Merge pull request #15 from AKSW/dev: updated paper list

updated paper list:
* updated ESWC-Paper with official publication info
* added Bayerlein et al. paper

aksw.bib

@@ -12542,11 +12542,18 @@ @InProceedings{Brei2024Leveragingsmalllanguage
 }
 
 @InProceedings{Frey2024AssessingEvolutionLLM,
-  author    = {Johannes Frey and Lars-Peter Meyer and Felix Brei and Sabine Gründer-Fahrer and Michael Martin},
-  booktitle = {Proceedings of Special Track Large Language Models for Knowledge Engineering at Extended Semantic Web Conference 2024 ({ESWC24})},
-  title     = {Assessing the Evolution of {LLM} capabilities for Knowledge Graph Engineering in 2023},
-  year      = {2024},
+  author    = {Frey, Johannes and Meyer, Lars-Peter and Brei, Felix and Gründer-Fahrer, Sabine and Martin, Michael},
+  booktitle = {The Semantic Web: {ESWC} 2024 Satellite Events},
+  title     = {Assessing the Evolution of {LLM} Capabilities for Knowledge Graph Engineering in 2023},
+  year      = {2025},
+  pages     = {51--60},
+  publisher = {Springer Nature Switzerland},
+  series    = {Lecture Notes in Computer Science},
+  volume    = {15344},
   abstract  = {In this study, we evaluate the evolution of LLM capabilities w.r.t. the RDF Turtle and SPARQL language as foundational skills to assist with various KGE tasks. We measure the LLM response quality using 6 LLM-KG-Bench tasks for a total of 15 LLM versions available over the course of 2023, covering 5 different “major version” LLM classes (GPT3.5 Turbo, GPT4, Claude-1.x, Claude-2.x, and Claude-instant-1.x).},
+  doi       = {10.1007/978-3-031-78952-6_5},
+  isbn      = {9783031789526},
+  issn      = {1611-3349},
   keywords  = {group_aksw sys:relevantFor:infai es frey lpmeyer martin},
   url       = {https://2024.eswc-conferences.org/wp-content/uploads/2024/05/77770050.pdf},
 }
@@ -12635,4 +12642,18 @@ @InProceedings{Stadler2024fair
   url       = {https://repository.publisso.de/resource/frl:6483281/data},
 }
 
+@Article{Bayerlein2024ConceptsSemanticallyAccessible,
+  author    = {Bayerlein, Bernd and Waitelonis, Jörg and Birkholz, Henk and Jung, Matthias and Schilling, Markus and v. Hartrott, Philipp and Bruns, Marian and Schaarschmidt, Jörg and Beilke, Kristian and Mutz, Marcel and Nebel, Vincent and Königer, Veit and Beran, Lisa and Kraus, Tobias and Vyas, Akhilesh and Vogt, Lars and Blum, Moritz and Ell, Basil and Chen, Ya‐Fan and Waurischk, Tina and Thomas, Akhil and Durmaz, Ali Riza and Ben Hassine, Sahar and Fresemann, Carina and Dziwis, Gordian and Beygi Nasrabadi, Hossein and Hanke, Thomas and Telong, Melissa and Pirskawetz, Stephan and Kamal, Mohamed and Bjarsch, Thomas and Pähler, Ursula and Hofmann, Peter and Leemhuis, Mena and Özçep, Özgür L. and Meyer, Lars‐Peter and Skrotzki, Birgit and Neugebauer, Jörg and Wenzel, Wolfgang and Sack, Harald and Eberl, Chris and Portella, Pedro Dolabella and Hickel, Tilmann and Mädler, Lutz and Gumbsch, Peter},
+  journal   = {Advanced Engineering Materials},
+  title     = {Concepts for a Semantically Accessible Materials Data Space: Overview over Specific Implementations in Materials Science},
+  year      = {2024},
+  issn      = {1527-2648},
+  month     = dec,
+  abstract  = {This article describes advancements in the ongoing digital transformation in materials science and engineering. It is driven by domain-specific successes and the development of specialized digital data spaces. There is an evident and increasing need for standardization across various subdomains to support science data exchange across entities. The MaterialDigital Initiative, funded by the German Federal Ministry of Education and Research, takes on a key role in this context, fostering collaborative efforts to establish a unified materials data space. The implementation of digital workflows and Semantic Web technologies, such as ontologies and knowledge graphs, facilitates the semantic integration of heterogeneous data and tools at multiple scales. Central to this effort is the prototyping of a knowledge graph that employs application ontologies tailored to specific data domains, thereby enhancing semantic interoperability. The collaborative approach of the Initiative's community provides significant support infrastructure for understanding and implementing standardized data structures, enhancing the efficiency of data-driven processes in materials development and discovery. Insights and methodologies developed via the MaterialDigital Initiative emphasize the transformative potential of ontology-based approaches in materials science, paving the way toward simplified integration into a unified, consolidated data space of high value.},
+  doi       = {10.1002/adem.202401092},
+  keywords  = {group_aksw sys:relevantFor:infai es lpmeyer},
+  publisher = {Wiley},
+  url       = {https://onlinelibrary.wiley.com/doi/10.1002/adem.202401092},
+}
+
 @Comment{jabref-meta: databaseType:bibtex;}