ISSN: 2308-4332
ISBN: 978-1-68558-244-9

• Registered: with the Library of Congress of the United States of America (ISSN)
• Free Access: in ThinkMind Digital Library

DBKDA 2025 is colocated with the following events as part of InfoSys 2025 Congress:

• ICNS 2025, The Twenty-First International Conference on Networking and Services
• ICAS 2025, The Twenty-First International Conference on Autonomic and Autonomous Systems
• ENERGY 2025, The Fifteenth International Conference on Smart Grids, Green Communications and IT Energy-aware Technologies
• WEB 2025, The Thirteenth International Conference on Building and Exploring Web Based Environments
• DBKDA 2025, The Seventeenth International Conference on Advances in Databases, Knowledge, and Data Applications
• SIGNAL 2025, The Tenth International Conference on Advances in Signal, Image and Video Processing
• BIOTECHNO 2025, The Seventeenth International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies
• AIHealth 2025, The Second International Conference on AI-Health

DBKDA 2025 Steering Committee

		Friedrich Laux Reutlingen University Germany			Lisa Ehrlinger Software Competence Center Hagenberg GmbH Austria
		Andreas Schmidt Karlsruhe Institute of Technology / University of Applied Sciences Germany			Peter Kieseberg St. Pölten University of Applied Sciences Austria
		Erik Hoel Esri USA			Constantine Kotropoulos Aristotle University of Thessaloniki Greece

DBKDA 2025 conference tracks:

Advances in fundamentals on databases

Foundations and architectures; Design features (data quality, performance, robustness, scalability, security, privacy, parallel and distributed approaches, mobility, etc.); Data quality, data structures, and data modeling; Advanced indexing methods; Advanced ranking algorithms and uncertainty; Physical organization and performance; Federated choreographies; Temporal conformance; Evolutionary clustering and dynamic hierarchical clustering

Knowledge Discovery and Machine Learning

Knowledge extraction via machine learning; Machine learning for datasets; Machine learning and graphs; Graphs analytics and deep learning; Machine learning models (supervised, unsupervised, reinforcement, constrained, etc.); Generative modeling (Gaussian, HMM, GAN, Bayesian networks, autoencoders, etc.); Bayesian learning models; Prediction uncertainty; Training of models (hyperparameter optimization, regularization, optimizers); Active learning (partially labels datasets, faulty labels, semi-supervised); Applications of machine learning (recommender systems, NLP, computer vision, etc.); Data in machine learning (no data, small data, big data, graph data, time series, sparse data, etc.).

NoSQL Databases

Key-value stores; Document stores; Wide-column stores; Graph databases; Spatial databases; Time-series databases; RDF stores; Hybrid DB management systems

Current ongoing researches

DBaaS Storage; Preference-driven databases; Personalized ranking models; Visual query systems; Reverse rank queries; Searching on process description graphs; Search over relational data streams; Linked data streams; Nearby coalescing; Automatic labelling; Personalized query expansion; Benchmarking replication; Community detection; Risk-adaptive security model; Faceted queries over ontologies; Inclusion dependencies; Periodic-frequent patterns; Dynamic query reordering; Queries for linked data; Footprint reduction; Multi-dimensional indexing; Set similarity join algorithms; Incremental continuous query processing; Linkset views; High-utility itemsets; Reputation estimation; Quality prediction; Approximate query answering; Hidden semantic data models; Temporal extractions; Target-oriented keyword search; Filter-based profile matching; Mutual information on data streams; Stream processing; Digitized documents streams; Queries with binary constraints; Propagation granularity; Processing over raw data; Lossy transformations; Queries on massive time series; Generalized indexing; Answering batch queries; Database task schedulers; Similarity search; Fuzzy object databases; Automated prediction of relationships; Linked data streams and Internet of things; Preferred repairs; Parallel-correctness and transferability; Guarded existential rules; Tree pattern containment; Large datasets; Accessing small data; Skyline queries; Distributed set-joins; Stream sampling; Dynamic graph streams; Dynamic data structures; Nearest neighbor search; Data lakes, Knowledge lakes

Databases and other domains

Leading-edge database technology and applications; Heterogeneous databases interoperability and mediation; Databases and Web services; Databases and artificial intelligence; Databases and agents; Advances in database management systems; Advanced transaction and workflow management; Advances on XML and databases

