Tootfinder

You are an expert in ontologies and kn owledge graphs? You have an interest (or even better expertise) in materials science engineering? Then you should apply! Open PostDoc/Senior Researcher position at FIZ Karlsruhe ISE Research Team in the Knowledge Graph department. More info at https://www.fiz-k…

You are an expert in ontologies and knowledge graphs? You have an interest (or even better expertise) in materials science engineering? Then you should apply! Open PostDoc/Senior Researcher position at FIZ Karlsruhe ISE Research Team in the Knowledge Graph department. More info at https://www.fiz-ka…

A Hybrid AI Methodology for Generating Ontologies of Research Topics from Scientific Paper Corpora
Alessia Pisu, Livio Pompianu, Francesco Osborne, Diego Reforgiato Recupero, Daniele Riboni, Angelo Salatino
https://arxiv.org/abs/2508.04213

A Hybrid AI Methodology for Generating Ontologies of Research Topics from Scientific Paper Corpora
Taxonomies and ontologies of research topics (e.g., MeSH, UMLS, CSO, NLM) play a central role in providing the primary framework through which intelligent systems can explore and interpret the literature. However, these resources have traditionally been manually curated, a process that is time-consuming, prone to obsolescence, and limited in granularity. This paper presents Sci-OG, a semi-auto\-mated methodology for generating research topic ontologies, employing a multi-step approach: 1) Topic…

When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance
Peizhang Shao, Linrui Xu, Jinxi Wang, Wei Zhou, Xingyu Wu
https://arxiv.org/abs/2507.07748

When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance
This paper establishes the first comprehensive review of Large Language Models (LLMs) applied within the legal domain. It pioneers an innovative dual lens taxonomy that integrates legal reasoning frameworks and professional ontologies to systematically unify historical research and contemporary breakthroughs. Transformer-based LLMs, which exhibit emergent capabilities such as contextual reasoning and generative argumentation, surmount traditional limitations by dynamically capturing legal seman…

Yesterday, I've attended the MSE Research Data Forum 2025 organised by #NFDIMatWerk. Aside from the conference presentations, our little ontologies group was meeting and discussing future work on ontologies in NFDI-MatWerk, including NFDIcore, MatWerk Application Ontologies, and PMDcore.

Ontology-Aligned Embeddings for Data-Driven Labour Market Analytics
Heinke Hihn, Dennis A. V. Dittrich, Carl Jeske, Cayo Costa Sobral, Helio Pais, Timm Lochmann
https://arxiv.org/abs/2509.04942

Ontology-Aligned Embeddings for Data-Driven Labour Market Analytics
The limited ability to reason across occupational data from different sources is a long-standing bottleneck for data-driven labour market analytics. Previous research has relied on hand-crafted ontologies that allow such reasoning but are computationally expensive and require careful maintenance by human experts. The rise of language processing machine learning models offers a scalable alternative by learning shared semantic spaces that bridge diverse occupational vocabularies without extensive…

Improving Biomedical Knowledge Graph Quality: A Community Approach
Katherina G Cortes, Shilpa Sundar, Sarah Gehrke, Keenan Manpearl, Junxia Lin, Daniel Robert Korn, Harry Caufield, Kevin Schaper, Justin Reese, Kushal Koirala, Lawrence E Hunter, E. Kathleen Carter, Marcello DeLuca, Arjun Krishnan, Chris Mungall, Melissa Haendel
https://arxi…

Improving Biomedical Knowledge Graph Quality: A Community Approach
Biomedical knowledge graphs (KGs) are widely used across research and translational settings, yet their design decisions and implementation are often opaque. Unlike ontologies that more frequently adhere to established creation principles, biomedical KGs lack consistent practices for construction, documentation, and dissemination. To address this gap, we introduce a set of evaluation criteria grounded in widely accepted data standards and principles from related fields. We apply these criteria …