Using SKGs in the emerging sector of Cooperative Connected Automated Mobility (CCAM)

The Transportation pilot of the SciLake project  announces its second scenario, which pertains to research in the emerging sector of Cooperative Connected Automated Mobility (CCAM), led by ICCS researchers in Greece. Knowledge from existing research related to co-funded European projects around CCAM will be used to enrich the previously developed Transportation Scientific Knowledge Graph (SKG) of the OpenAIRE community  and implement the project’s advancements.

The current version of the Transportation SKG has been rendered obsolete due to its outdated information regarding CCAM. With the rapid evolution of the sector, it is crucial for researchers to keep up with new trends, definitions, key terms and any other forms of expert knowledge. To address this gap, a detailed taxonomy around CCAM has been identified from another EU funded project called SINFONICA, which is publicly available under a relevant deliverable [4].

The next step is to analyze this taxonomy and cooperate with technical partners from the SciLake project to identify valuable enrichments for the SKG based on entities mentioned in the taxonomy and on patterns of importance related to CCAM in scientific metadata and texts. Experts from the domain will then be in place to examine the results, provide feedback, and identify new domain knowledge. As a result, new scilake Transport CCAM Pilot datasets are expected to be unveiled, significant papers to be identified and current research trends to be revealed. In parallel, an existing Knowledge Base provides valuable data to be incorporated into the project’s developed models. Covering a wide range of aspects around CCAM, from key enabling technologies to legal documentation and general thematic categories, this resource will be appropriately modified to be ready for use by the project’s models. The ultimate goal is to fine tune the targeted extracted results to assist researchers in their work on CCAM.

References [1] [2] [3] [4]



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