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Solving various issues surrounding AI and data

Unlike the use of external data in conventional analysis, the value of AI and machine learning differs greatly when external data changes its shape and persists as a learning result.

This consortium will tackle various issues surrounding AI, including annotations.

Data Collection and Utilization WG

In the use of data in AI (deep learning) and ML (machine learning), the path to finding the location and owner of the desired data and reaching a contract has become very long and tough. This is because the data provider has to confirm the commercial flow for each individual company and business case, negotiate the contract contents and price, etc., and the data owner who hesitates to provide data due to the complicated work and cost required not a few. On the other hand, there are not a few data owners who are unable to make public use of the data they have. The consortium provides the environment to connect among data holders, consumers and researchers for the open innovation.

In addition, there are various types of data such as (raw) data generated directly from devices such as sensors, cleansed data, and annotated data. Even with the same data, cleansing and annotation standards differ depending on the purpose of use.
The Data Collection and Utilization Working Group conducts activities that contribute to the promotion of data sharing and utilization by data owners, annotators, and data users.

Promote research and utilization by connecting stakeholders

Provide networking and collaboration opportunities for data holders, AI researchers, solution vendors and other data consumers, and contribute to the creation of new businesses.

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