On 1st of October, the EIT ICT Labs in Berlin hosted the first ever Software Campus Summit. 30 participants of the Software Campus program presented their project results to representatives from the BMBF, the DLR, and other industry partners.
Here, I introduced the Context Data Cloud as a service enabler platform hosted by mobile network operators for providing innovative context-aware services based on mobile network data. I demonstrated the Location Analytics Map and discussed our novel Semantic Positioning that overcomes the limitations of classic geofencing methods and adds semantic features to proactive self-referencing and cross-referencing LBS. In addition, I showcased the applicability of our approach with the Friend Tracker service of the CDCApp. Please have a look:
Geospatial data that is published within the LOD Cloud (e.g., LinkedGeoData) mostly consists of static information, such as a name, geo coordinates, an address, or opening hours. Enriching this data with location-specific crowdsourced information (e.g., checkins, ratings, or comments) as well as the contextual situation in which users visited a place (e.g., time of the day, weather condition, dwell time, or holiday) and interlinking this information with other datasets will enable location analytics scenarios within the LOD Cloud.
Linked Crowdsourced Data is - as the name implies - a crowdsourced dataset for real user location preferences. People using the CDCApp contribute to this dataset by checking into different locations. This information is accompanied by contextual information, such as the weather condition during the check-in, the WiFi access points that were measured in this area or whether the check-in occured during a regional holiday.
The Context Data Cloud for Android (CDCApp) is a location-based community app offering a set of semantic services to users such as a Friend Tracker or a Popular Places Finder. Users can check-in to certain points of interest in their vicinity providing information about their favorite or frequently visited locations to other users within their social community. These services are based on the Context Data Cloud platform and exploit the rich set of data available within the LOD Cloud.
Please do not hesitate to download the app at the Google Play Store!
This app collects personal location preference data (e.g., favorite or frequently visited locations) in combination with the current contextual situation (e.g., the weather when checking in to a point of interest). A totally anonymized and aggregated version of this dataset is published in Linked Data format as Linked Crowdsourced Data and is interlinked to other datasets within the LOD Cloud.
By contributing with your data, you enable us to create this valuable dataset of real user location preferences to be used within our research at Technische Universität Berlin in the areas of Semantically enriched Context-aware Services and Location Analytics.