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.