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The Web of AI project has concluded!
Web of AI helps to better conceptualise and use AI on the World Wide Web.  (16.05.2022)
Förderjahr 2020 / Project Call #15 / ProjektID: 5158 / Projekt: Web of AI

Web of AI helps to better conceptualise and use AI on the World Wide Web.  🤖🌐

Based on the Web Ontology Language (OWL), we developed, together with international partners, a comprehensive, formal model of artificial intelligence tasks and systems called the Intelligence Task Ontology and Knowledge Graph (ITO). ITO covers the entire spectrum of AI from image recognition to text translation to ECG interpretation. 

With the help of the model developed, AI services can be semantically annotated and thus better found and used. The developed model enables fundamental economic and scientific analyses: Which problems/business processes can now be addressed well by AI services? Which processes are not yet well addressed?

Web of AI has concluded after an exciting and productive time! Here we provide entry points for discovering the project results.

Entry points for discovering the project results

You can find the Github page of ITO here: https://github.com/OpenBioLink/ITO/

We also created a tailored, interactive portal for visualizing and understanding the content of the model: https://openbiolink.github.io/ITOExplorer/ 

Last but not least, our work and its result are document in four scientific papers:

Adriano Barbosa-Silva, Simon Ott, Kathrin Blagec, Jan Brauner, Matthias Samwald. “Mapping global dynamics of benchmark creation and saturation in artificial intelligence”. arXiv:2203.04592, March 2022. https://arxiv.org/abs/2203.04592 

Kathrin Blagec, Adriano Barbosa-Silva, Simon Ott, Matthias Samwald. “A curated, ontology-based, large-scale knowledge graph of artificial intelligence tasks and benchmarks”. arXiv:2110.01434, October 2021. https://arxiv.org/abs/2110.01434 

Kathrin Blagec, Georg Dorffner, Milad Moradi, Simon Ott, Matthias Samwald. “A Global Analysis of Metrics Used for Measuring Performance in Natural Language Processing.” In Workshop on Efficient Benchmarking in NLP at ACL 2022, 2022. http://arxiv.org/abs/2204.11574  

Kathrin Blagec, Jakob Kraiger, Wolfgang Frühwirt, Matthias Samwald. “Benchmark Datasets Driving Artificial Intelligence Development Fail to Capture the Needs of Medical Professionals”. arXiv:2201.07040, January 2022. http://arxiv.org/abs/2201.07040  

 

We thank netidee for making these exciting developments possible! 🤓😊

 

 

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