Position Paper: Dataset profling for un-Linked Data

The vast amount of data on the web presents a growing need to advance data search. Rich and meaningful metadata can enhance the discovery of datasets and establish connections between them. Where metadata is not comprehensive, it can be expanded through dataset profiling. The relative importance of different types of profiles varies depending on the user’s context and the objective of the task. We discuss an approach to find un-Linked datasets and increase result relevance by offering related information. We propose generating rich profiles for datasets; counting the number and strength of relations between them and showing a graph of profiles that represents connections between different datasets. We can thereby capture correlations between datasets that can then improve the efficiency and effectiveness of data search. If developed further this would improve discoverability and reusability of datasets.