth, P., Rula, A., Schneider, J., Tiddi, I., Simperl, E., Alexopoulos, P., Hoekstra, R., Alam, M., Dimou, A., & Tamper, M. (Eds.) (2022). The Semantic Web: ESWC 2022 Satellite Events: Hersonissos, Crete, Greece, May 29–June 2, 2022 : proceedings. (Lecture Notes in Computer Science; Vol. 13384). Springer. https://doi.org/10.1007/978-3-031-11609-4[details]
2021
Alam, M., Ali, M., Groth, P., Hitzler, P., Lehmann, J., Paulheim, H., Rettinger, A., Sack, H., Sadeghi, A., & Tresp, V. (Eds.) (2021). Machine Learning with Symbolic Methods and Knowledge Graphs: co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021) : Virtual, September 17, 2021. (CEUR Workshop Proceedings; Vol. 2997). CEUR-WS. http://ceur-ws.org/Vol-2997[details]
2023
Grafberger, S., Karlaš, B., Groth, P. T., & Schelter, S. (2023). Towards Declarative Systems for Data-Centric Machine Learning. Abstract from Data-Centric Machine Learning Research work- shop (DMLR) at ICML. https://dmlr.ai/assets/accepted-papers/41/CameraReady/autodc.pdf
Hu, Q., Daza, D., Swinkels, L., Usaite, K., Hoen, R-J. ., & Groth, P. (2023). Harnessing the Web and Knowledge Graphs for Automated Impact Investing Scoring. Paper presented at KDD Workshop: Fragile Earth: AI for Climate Sustainability - from Wildfire Disaster Management to Public Health and Beyond, Long Beach, California, United States. https://doi.org/10.48550/arXiv.2308.02622
2022
Soiland-Reyes, S., Sefton, P., Castro, L. J., Coppens, F., Garijo, D., Leo, S., Portier, M., Groth, P., & Goble, C. (2022). Creating lightweight FAIR Digital Objects with RO-Crate and FAIR Signposting. Poster session presented at 1st International Conference on FAIR Digital Objects , Leiden, Netherlands. https://doi.org/10.5281/zenodo.7245315
2019
Symeonidou, A., Sazonau, V., & Groth, P. (2019). Transfer learning for biomedical named entity recognition with BioBert. Poster session presented at 15th International Conference on Semantic Systems, SEMPDS 2019, Karlsruhe, Germany. http://ceur-ws.org/Vol-2451/paper-26.pdf
Prijs / subsidie
van Noort, G. & Groth, P. (2019). Ethical MInDS: Mapping interventions for data use in squads.
2024
Hulsebos, M. (2024). Table Representation Learning. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
Karabulut, E., Pileggi, S., Groth, P. & Degeler, V. (21-7-2023). Data and Statistics for the SLR entitled "Ontologies in Digital Twins: A Systematic Literature Review". Zenodo. https://doi.org/10.5281/zenodo.8172341
Thanapalasingam, T., van Krieken, E., Bloem, P. & Groth, P. (13-4-2023). IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation. Zenodo. https://doi.org/10.5281/zenodo.8039857
Brate, R., Groth, P. & van Erp, M. (2020). Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels. Zenodo. https://doi.org/10.5281/zenodo.4199996
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