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Document pages: 20 pages
Abstract: Innovation ecosystems can be naturally described as a collection of networkedentities, such as experts, institutions, projects, technologies and products.Representing in a machine-readable form these entities and their relations isnot entirely attainable, due to the existence of abstract concepts such asknowledge and due to the confidential, non-public nature of this information,but even its partial depiction is of strong interest. The representation ofinnovation ecosystems incarnated as knowledge graphs would enable thegeneration of reports with new insights, the execution of advanced dataanalysis tasks. An ontology to capture the essential entities and relations ispresented, as well as the description of data sources, which can be used topopulate innovation knowledge graphs. Finally, the application case of theUniversidad Politecnica de Madrid is presented, as well as an insight of futureapplications.
Document pages: 20 pages
Abstract: Innovation ecosystems can be naturally described as a collection of networkedentities, such as experts, institutions, projects, technologies and products.Representing in a machine-readable form these entities and their relations isnot entirely attainable, due to the existence of abstract concepts such asknowledge and due to the confidential, non-public nature of this information,but even its partial depiction is of strong interest. The representation ofinnovation ecosystems incarnated as knowledge graphs would enable thegeneration of reports with new insights, the execution of advanced dataanalysis tasks. An ontology to capture the essential entities and relations ispresented, as well as the description of data sources, which can be used topopulate innovation knowledge graphs. Finally, the application case of theUniversidad Politecnica de Madrid is presented, as well as an insight of futureapplications.