Distributed And Parallel Databases

Distributed and Parallel Databases publishes papers in all the traditional as well as most emerging areas of database research, including:

Availability and reliability;

Benchmarking and performance evaluation, and tuning;

Big Data Storage and Processing;

Cloud Computing and Database-as-a-Service;

Crowdsourcing;

Data curation, annotation and provenance;

Data integration, metadata Management, and interoperability;

Data models, semantics, query languages;

Data mining and knowledge discovery;

Data privacy, security, trust;

Data provenance, workflows, Scientific Data Management;

Data visualization and interactive data exploration;

Data warehousing, OLAP, Analytics;

Graph data management, RDF, social networks;

Information Extraction and Data Cleaning;

Middleware and Workflow Management;

Modern Hardware and In-Memory Database Systems;

Query Processing and Optimization;

Semantic Web and open data;

Social Networks;

Storage, indexing, and physical database design;

Streams, sensor networks, and complex event processing;

Strings, Texts, and Keyword Search;

Spatial, temporal, and spatio-temporal databases;

Transaction processing;

Uncertain, probabilistic, and approximate databases.