RICDaM (Recommending Interoperable and Consistent Data Models) is a framework that produces a ranked set of candidates to model an input dataset.
Those candidates are obtained from Content, Interoperability, and Consistency scores that exploit a background Knowledge Graph built from existing RDF datasets in the same or related domains.
More details in the following research paper:
D. Oliveira and M. d’Aquin, “RICDaM: Recommending Interoperable and Consistent Data Models,” in Proceedings of the ISWC 2020 Demos and Industry Tracks: From Novel Ideas to Industrial Practice co-located with 19th International Semantic Web Conference (ISWC 2020), 2020, vol. 2717, p. 5. [Online]. Available: http://ceur-ws.org/Vol-2721/paper535.pdf
This repository contains a demonstrator and example datasets.
To run the demonstrator using the ready-to-use Docker image:
docker run --rm -p 8050:8050 ghcr.io/danielapoliveira/ricdam:v1.0.0
Then, point your browser to http://localhost:8050/ricdam/.
To build a Docker image for the demonstrator:
docker buildx build -t ghcr.io/danielapoliveira/ricdam:v1.0.0 .
Note: Ready-to-use images are available in the GitHub Container Registry.