Introduction

This is a semi-automatic semantic consistency-checking method for learning ontology from RDB, in which the graph-based intermediate model is leveraged to represent the semantics of RDB and the specifications of learned ontologies.

• The graph-based intermediate model is encoded by SMV program.
• The specifications of learned ontologies is formalized by CTL formula.

This code could be ran nuXmv by using model chcker to verify whether the learned ontolgies satisfy the RDB model by excuting the following commands:

1. read_model -i Mini_University.smv
2. flatten_hierarchy
3. encode_variables
4. build_model
5. check_fsm
6. check_ctlspec

Cite

@article{info12050188, author = {Ma, Chuangtao and Molnár, Bálint and Benczúr, András}, title = {A Semi-Automatic Semantic Consistency-Checking Method for Learning Ontology from Relational Database}, journal = {Information}, volume = {12}, year = {2021}, number = {5}, article-number = {188}, issn = {2078-2489}, doi = {10.3390/info12050188} }