Calls > Research Track

Call for Research Track

Overview

The ADBIS series of conferences provides a forum for the dissemination of research accomplishments and promotes interaction and collaboration among the database, information systems, data science, artificial intelligence, and machine learning communities from Europe and the rest of the world. ADBIS conferences have provided an international platform for researchers and developers to present and discuss cutting-edge results on database theory, data management and information technologies, data engineering, analytics and visualization, and their advanced applications. ADBIS 2026 will consist of regular sessions with technical contributions reviewed and selected by an international program committee, as well as invited keynotes and tutorial talks presented by leading scientists.

Topics

We invite the submission of original research contributions addressing core data management tasks, as well as techniques and technologies in the following broad areas of data management:

Database Management Systems
Information Systems Architectures and Data Services
Management and Mining of Heterogeneous Data Types
Big Data Management and Analytics
Scalable Data Science
Responsible Data Science

A list of specific topics of interest is provided below, and is by no means exhaustive:

Availability, reliability, and scalability
Benchmarking and performance evaluation
Bias in big data and how to mitigate it
Big data storage, processing and transformation
Business process modelling and optimization
Cloud data management
Complex event processing and data streams
Concurrency control, recovery and transaction management
Crowdsourced and collaborative data management
Data economy, data markets
Data integration and heterogeneous data management
Data management and analytics for semantic web and social networks
Data mining and knowledge discovery
Data models and semantics
Data platforms for modern hardware, and modern hardware for data platforms
Data quality, curation, and provenance
Data sovereignty, privacy, security, and access control
Data system benchmarking, tuning, monitoring, and performance evaluation
Data warehousing, large-scale analytics, and ETL tools
Distributed and parallel data management, distributed ledgers, and blockchains
Explainable data-driven systems
FAIRness (Findability, Accessibility, Interoperability and Reusability) in data analytics
Graph data management
Green data management
Human-data interaction
Human-in-the-loop data processing
Information system architectures and networking
Knowledge graphs and knowledge management
Metadata management and standards
Middleware and workflow management
ML/AI for DB and DB for AI/ML
Natural language processing for databases
Query processing and optimization
Responsible data management and ethics
Scientific and statistical data management
Semi-structured data management
Sensor and mobile data management
Spatial, temporal, and geographic data management
Storage, indexing, and physical database design
Text data management and information retrieval
Visualization, exploration & analytics techniques for various data types; e.g., stream, spatial, unstructured
Uncertain, probabilistic, and approximate data management
Usability, automaticity, interpretability, and explainability of data systems

Important Dates

All deadlines are 11:59 PM AoE

Abstract submission deadline: April 14, 2026
Paper submission deadline: April 21, 2026
Notification of acceptance/shepherding: May 29, 2026
Camera-ready papers/end of shepherding: June 25, 2026

Paper Submission

ADBIS 2026 invites original papers (not submitted elsewhere in parallel) describing results that broadly belong to the aforementioned list of topics. Accepted full papers will be published in a Springer Lecture Notes in Computer Science (LNCS) volume and accepted short papers are published in Springer's Communications in Computer and Information Science (CCIS) series.

Full papers can be:

Regular research papers, reporting novel, solid research findings within the scope of the conference, typically but not exclusively found in proposing new models, querying or data handling methods, algorithms, data structures, and system architectures for the management of data.
Experimental re-evaluation papers, assessing previously published research results in terms of (i) performance evaluation for algorithms and systems, or, (ii) assessment of the application for methodologies, with the contribution of the paper being found (i) in the evaluation findings and (ii) in the discussion of strong and weak aspects of the algorithm/system/method being assessed.

Short papers can be:

Early findings/work-in-progress reports for prompt dissemination and discussion of early research results, that include early experimental findings and implementations, with an emphasis on (i) the description of the early findings, (ii) the possibilities they present, and, (iii) the difficulties being faced towards full fruition.
Vision papers, discussing possibilities and challenges in the exploration of radically new system architectures or methodologies for data management in important areas related to the scope of the conference, or areas that are currently considered outside the scope of the conference but hold the potential of becoming relevant.

Submission Guidelines

The page limits are as follows:

Full (research or experimental) papers: 16 LNCS style pages, including references
Short (early findings or visionary) papers: up to 10 LNCS style pages, including references

Papers should be submitted in PDF format using the CMT online submission system at: https://cmt3.research.microsoft.com/ADBIS2026

ADBIS uses single-blind reviewing, meaning authors should list their names and affiliations in their submissions.

Authors should consult Springer’s authors’ guidelines and use their proceedings templates, either for LaTeX or for Word, for the preparation of their papers. Springer encourages authors to include their ORCIDs in their papers. In addition, the corresponding author of each paper, acting on behalf of all of the authors of that paper, must complete and sign a Licence-to-Publish agreement. The corresponding author, who must match the corresponding author marked on the paper, must have the full right, power, and authority to sign the agreement on behalf of all of the authors of a particular paper, and accepts responsibility for releasing this material on their behalf. Once the files have been sent to Springer, changes relating to the authorship of the papers cannot be made. An author of an accepted paper must register for ADBIS 2026 to have the paper published, and accepted papers must be presented at the conference by one of the authors.

Awards

Springer will sponsor the ADBIS 2026 Best Paper Award, Best Demonstration and Best Short Paper, which will be announced during the ADBIS 2026 Conference Dinner.

Special Issue

The best papers of the conference will be invited to submit an extended and revised version of their papers to a special issue of the Elsevier Information Systems journal (https://www.sciencedirect.com/journal/information-systems).

Inclusion and Diversity in Writing and Presentation

ADBIS 2026 continues to participate in the DB Diversity, Equity and Inclusion (DEI) initiative, which aims to guide researchers in our community to adopt a more inclusive mindset in general toward different individuals regardless of their age, gender, gender identity, race, cultural background, religion, physical and mental ability, sexual orientation, parental and marital status, etc.

Authors are strongly encouraged to be inclusive in the writing and presentation of their work.
Please visit the subsection "D&I materials" at https://dbdni.github.io/ for details.

Use of Generative AI

Authors should explicitly disclose the use of generative AI and AI-assisted technologies in their manuscripts when these tools are employed for more than just editing the author’s text. This disclosure can be made through a statement placed at the end of the manuscript, preceding the References section. If it comes to our notice that a submission utilized large language models (LLMs) without clear disclosure, such papers will be subject to immediate desk rejection.

Program Chairs

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