Position Paper: Dataset profiling for un-Linked Data
he 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 de-pending on the user's context and the objective of the task. We discuss an approach to and 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 effciency and effectiveness of data search. If developed further this would improve discoverability and reusability of datasets.
Top- Kacprzak, Emilia
- Koesten, Laura
- Heath, Tom
- Tennison, Jeni
Category |
Paper in Conference Proceedings or in Workshop Proceedings (Paper) |
Event Title |
3rd International Workshop on Dataset PROFIling and fEderated Search for Linked Data, PROFILES 2016 |
Divisions |
Visualization and Data Analysis |
Subjects |
Informatik in Beziehung zu Mensch und Gesellschaft |
Event Location |
Anissaras, Greece |
Event Type |
Workshop |
Event Dates |
30 May 2016 |
Date |
30 May 2016 |
Export |