Semantic Data Integration 2026

8th International Workshop on
​Semantic Data Integration (SDI ’26)

in conjunction with
The 20th IEEE International Conference on Semantic Computing (ICSC 2026)

Feb 2 – Feb 4, 2026
Laguna Hills, California
Format: Hybrid event

CALL FOR PAPERS

There has been an exponential growth and availability of data, both structured and unstructured. Massive amounts of data are available to be harvested for competitive business advantage, government policies, and new insights into a broad array of applications (including healthcare, biomedicine, energy, smart cities, genomics, transportation, etc.). Yet, most of this data is inaccessible to users, as we need technology and tools to find, transform, analyze, and visualize data in order to make it consumable for decision-making. Meaningful data integration in a schema-less and complex Big Data world of databases on the web is a big open challenge. Semantic computing is being used in the area of data integration for the creation of Open Knowledge Networks and Knowledge Discovery. The Linked Open Data (LOD) community effort is an initiative that has led to a huge data space in the form of triples. Linked data is the method of connecting and publishing related structured data on the web. LOD can be used in several interesting and useful Web and mobile applications. The focus of this workshop is on recent advances in Semantic computing approaches for data integration, knowledge engineering with big data, the construction of knowledge graphs, large language models, and graph retrieval augmented generation.

Topics of Interest

The topics of interest within the context of this workshop include Semantic computing approaches for data extraction, integration, cleaning, and quality, but are not limited to:

  • Schema-based data integration
  • Schema matching
  • Traditional Extract-Transform-Load (ETL) frameworks
  • Ontology-based integration systems,
  • Graph-based algorithms for data integration
  • Knowledge Engineering with Big Data
  • Knowledge Graph Construction
  • Large Language Models and Graph Retrieval Augmented Generation
  • Real-time integration
  • Schema-less approaches, such as NoSQL, for data integration
  • Data quality challenges such as cleaning, record linkage, de-duplication, provenance, and auditing
  • Social event detection using Linked Data
  • Ontology Alignment/Matching
  • Multilinguality using Linked Data
  • Entity extraction, Information extraction
  • Recommendation systems based on linked data
  • Question Answering using Linked Data
  • Application-specific integration and data quality

Important Dates

Submission deadline:   December 15, 2025
Camera-Ready Submission & Registration:   December 31, 2025
Workshop Date:  Feb 4, 2026

(all deadlines are at 11:59 pm U.S. Pacific time)

Workshop Program

TBA

Organizing Committee

  • Srividya Bansal, School of Computing and Augmented Intelligence, Arizona State University, Mesa, AZ (email: [email protected])
  • Ajay Bansal, School of Computing and Augmented Intelligence, Arizona State University, Mesa, AZ (email: [email protected])
  • Jaydeep Chakraborty, Walmart Labs (email: [email protected])
  • Amar Yadav, School of Computing and Augmented Intelligence, Arizona State University, Mesa, AZ (email: [email protected])

    Submission

    Authors are invited to submit a paper up to 6 pages (in English) in double-column IEEE format following the submission guidelines available at the ICSC 2026 web page (https://www.ieee-icsc.org/submission). 

    Papers must be original and not be submitted to or accepted by any other conference or journal. An electronic version (PDF format) of the full paper should be submitted by the deadline. All papers should be submitted through Easychair (choose Track: Semantic Data Integration)
    ​
    Each paper will be peer-reviewed by at least two experts in the topical area. Papers accepted by the workshop will be published in the conference proceedings published by the IEEE Computer Society Press.

    For any questions regarding the workshop, please contact Srividya Bansal at [email protected].