Recording the location of people using location-acquisition technologies, such as GPS, allows generating life patterns, which associate people to places they frequently visit. Considering life patterns as edges that connect users of a social network to geographical entities on a spatial network, enriches the social network, providing an integrated sociospatial graph. Queries over such graph extract information on users, in correspondence with their location history, and extract information on geographical entities in correspondence with users who frequently visit these entities.In this paper we present the concept of a socio-spatial graph that is based on life patterns, where users are connected to geographical entities using life-pattern edges. We provide a set of operators that form a query language suitable for the integrated data. We consider two implementations of a socio-spatial graph storage-one implementation uses a relational database system as the underline data storage, and the other employs a graph database system. The two implementations are compared, experimentally, for various queries and data. An important contribution of this work is in illustrating the usefulness and the feasibility of maintaining and querying integrated socio-spatial graphs.

Cellular phones and GPS-based navigation systems allow recording the location history of users, to find places the users frequently visit and routes along which the users frequently travel. This provides associations between users and geographic entities. Considering these associations as edges that connect users of a social network to geographical entities on a spatial network yields an integrated socio-spatial network. Queries over a socio-spatial network glean information on users, in correspondence with their location history, and retrieve geographical entities in association with the users who frequently visit these entities.In this paper we present a graph model for socio-spatial networks that store information on frequently traveled routes. We present a query language that consists of graph traversal operations, aiming at facilitating the formulation of queries, and we show how queries over the network can be evaluated efficiently. We also show how social-based route recommendation can be implemented using our query language. We describe an implementation of the suggested model over a graph-based database system and provide an experimental evaluation, to illustrate the effectiveness of our model.

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Many devices, such as cellular smartphones and GPS-based navigation systems, allow users to record their location history. The location history data can be analyzed to generate life patterns-patterns that associate people to places they frequently visit. Accordingly, an SSN is a graph that consists of (1) a social network, (2) a spatial network, and (3) life patterns that connect the users of the social network to locations, i.e., to geographical entities in the spatial network. In this paper we present a system that stores SNN in a graph-based database management system and provides a novel query language, namely SSNQL, for querying the integrated data. The system includes a Web-based graphical user interface that allows presenting the social network, presenting the spatial network and posing SSNQL queries over the integrated data. The user interface also depicts the structure of queries for the purpose of debugging and optimization. Our demonstration presents the management of the integrated data as an SSN and it illustrates the query evaluation process in SSNQL.