Published March 6, 2023 | Version v1
Preprint Open

Towards InnoGraph: A Knowledge Graph for AI Innovation

  • 1. Jozef Stefan Institute, Jozef Stefan International Postgraduate School
  • 2. University of Milano-Bicocca
  • 3. Jozef Stefan Institute
  • 4. Ontotext (Sirma AI)
  • 5. SINTEF AS

Description

Researchers seeking to comprehend the state-of-the-art innovations in a particular field of study must examine recent patents and scientific articles in that domain. Innovation ecosystems consist of interconnected information about entities such as researchers, institutions, projects, products, and technologies. However, representing such information in a machine-readable format is challenging because concepts like "knowledge" are not easily represented. Nonetheless, even a partial representation of innovation ecosystems provides valuable insights. Therefore, representing innovation ecosystems as knowledge graphs (KGs) would enable advanced data analysis and generate new insights. To this end, we propose InnoGraph, a framework that integrates multiple heterogeneous data sources to build a Knowledge Graph of the worldwide AI innovation ecosystem.
 

Notes

The work on InnoGraph is partially funded by the projects enRichMyData (HE 101070284), Graph-Massivizer (HE 101093202), DataCloud (H2020 101016835), and BigDataMine (NFR 309691). The original work is inspired by a partnership between OECD and JSI, on the OECD AI Policy Observatory.

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Towards InnoGraph A Knowledge Graph for AI Innovation.pdf

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Funding

DataCloud – ENABLING THE BIG DATA PIPELINE LIFECYCLE ON THE COMPUTING CONTINUUM 101016835
European Commission
enRichMyData – Enabling Data Enrichment Pipelines for AI-driven Business Products and Services 101070284
European Commission
Graph-Massivizer – Extreme and Sustainable Graph Processing for Urgent Societal Challenges in Europe 101093202
European Commission