KMi is a diverse and multidisciplinary R&D lab that has been at the forefront of innovation since 1995, conducting research in computing technologies for social and environmental good. Our research spans Semantic Technologies, Artificial Intelligence, Educational Media, Social Data Science, Scholarly Data, Blockchain, Citizen Science, Collective Intelligence, Smart Cities, and others.
Upcoming Seminar
An AI Ethics Primer - How to apply basic ethical principles to machine decisions
This event will take place on Tuesday 25 February 2025
Em Dean - Knowledge Media Institute, The Open University
This participatory seminar attempts to de-mystify the process of "doing ethics" and gives participants practical considerations and techniques for applying ethical principles in...
Showcase
People
I'm working as a UX designer for CORE. With the team, we improve current and develop new features for the CORE dashboard.
Works on improving and and maintaining CORE (http://core.ac.uk) FOSTER (http://fosteropenscience.eu) and Stories Of Change (http://storiesofchange.ac.uk). Once he was a Super Mario plumber.
Testimonials
"If you are or want to be a brilliant mind, this is where you want to be!"
Valentina Presutti, Institute of Cognitive Science and Technologies, Italy
"I cannot imagine going to a conference without experiencing deep scientific conversations with KMiers!"
Raphaël Troncy, EURECOM: Graduate School & Research Center, France
"Top location for SW research for decades and going strong!"
Pascal Hitzler, Kansas State University, USA
Publications
Herodotou, C., Carr, J., Shrestha, S., Comfort, C., Bayer, V., Maguire, C., Lee, J., Mulholland, P. and Fernandez, M. (2025) Prescriptive analytics motivating distance learning student action: A case study of a student-facing dashboard, LAK25: The 15th International Learning Analytics and Knowledge Conference (LAK 2025), Dublin, Ireland
Ao, S. (2025) Building Trustworthy AI: Uncertainty Quantification and Failure Detection in Large Vision-Language Models
Daga, E. (2025) Process Knowledge Graphs (PKG): Towards unpacking and repacking AI applications, Journal of Web Semantics, 84
