Call for Papers

We solicit submissions in the following areas of data management. Submissions addressing foundational aspects and (short) papers illustrating applications of foundational results in real-world contexts are particularly welcome.

Topics

  • Approximate and probabilistic query answering
  • Data analytics
  • Data exchange and integration
  • Data exploration
  • Data mining
  • Data modelling
  • Data privacy, security, and blockchain
  • Data provenance
  • Data streams
  • Data visualization
  • Data warehousing
  • Database benchmarking
  • Database concurrency and transactions
  • Database storage and indexing
  • Distributed and parallel databases
  • Domain-specific databases
  • Ethics of data science
  • Graph data management
  • Incompleteness, inconsistency, and uncertainty in databases
  • Information extraction
  • Information retrieval
  • Knowledge representation
  • Logic and databases
  • Machine learning and databases
  • Model theory and databases
  • Physical design
  • Query languages
  • Query processing and optimization
  • Semantic Web
  • Social networks
  • Spatial/temporal data

Submissions

This year submissions are requested in the CEURART format since this is the camera-ready required format. However, submissions following the previous LNCS format will still be accepted.
At least one author of each accepted paper must attend the workshop to present the work.

We invite two types of submissions:

  • Short papers (up to 4 pages) containing original ongoing research or recently published results.
  • Extended abstracts (up to 10 pages) presenting original research.

Submissions should be written in English and formatted according to the single-column CEURART style. You can use the CEUR Overleaf template as reference.

Submissions must be uploaded in PDF format using the following link:
https://easychair.org/conferences/?conf=amw2024

Both extended abstracts and short papers will be published in the CEUR Workshop Proceedings.1


  1. The authors can opt-out if they wish. ↩︎