inContext-Sensing

inContextSensing is a web application that shows how

users with no expertise can benefit of a Linked Data representation to make sense of raw sensor data. Our motivations

are that

1. these users are becoming the main consumers of sensor data,

   but sensors conceptualisation do not consider their point of view;

2. so far, no application dynamically creates Linked Data for sensors, since the linked datasets are usually predefined.

A DEMO paper has been published about this at the International Semantic Web Conference 2011 (ISWC2011):

inContext Sensing: LOD augmented sensor data

Contacts:

• Myriam Leggieri,
• Alexandre Passant,
• Manfred Hauswirth.
• Michael Hausenblas.