Early warning systems are becoming one of the main pillars of disaster prevention in natural hazards especially where mitigation strategies are not realizable. Therefore, the call for multi-hazard early warning systems and improvement of monitoring of natural hazards is steadily growing. However, data gathering (generation) through sensor integration as well as system independent supply of information from early warning networks are of particular challenge.Because very complex information and warning chains have to be served for, standardisation and interoperability plays an important role for all organisations and infrastructures being involved. The SLEWS project investigates the complete information chain, starting from data gathering using wireless sensor networks via information processing and analysis to information retrieval. This is demonstrated for landslides and mass movements. The proposed approach adds especially to the funding target of mobile, cost-reduced and easy deployable measurement systems, as well as the modern information systems under consideration of interoperability and service orientated architecture concepts. The proposed wireless network provides the basis for applying further techniques like sensor
fusion, identification of malfunctions or errors. The obtained geodata is processed according to the requirements of particular users and can be provided for use in a local or regional as well as global information structure. Interfaces will be created, which make a mobile and flexible adaptation or integration of geodata possible. Thus, it is ensured that the early warning system reaches the spectrum of potential users and provides a maximum flexibility.