HDMS 2025

The Microsoft CMT Service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.

We invite submissions to the following three tracks:
(A) Research/Industry/Data-Science/Application/Exper-Analysis/Tutorial/Journal
(B) Research Posters and Demos
(C) Student Posters (unpublished work by undergraduate/postgraduate students)

Specifically:

(A) Research/Industry/Data-Science/Application/Exper-Analysis/Tutorial/Journal:

Submissions recently accepted at top DM international conferences or journals are automatically accepted (any track of these conferences). Examples include but are not limited to SIGMOD, VLDB, PODS, ICDE, EDBT, ICDT, CIKM, SIGIR, KDD, WWW, MDM, SoCC, DEBS, MLSys, associated workshops, and associated journals.
Each submission must include the DOI link of the published paper. Original submissions that have not been previously published must be uploaded to arXiv.org or a similar DOI-registered repository. This is important as HDMS has no proceedings and this is the only way for authors to timestamp/protect their work before presenting it at HDMS.
Authors can use the original format and original length for submissions that have undergone peer review at any top event. Work that has not undergone peer review is limited to 12 pages in ACM double column format. Submissions that have not appeared at top events or have not undergone peer review (e.g., arxiv.org or similar papers), will be reviewed by the PC.
Any submitted paper (peer reviewed or not) might be accepted for full, short, or poster presentation, based on program time constraints.
Papers in this category should be submitted to the "Research/Industry/Data-Science/Application/Exper-Analysis/ Tutorial/Journal" track on CMT.

(B) Research Posters and Demos:

Research Poster & Demo submissions recently accepted at top international conferences are automatically accepted (any track of these conferences). Examples include but are not limited to SIGMOD, VLDB, PODS, ICDE, EDBT, ICDT, CIKM, SIGIR, KDD, WWW, MDM, SoCC, DEBS, MLSys, and associated workshops.
Authors can use the original format and original length for submissions that have undergone peer review at any top event. Work that has not undergone peer review is limited to 2 pages and 4 pages in ACM double column format, for Demos and Posters respectively. Submissions that have not appeared at top events or have not undergone peer review (e.g., arxiv.org or similar papers), will be reviewed by the PC.
Both Posters and Demos will be presented at the symposium during a designated session named "Lightning Talks". Both will also receive a separate slot in the program for a more extensive presentation using an Easel (for posters) and Table/Easel (for demos).
Papers in this category should be submitted to the "Research Posters and Demos" track on CMT.

Student Poster submissions by undergraduate and postgraduate that have worked on some research project or other research activity related to any area of data management are invited to submit a short abstract (up to 1 page in WORD format). More details will be posted on the HDMS website shortly.
These submissions refer to unpublished work. In case a submission refers to peer review published work, the student should submit the contribution to category (B).
Student Posters will be presented using an Easel during the poster session.
Papers in this category should be submitted to the "Student Posters" track on CMT.

Core database technologies (e.g., query processing and optimization, storage and indexing, database concurrency control, OLTP and OLAP processing).

Non-traditional data management architectures (e.g., data stream management, cloud data management, peer-to-peer systems, mobile data management, blockchain databases).

Data management applications (e.g., geographical information systems, data warehouses, social networks, scientific databases, IoT, crowdsourcing).

Models and languages for the management of data (e.g., XML, RDF, probabilistic databases, meta-data management, multi-media, graph data management).

Techniques for high performance and scalability in the management of data (e.g., distributed data processing, hardware accelerators, new hardware technologies).

Confluence of data management with: information retrieval, knowledge management, natural language processing, and data mining.

Databases and AI (e.g., vector databases, LLMs, RAG).

Other aspects of modern information systems (e.g., security, privacy, user interfaces, energy use minimization).

TOPICS

IMPORTANT DATES

ORGANIZING COMMITTEE

General Co-chairs:

Program Co-Chairs:

Demo & Poster Chairs:

DBHELLAS

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