Our current society is marked by an increase in the use of sensors, from image sensors in photo and video cameras to sensors in text scanners, DNA scanners and networks such as LOFAR and medical phenomenological data.
These sensor networks generate a huge datastream that has to satisfy the informational needs of companies, social organizations and individual consumers.
This need for information has been supported for years by the exponentially growing Internet, where very large amounts of data are being made accessible.
Increasingly, the demand for information in an operational sense is focused on the question:
How can large amounts of sensor data be turned into meaningful, reliable information?
The next revolution that is expected is the linking of the Internet to the real world (“physical world”) by means of ever-present sensors:
the “Global Sensor Network”.
This will make the data of a large number of distributed sensors
become structurally and continually available.
This causes the information question to become even more challenging:
How can information be gained from large amounts of continually streaming data in large-scale, distributed sensor networks in a reproducible, scalable and reliable fashion?
