Since the beginning of the past week, we have been running a pilot experiment in a major Italian pediatric hospital, in a collaboration with the hospital and the ISS. The experiment involves patients, doctors, healthcare workers and visitors, simultaneously collecting contact information and clinical information. We aim at measuring epidemiologically relevant quantities in a real-world healthcare setting.
Archive for the ‘Our projects’ Category
First deployment in a healthcare setting
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Live Social Semantics
In moving from measuring social interactions to augmenting them, a critical task is the integration of heterogeneous data sources, such as real-world face-to-face contacts, on-line friendships and shared interests (both explicitly stated or implicitly inferred from metadata). This integration holds the key to exposing the social semantics of the measured interactions, and paves the door to new kinds of applications that assist social networking, support social browsing, and provide recomendation, and serendipitous discovery.
We believe that the best way to learn about the right research questions is to actually design and build a working system that can be deployed at real-life social gatherings. We partnered with the TAGora project, and specifically with the team of the University of Southampton (Harith Alani, Martin Szomszor and Gianluca Correndo) and designed the Live Social Semantics (LSS) experiment. The basic idea is to focus on a conference gathering and establish a contact between: A) the real-world identities and physical-space relations of conference attendees, B) their identities and relations in web-based systems for social networking and collaborative tagging, and C) their identities in semantic representation of knowledge that describe their interests and collaborations (paper co-authorship, for example). The SocioPatterns project provides the social sensing platform needed for A), while the TAGora project provided the profile-mining and semantic integration techniques required to collect, filter and represent B) and C). The movie below illustrates the experiment concept and the user-facing aspects of the system.
Attendees enroll in Live Social Semantics (LSS) by volunteering to wear a RFID-equipped badge that can detect face-fo-face proximity. This is the real-world part of the experiment. The real-world identity of an attendee is then associated with multiple on-line identities of her choice by creating a user profile in the LSS web interface. LSS currentlty supports Facebook, Flickr, Delicious, and Last.FM. Once a profile has been created, the system will gather data from these systems in the background, record on-line friendships and infer interests and shared interests. The system will also mine for co-membership in communities of practice (COP) using semantic web sources such as the RKBExplorer.
The data collected and integrated by LSS are stored as RDF relations in a triple store, and fed back to the conference attendees in a number of ways. There are public real-time visualizations of the ongoing face-to-face contacts (as in previous SocioPatterns experiments), but now annotated using information and profile pictures from on-line social networks and semantic data. Participants can also visit their account page on the LSS web interface and browse the list of persons they have been in contact with during the event, ranked by the measured strengths of the interactions. On top of that, the system provides an interactive web-based visualization that allows users to browse their ego networks across all supported systems, exploring the interplay of face-to-face time, on-line friendships and shared interest. The system also provides simple forms of recommendation, by suggesting the closure of social triangles that span the supported networks: for example, if attendee A has spent face-to-face time with attendee B, the system can point her to the profile of a third attendee C who is a Facebook friend of both A and B, and hasn’t met A yet at the event.
The architecture of the system and some basic usage statistics are reported in a paper that will be presented in the “Semantic Web in Use” track of the International Semantic Web Conference 2009 (ISWC2009). From a research perspective, the collected data enable to relate, quantitatively, how much an on-line friendship between individuals is predictive of their face-to-face time, and how the structure of the on-line and real-world social networks relate to one another. Results about this will be posted here in the coming weeks.
SocioPatterns at Infectious in the Science Gallery, Dublin
Last week we deployed a new SocioPatterns experiment at the “Infectious” exhibition in the Science Gallery at the Trinity College in Dublin, Ireland. The following movie is a teaser for the exhibition.
Setup
All visitors of the exhibition get to wear SocioPatterns/OpenBeacon tags during their visit. For this exhibition, the firmware has been enhanced to support a “virtual contagion” process. When visitors enter the exhibition their tags are initially “uninfected”. A tag can get “infected” if the person wearing it spends time in the vicinity of an “infected” person. Infected tags have a different blinking pattern and show up as red marks in the real-time visualization available to the visitors, as opposed to green for uninfected ones.
This deployment also features a reactive part that involves audio-visual effects triggered by the proximity of individuals. Various visualizations of either the whole interaction network or contextual subsets, are located throughout the exhibition.
The following is an extract from the April 16 journal on the national Irish TV (RTE) that should give you an idea of the exhibition in general and the theatrical framing of the tag distribution process, as well as (the current state of) the alarm effects in the tunnel.
The following video offers a nice overview of the complete exhibition, starting with the SocioPatterns deployment.
Also have a look at the exhibition guide superbly designed to look like a government emergency procedure leaflet.
Science
This particular SocioPatterns deployment clearly has a high “drama” component to it. It is, however, also scientifically relevant. In particular the fact that it involves a continuous stream of visitors entering and leaving the exhibition is of interest. Such ”high-flow” setting is akin e.g. train stations or airports. A better understanding of the structural and temporal nature of social interaction patterns in such high-flow settings is relevant in a number of domains, including epidemiology. Clearly, collecting detailed data on these patterns in an actual train station or airport is very difficult. The relatively controlled and approximating settings of this exhibition does however provides us a promising opportunity to indeed collect such data.
