GALE: Global Accessibility to Local Experience

Recommender Systems have been generated in the past 15 years with the aim to suggest to individual users opportunities arising in the virtual space of the Internet on the basis of the individual profile of the user, her/his past history as a customer/web-user and even her/his friends' community in social networks. Further, the rise of online social networks such as Facebook has allowed for a new source of information to be exploited by recommendation systems: the user social network.
Internet access is now becoming increasingly mobile and smart phones are changing the way people interact with places and with each other in an increasingly complex manner. Smart phones are starting to impact the way users access information on the go and receive suggestions. More specifically, innovative recommender systems are currently being developed to exploit GPS-based or other location-sensitive information, associated on-the-go to individual users through smartphones. This second generation of recommender systems, by being location-based, pose an entirely different set of problems which not only have to do with the knowledge of the user (her or his "profile"), but also with that of the places. Knowledge of places can be achieved by means of guides, textbooks and journey reports, or by direct experience. These ways are quite different in nature. The former is globally accessible (everybody can get it from afar) and relatively fast to obtain, especially in the age of the Internet. The latter is only locally accessible (one needs to be in the place to access it) and, being generated by those living in the place through personal local interaction, it becomes accessible only after long-term interactions and the construction of personal relationship of mutual trust. When visiting a new place, you would necessarily rely only on global information to navigate the place and access its resources. Conversely, if you are a local, your knowledge of the place is mostly constructed through your personal long-term exchange with what all your neighbors are doing every day and with their favorite places in the neighborhood; as a result, you not only would rely on local knowledge, but you would also contribute - by interacting locally - to the formation and continuous re-shaping of the information used by your neighbors too in their interaction. If we name the long-term, locally generated knowledge of the place "neighborhood knowledge", we can say that what people locally do in places is in one way or another dependent on the extent to which they have access to the neighborhood knowledge.
The second generation of recommender systems allows "global" place-users, i.e. people visiting a place who are not experienced with the place itself, to access "globally" available information. However, a good deal of information is still not exploited in these systems, as the geographic and the social only "meet" in a superficial way: in other words, the system does not take advantage of any information about the particular use of the place that local "communities" have done in the past and do "at the moment".
As neighborhood knowledge information is now becoming increasingly available through the viral expansion of location-based social networks such as foursquare or Gowalla, it is now possible to explore a third generation of recommender systems, where knowledge about how the place had been used in the past (historical use) or is used at the moment of the inquiry (real-time use) by communities of users is the key element of the system. The main motivation behind the GALE project is to pioneer such third generation recommender systems which would make it possible for the rapidly growing population of "global" city users to access a level of information, that of the neighborhoods knowledge, which is inherently inaccessible to global repositories, and to do that in real time.

We will contribute to the knowledge about the use of spatial and temporal information in the context of recommendation systems. Our new generation of technological systems for recommendation will be unprecedented as informed by multiple disciplines: a theory of neighborhoods developed in urban design, and the complex systems background will make our approach unique. Most current recommendation methods are developed without this multi-disciplinary perspective and do not have strong theoretical foundations. In terms of urban planning, the ability to test theories related to fluid neighborhood in practice, and with a quantitative attention both to temporal and spatial perspective, as well as to the social aspects, is unprecedented. This is likely to substantially contribute to a much needed paradigm shift towards "a new urban planning agenda" as advocated by UN-Habitat, based on the governance of inner dynamics of change in the built environment as opposed to massive top-down approaches. In particular, that will be conducive to strengthening the compact/sustainable city model by means of new evidence of fundamental patterns in the spatial formation and functioning of local "smart" communities. In terms of complex networks, we will create knowledge in two of the hottest research topics in the fields, namely spatial networks, i.e. networks whose nodes and links are embedded in a geographical space, and temporal networks, i.e. networks where the links change over time.
The ability to improve the way in which we perceive our surroundings has a high impact on our life. GALE will develop systems that help users to discover and use neighborhoods consistently with their attitude and profile. Systems able to aid people in their everyday choices and movements have the potential to improve the user experience and the use of space. All of this will impact society: the way the system of public and private services are localized and accessed, the extent to which local community centers threatened by financial and locational challenges find new ways to reaffirm their strengths and strategic role in more sustainable, safe and adaptable urban quarters. In this sense, impact to industry that will be generated by the development of a third generation unprecedented and powerful recommendation tool will complement impact to urban communities centrality and regeneration in terms of planning strategies and visions, which will open new opportunities for both advanced IT research and innovative location-based markets. Overall, and in the longer term, impacts on society will result from the redefinition of the notion of neighborhood and applied research on transportation and identity as key-factors to shape urban public policy.
GALE's impact on the economy is well expressed in the kind of deployment and validation scheme proposed: here, GALE will test and validate its products and visions by means of a process involving UoS students in Glasgow which will be entirely conducted in the framework of a city-wide strategic effort of economic growth, led by the Glasgow Economic Leadership Board. The Board, which gathers the most important leaders of Glasgow's economic and industrial fabric and is currently engaged in the redefinition and implementation of strategies for the economic growth of the city, identified path to growth in several key sectors including HE students, which are seen as a crucial driver in that context.
Our direct link to IBM will allow our research to be transmitted and considered in commercial contexts: our recommendation product will be very unique given the variety of disciplines considered for the project.
The commercial exploitation potential of the recommendation product we are producing will also be made stronger by presence of the leader of the Intel Collaborative Research Institute on Sustainable Connected Cities (ISCCI) on our advisory board as we aim to reach to this consortium.