Crowdsourced context-modeling as key to future smart spaces

Managing smart spaces with software requires the acquisition and processing of context information about a space. To be usable for exchanging information, a context representation has to be structured with a context model. Existing context-modeling techniques usually require experts and lack support for collaborative distributed creation, which prevents a crowdsourced development in a distributed collaborative way by non-experts. To facilitate context modeling, this paper presents a hybrid meta model that combines features from key-value, markup, object oriented, and ontology based context-modeling approaches. An architecture is introduced that allows the dynamic collaborative extension and crowdsourced convergence of context models.