Affiliation:
1. Lyon 1 University and CNRS Liris
Abstract
While schema mapping specification is a cumbersome task for data curation specialists, it becomes unfeasible for non-expert users, who are unacquainted with the semantics and languages of the involved transformations.
In this article, we present an interactive framework for schema mapping specification suited for non-expert users. The underlying key intuition is to leverage a few exemplar tuples to infer the underlying mappings and iterate the inference process via simple user interactions under the form of Boolean queries on the validity of the initial exemplar tuples. The approaches available so far are mainly assuming pairs of complete universal data examples, which can be solely provided by data curation experts, or are limited to poorly expressive mappings.
We present a quasi-lattice-based exploration of the space of all possible mappings that satisfy arbitrary user exemplar tuples. Along the exploration, we challenge the user to retain the mappings that fit the user’s requirements at best and to dynamically prune the exploration space, thus reducing the number of user interactions. We prove that after the refinement process, the obtained mappings are correct and complete. We present an extensive experimental analysis devoted to measure the feasibility of our interactive mapping strategies and the inherent quality of the obtained mappings.
Publisher
Association for Computing Machinery (ACM)
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. GXJoin: Generalized Cell Transformations for Explainable Joinability;Lecture Notes in Computer Science;2024
2. Ver: View Discovery in the Wild;2023 IEEE 39th International Conference on Data Engineering (ICDE);2023-04
3. Efficiently Transforming Tables for Joinability;2022 IEEE 38th International Conference on Data Engineering (ICDE);2022-05
4. Schema Mapping;Encyclopedia of Big Data Technologies;2022
5. Scalable and Usable Relational Learning With Automatic Language Bias;Proceedings of the 2021 International Conference on Management of Data;2021-06-09