32nd IEEE International Conference on Data Engineering

May 16-20, 2016 · Helsinki, Finland

It is with great pleasure that the organizers of the 32nd IEEE International Conference on Data Engineering invite you to take part in ICDE 2016 to be held in Helsinki, Finland, from May 16 to 20, 2016. As the capital of Finland, Helsinki is a vibrant city on the Baltic Sea renowned for its design and friendly atmosphere. The venue is at Aalto University's School of Business, which is located right in the city center.
  • Helsinki_City
  • Finlandia_Hall
  • Venue
Photos now available in Photo Gallery under 'General Information'.

Conference Overview

The annual ICDE conference addresses research issues in designing, building, managing, and evaluating advanced data systems and applications. It is a leading forum for researchers, practitioners, developers, and users to explore cutting-edge ideas and to exchange techniques, tools, and experiences.

The 32nd IEEE ICDE will be held in Helsinki, Finland, May 16-20, 2016. Due to its numerous contributions to the areas of software engineering, mobile communications and computing, databases, and data mining, Finland is the perfect venue for addressing emerging database issues such as post-disk database architectures, Internet-of-Things support, and vertical applications.

Areas of Interest

We invite the submission of papers in the following areas but at the same time we welcome any original contributions that may cross the boundaries among areas or point in other novel directions:
  • Cloud Computing and Database-as-a-Service
  • Big Data and Data-Warehousing System Architectures
  • Data Integration, Metadata Management, and Interoperability
  • Modern Hardware and In-Memory Database Architecture and Systems
  • Privacy, Security, and Trust
  • Query Processing, Indexing, and Optimization
  • Social Networks, Social Web, Graph, and Personal Information Management
  • Crowdsourcing, Distributed, and P2P Data Management
  • Streams and Sensor Networks
  • High Performance Transaction Management
  • Temporal, Spatial, Mobile, and Multimedia Data
  • Strings, Texts, and Keyword Search
  • Semi-structured, Web, and Linked Data Management
  • Uncertain and Probabilistic Data
  • Visual Data Analytics, Data Mining, and Knowledge Discovery