Tabular data in the form of CSV files is the common input format in a data analytics pipeline. However a lack of understanding of the semantic structure and meaning of the content may hinder the data analytics process. Thus gaining this semantic understanding will be very valuable for data integration, data cleaning, data mining, machine learning and knowledge discovery tasks. For example, understanding what the data is can help assess what sorts of transformation are appropriate on the data.
Tables on the Web may also be the source of highly valuable data. The addition of semantic information to Web tables may enhance a wide range of applications, such as web search, question answering, and knowledge base (KB) construction.
Tabular data to Knowledge Graph (KG) matching is the process of assigning semantic tags from Knowledge Graphs (e.g., Wikidata or DBpedia) to the elements of the table. This task however is often difficult in practice due to metadata (e.g., table and column names) being missing, incomplete or ambiguous.
This challenge aims at benchmarking systems dealing with the tabular data to KG matching problem, so as to facilitate their comparison on the same basis and the reproducibility of the results.
The 2019 edition of this challenge will be collocated with the 18th International Semantic Web Conference and the 14th International Workshop on Ontology Matching.
The challenge includes the following tasks organised into several evaluation rounds:
The challenge will be run with the support of the AICrowd platform.
Ontology alignment and link discovery systems are welcome to participate. We plan to create input data in OWL/RDF format to facilitate their participation.
There will be prizes sponsored by SIRIUS and IBM Research for the best systems and the best student systems in the challenge.
The prize winners will be announced during the ISWC conference (on October 30, 2019).
We will take into account all evaluation rounds specially the one running till the conference dates, the covered tasks and the novelty of the applied techniques (we encourage the submission of a system paper).
We encourage participants to submit a system paper. The paper should be no more than 8 pages long and formatted using the LNCS Style. These papers are not peer-reviewed, but they will revised by 1-2 challenge organisers. Please use this form for the submission (requires a google account and a valid email).
To ensure easy comparability among the participants we suggest the following outline:
This track is organised by Kavitha Srinivas (IBM Research), Ernesto Jimenez-Ruiz (Alan Turing Institute; University of Oslo), Oktie Hassanzadeh (IBM Research) and Jiaoyan Chen (University of Oxford). If you have any problems working with the datasets or any suggestions related to this challenge, do not hesitate to contact us.
The challenge is currently supported by the AIDA project, the SIRIUS Centre for Research-driven Innovation, and IBM Research.