Evaluating Utility of Joining Datasets using Visual Analytics

What is it about?

Open datasets play a crucial role in today's world as it is quite vital for informed decision-making. However, finding joinable open datasets across multiple open data sources and computing their utility remains an open challenge. In order to address this, we have developed a utility metric that can calculate the usefulness of open datasets when joined with other such datasets. This metric is further used in a framework called VALUE, which the users can leverage to discover joinable datasets, rank them based on their usefulness, and finally analyze the joined data. By adopting this transparent approach, users can fine-tune the criteria for combining datasets according to their own understanding, ensuring informed decision-making and practical applications in real-world scenarios.

Featured Image

Photo by John Schnobrich on Unsplash

Photo by John Schnobrich on Unsplash

Why is it important?

This paper is important because it addresses a critical challenge in the linked data community: how to evaluate the utility of linked open data. This visual analytics based approach provides a practical way to address this challenge, and it has the potential to help users make better and more informed decisions.