Description
New dataset contributions
The data that table-to-Knowledge-Graph matching systems are trained and evaluated on, is critical for their accuracy and relevance. We invite dataset submissions that provide challenging and accessible new datasets to advance the state-of-the-art of table-to-KG matching systems.
Preferably, these datasets provide tables along with their ground truth annotations for at least one of CEA, CTA and CPA tasks. The dataset may be general or specific to a certain domain.
Submissions will be evaluated according to provide the following:
- Description of the data collection, curation, and annotation processes
- Availability of documentation with insights in the dataset content
- Publicly accessible link to the dataset (e.g., Zenodo) and its DOI
- Explanation of maintenance and long-term availability
- Clear description of the envisioned use-cases
- Application in which the dataset is used to solve an exemplar task
Dataset revision contributions
Besides entirely new datasets, we also encourage revisions of existing datasets and their annotations. Revisions can be of any kind as below, but we welcome alternative revisions:
- Revisited annotations with improved quality
- Revisited data with improved quality
- New annotations for an existing dataset enabling new tasks on it
Please clearly describe and illustrate what the problem is that the revision addresses, and how the adopted approach yields a high quality dataset for downstream applications. Dataset and annotation revisions are expected to be made public with a permissive license for wider use in the community.