Databases technologies

Self-managing databases; Mobile databases; Database access; Embedded databases; Very large scale databases; Spatial and spatio-temporal databases; Data warehousing; Multimedia databases; Semantic databases; Data integration resources on the Internet; Object-oriented databases; Web-based databases; Deductive and active databases

Databases content processing

Contextual aggregated information retrieval; Aggregated query for workflows; Mining for complex data; Mining for text, video, and pictures; Knowledge discovery and classification; Process mining; Scalable data extraction; Query processing and optimization; Query rewrite rules; Navigational path expressions; Load-balancing in accessing distributed databases; Incompleteness, inconsistency, uncertainty; Storage and replication; Patterns and similarities in data streams; Fast matching; Multiple views

Knowledge and decision bases

Knowledge representation and management; Knowledge discovery (business intelligence); Semantic information; Ontology and advanced knowledge search; Heuristics and meta-heuristics; Intelligent knowledge querying; Feature sampling and feature selection; Context-aware knowledge base; Blogs and social relationship search; Deductive reasoning; Reasoning databases; Ontology-based reasoning; Knowledge graphs

Specifics on application domains databases

Database applications in Life Sciences; Advanced database applications; Bioinformatics databases; Healthcare databases; Finance and marketing databases; Telecom databases; Geospatial databases; Census databases; Meteorological databases; Business intelligence databases; e-Business databases

XML-driven data, knowledge, databases

Data /dissemination, distributed, processing, management/; XML-data /storage, exchange, compress, metadata/; XML-data and metadata management; XML repositories; Knowledge discovery from XML repositories; XML-data processing /queries, indexing, management, retrieval, mining/; XML data and knowledge /representation, discovery, mining, orchestration/; XML-data in advances environments /clouds, P2P, multimedia, mobile, finance, biotechnologies, geospatial, space/; XML-data and process /data warehouse, workflow, web, learning, control/;

Data privacy

Privacy models; Privacy metrics; Privacy preservation; Watermarking; Data Hiding; Background knowledge; Privacy /data streams, social networks, databases, semantic web/; Privacy mechanisms /cryptography, privacy-aware access control, generalization-based algoritm, perturbation-based algorithm, preservation, sequental releases/; Practical studies /privacy leaking, privacy breach, threats to privacy, privacy in outsourcing/

Data quality and uncertainty

Models, frameworks, methodologies and metrics for data quality; Quality of complex data /documents, semi-structured data, XMLs, multimedia data, graphs, bio-sequences/; Uncertain and noisy data; Uncertain data representation; Processing uncertain data /querying, indexing, mining/; Mining uncertain data/probabilistic, spatially- and temporally- uncertain, uncertain streams/ Data lineage and provenance; Data profiling and measurement; Data integration, linkage and fusion; D uplicate detection and consistency checking; D ata mining and data quality assessment; Quality methods and algorithms / data transformation, reconciliation, consolidation, extraction, cleansing/; User perception on data quality and cleansing;

Data query, access, mining, and correlation

Data access technologies, Query optimisation, Discovering multi-modal correlations; Mining structural data from non-structural mixed-media documents; Data stream mining /frequent patterns, bursty event detection/; Profile mining; Corelation and anomaly in multi-modal-data /social networks, web traffic logs, sale transactions/; Information retrieval on a mixed collections; Multimedia data mining; Data mining system for medical multimedia data; Contents-based image/video retrieval systems

Data and process provenance

Provenance architectures and algorithms; Provenance modelling; Information management for provenance data; Provenance ontology and semantic; Provenance querying; Provenance annotation; Security, trust, and privacy for provenance information; Case studies and practice; Reasoning over provenance; Provenance analytics, mining and visualization

Data management

Distributed Query Languages; Query processing and optimization; Adaptive query processing; Management of mobile data; Managing data privacy and security; Data storage and management; Data stream systems; Data locating; Data warehouse management; Management of dynamic data; Workload adaptability; Transaction management; Performance evaluation and benchmarking or data management

Deadlines:

Deadlines differ for special tracks. Please consult the conference home page for special tracks Call for Papers (if any).