STEM Faculty

Angelo Salatino

Research Fellow

Professional biography

Dr. Angelo Salatino is a Research Fellow at the Scholarly Knowledge team (SKM3), at the Knowledge Media Institute (KMi) of the Open University. He obtained a Ph.D., studying methods for the early detection of research trends. In particular, his project aimed at identifying the emergence of new research topics at their embryonic stage (i.e., before being recognised by the research community).

Currently, he is mainly working on: i) new technologies for classifying scientific papers according to their relevant research topics, and ii) how the research output of academia fosters innovation in the industry.

Research interests

His research interests are in the areas of Semantic Web, Network Science and Knowledge Discovery technologies, with focus on the structure and evolution of science: Science of Science

Latest news

KMi PhD student brings his research to Amazon

07 Oct 2026

Tanay Aggarwal, a PhD student at KMi, has joined Amazon as an Applied Scientist II for a 16-week internship in…

Three new UKRI projects strengthen KMi’s leadership in AI for…

30 Sep 2026

KMi’s Francesco Osborne and Angelo Salatino, have secured UK Research and Innovation (UKRI) support for three new metascience projects worth…

Celebrating the success of SEMANTiCS 2026

21 Sep 2026

Last week, from 15 to 17 September, the 22nd edition of the International Conference on Semantics Systems (commonly known as…

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Latest publications

Displaying 10 of 69 publications

Fadda, M., Motta, E., Osborne, F., Reforgiato Recupero, D. and Salatino, A., 2026, ‘Generating knowledge graphs from news articles via multi-agent claim extraction and attribution’, Knowledge-Based Systems, 352, https://oro.open.ac.uk/111827/.
Ramzan, F., Salatino, A., Osborne, F., Reforgiato Recupero, D. and Motta, E., 2026, ‘CSO Classifier 4’, 0: Software for efficient ontology-based topic annotation in computer science. SoftwareX, 35, https://oro.open.ac.uk/111829/.
Fadda, M., Motta, E., Osborne, F., Reforgiato Recupero, D. and Salatino, A., 2026, ‘Integrating Large Language Models and knowledge graphs to capture political viewpoints in news media’, EPJ Data Science, 15(1), https://oro.open.ac.uk/111485/.
Aggarwal, T., Salatino, A., Osborne, F. and Motta, E., 2026, ‘Leveraging Large Language Models for Generating Research Topic Ontologies: A Multi-Disciplinary Study’, ACM Transactions on Intelligent Systems and Technology, 17(5), https://oro.open.ac.uk/110795/.
Aggarwal, T., Salatino, A., Osborne, F. and Motta, E., 2026, ‘Benchmarking Resource-Efficient LLMs for Research Topic Ontology Generation in the Biomedical Field’, in Workshop on LLM-driven Knowledge Graph and Ontology Engineering (llms4kgoe) 2026 co-located with ESWC 2026, 11 May 2026, Dubrovnik, Croatia., https://oro.open.ac.uk/112032/.
Salatino, A., Osborne, F., Recupero, D. R., Angioni, S. and Motta, E., 2026, ‘Does Diversity of Expertise Drive Citation Impact? Evidence from Computer Science’, Scientometrics, 131 pp. 1119–1146., https://oro.open.ac.uk/109014/.
Bolanos Burgos, F., Salatino, A. A., Osborne, F. and Motta, E., 2026, ‘Modelling and classifying the components of literature reviews: a novel annotation schema and evaluation of transformer models’, PeerJ Computer Science, 12, https://oro.open.ac.uk/110897/.
Yu, L., Salatino, A. and Filgueira, R., 2026, ‘Mapping Change: A Temporal and Semantic Knowledge Base of Scottish Gazetteers’, in Acosta, Maribel; van Erp, Marieke; Rudolph, Sebastian; Hartig, Olaf; Spahiu, Blerina and Rula, Anisa eds. The Semantic Web: 23rd European Semantic Web Conference, ESWC 2026, Dubrovnik, Croatia, May 10–14, 2026, Proceedings, Part II. Lecture Notes in Computer Science (16550). Springer, pp. 76–94., https://oro.open.ac.uk/110662/.
Aggarwal, T., Salatino, A., Osborne, F. and Motta, E., 2026, ‘Large language models for scholarly ontology generation: An extensive analysis in the engineering field’, Information Processing & Management, 63(1), https://oro.open.ac.uk/105868/.
Meloni, A., Reforgiato Recupero, D., Osborne, F., Salatino, A. A., Motta, E., Vahadati, S. and Lehmann, J., 2025, ‘Exploring Large Language Models for Scientific Question Answering via Natural Language to SPARQL Translation’, ACM Transactions on Intelligent Systems and Technology, 17(6), https://oro.open.ac.uk/105679/.

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