Estimating Metadata of Research Artifacts to Enhance their Findability

To accelerate open science, it is encouraged to publish and share research artifacts, e.g., scholarly papers, datasets, and code, with their metadata. Although the metadata facilitates the discovery of research artifacts, the metadata is not always complete. In this study, we verify the feasibility of estimating metadata that has not yet been filled (unfilled metadata) using metadata that has been filled (filled-in metadata) for realizing automatic completion of metadata. We implement an estimation method and evaluate its performance through experiments. The method takes filled-in metadata expressed in text as input and estimates unfilled metadata using a BERT-based model. In our experiments, the filled-in metadata was set as the name of the research artifacts, and the unfilled metadata was set as their type. Experimental results showed a high estimation performance.