2nd International Workshop on Data Science for Internet of Things

The 2nd International Workshop on Data Science for Internet of Thinkgs will take place in Orlando, USA, on October 22nd. Check all details on content and paper submission at . The workshop is sponsored by Semantix and the María de Maeztu Strategic Research Program, in the context of the project Wireless Networking through Learning: Searching for Optimality in Highly-dynamic and Decentralized scenarios (Boris Bellalta, Wireless Networking Research Group & Anders Jonsson, Artificial Intelligence and Machine Learning Research Group). You can learn about the 1st edition in 2016 here.

Selected information:

Data science is an interdisciplinary field that involves techniques to acquire, store, analyze, manage and publish data. For example, data can be analyzed using machine learning, data analysis and statistics, optimizing processes and maximizing their power in larger scenarios.

In the Internet of Things (IoT), smartphones and household appliances can easily become sensor nodes and compose sensor networks, measuring environmental parameters and generating user interaction data. As sensor networks are mainly data-oriented networks, i.e., sensed data is their most valuable asset and the reason for the operation of the whole network, data science techniques have been adopted to improve the IoT in terms of data throughput, self-optimization and self-management. In fact, incorporating the lifecycle proposed by the data scientists will impact the future of the IoT, allowing researchers to reproduce scenarios, and optimize the acquisition, analysis and visualization of the data acquired by IoT devices.

This workshop will address techniques used for data management planning into IoT scenarios in order to optimize data acquisition, management and later discovery.


Data collection

  • Prediction-based data reduction in the IoT
  • Data-based sensor failure techniques
  • Data-based error detection techniques

Data analysis

  • Methods for assessing IoT data quality
  • Strategies for IoT data visualization

Data management solutions

  • Standards for IoT data discovery
  • IoT data publication
  • Integrating IoT data with external data sources
  • Privacy and security in the IoT data sharing

Reproducibility of IoT scenarios

  • Long-lived IoT data storage
  • IoT data integrity standards
  • IoT data discovery standards
  • IoT data description (metadata)
  • Data-centric simulations of the IoT
  • Tests reproducibility for IoT scenarios

Autonomous IoT

  • Autonomic architectures for IoT
  • IoT-optimization using external information
  • Management of IoT devices based on data knowledge

Data management planning use cases

  • Data science in smart cities
  • Data science in smart environments
  • Data science for wearable devices

Important dates

Paper submission: 5 July 2017

Acceptance Notification: 26 July 2017

Camera Ready Submission: 2 August 2017

Workshop: 22 October 2017

General Chairs