Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and agent technologies, as well as from the generalization of the XML adoption.

High-speed communications and computations, large storage capacities, and load-balancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods.

Evolution on e-business, ehealth and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the ‘de facto’ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology.

The Fifteenth International Conference on Advances in Databases, Knowledge, and Data Applications, DBKDA 2023, continues a series of international events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base technologies and content processing, as well as specifics in applications domains databases.

We solicit both academic, research, and industrial contributions. We welcome technical papers presenting research and practical results, position papers addressing the pros and cons of specific proposals, such as those being discussed in the standard fora or in industry consortia, survey papers addressing the key problems and solutions on any of the above topics short papers on work in progress, and panel proposals.

Industrial presentations are not subject to the format and content constraints of regular submissions. We expect short and long presentations that express industrial position and status.

Tutorials on specific related topics and panels on challenging areas are encouraged.

The topics suggested by the conference can be discussed in term of concepts, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas.

All topics and submission formats are open to both research and industry contributions.

DBKDA 2023 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