While our earlier experiments were deployed at conferences with a relatively homogeneous and stable population, here we have a more heterogenous and dynamic population. We can thus now compare the social interaction patterns in these different settings. We are interested in deploying SocioPatterns experiments in yet other kinds of social settings (proposals are welcome!)
The SocioPatterns deployment at the Infectious exhibition includes a “live” simulation of contagious spreading. By framing this functionality as a “game” and controlling the nature of the information that is provided to the visitors in different runs on different days, we hope to collect data on and compare different kinds of behavioral effects.
Acknowledgements
This project has been deployed by Ciro Cattuto and Wouter Van den Broeck in collaboration with the Science Gallery. We would like to thank Michael John Gorman, Don Pohlman and Derek Williams from this great venue for making this possible. We would also like to thank Milosch and Brita Meriac from OpenBeacon.org for once again providing excellent RFID hardware, and the ISI Foundation for their continued support.
Pictures
To wrap up this post, we would like to share some pictures taken at the exhibition.
A bunch of RFID tags ready to be distributed at the entrance.
Handing out the RFID tags.
Handing out the RFID tags.
The tunnel contains alarm effects triggered by nearby infected tags.
Nearing the end of the tunnel with the disinfection stations.
Queuing to get healed at the disinfection stations.
The visualization at the end of the tunnel during the crowded opening event.
SocioPatterns at the 25C3 conference
On December 26-30th we deployed a new SocioPatterns experiment at the 25th Chaos Communication Congress in Berlin (25C3). This is the first large-scale deployment of our platform for sensing social interactions. We added to the visualization interface several ways of focusing on particular subsets of the real-time and cumulative contact networks. In line with the conference’s action line “nothing to hide”, we made the live contact network available on the web.
We thank the following persons for their work and support: Milosch Meriac, Brita Meriac, and aestetix, Janette Lehmann, Aurora Mazzone, Marco Perosa, Eric Preston, Tomasz Rybak. Our work at 25C3 was carried out in the context of a broader tracking event by the OpenBeacon project and the OpenAMD project, with hardware and infrastructure provided by Bitmanufaktur. We also thank the organizers of 25C3 for hosting our work at such a stimulating event!
Visualizations, movies and results from the data collected at 25C3 will be posted to this blog in the next few weeks.
Contact Patterns part 2
The following movie visualizes the social interactions between the participants of a recent workshop at Villa Gualino. The visualized data is obtained through a distributed sensing platform. This platform uses active RFID technology to detect “contacts” during which participants are both near each other and are facing each other. If such configuration is sustained for longer than a few seconds, then this generally indicates that some form of social interaction is taking place. Next to the actual contacts, the platform also infers where these contacts take place. An earlier post in this blog provides more details on the technical set-up and the objectives of this project. Note however that we here use the peer-to-peer contact detection scheme detailed in this subsequent post. More details about this are provided in a manuscript available at arxiv.org/abs/0811.4170.
[movie]
What this movie shows is a time-lapsed replay of some sections of a real-time visualization that was publicly displayed during the workshop, shown in the picture below. In this visualization, the RFID stations are represented as immobile labeled marks laid out in an oval configuration. Their labels name the areas in which the respective stations are located. There are two stations in sala A in which the workshop presentations took place, three in the bar next to sala A, two in the cafetaria in which lunch was served, and one in the lobby. The size of the round part of the station marks is proportional to the summed strengths of the signals received from beacons.
The publicly displayed visualization. The left screen shows the instantaneous contact network, the right screen shows the cumulative network, which will be discussed in more detail in a future post.
The mobile circlets represent the beacons, which are the small RFID devices worn by the participants. Their size is proportional to their strength, which is the sum of the weights of the contacts they are involved in. Their situation in the visualization is controlled by a force-directed layout algorithm.
A first set of spring forces are applied between beacons and those stations that are within their radio signal range. Their length and tension is proportional to the strength of the respective signals. Stronger signals, which reflect closeness, are translated in shorter spring lengths and increased tensions. The relative location of the participants with respect to the stations is thus (flexibly) mapped to the abstract geography of the visualization. As the signal strengths change when the participants move around with their beacons, the mapping of their marks will be effected accordingly. A clear example of this is the “migration” of the bulk of the beacon marks towards the bar stations marks during the coffee breaks.
A second set of spring forces is applied between beacons that are in contact with each other. These contacts are furthermore explicitly represented as edges. The thickness and shade of these edges, and their spring length and tension, are all proportional to the weight of the contact.
The layout system also involves drag forces and n-body repelling forces. Unlike the spring forces, these do not reflect actual information, but solely serve to optimize the layout. The drag forces are applied to stabilize the spring driven movements, while the repelling forces, which are applied between all beacons marks, prevent overlap.
Comparing this new movie with the one in the first post clearly shows that the new peer-to-peer scheme produces much more precise contact data. The previous system only used proximity as a proxy for social interactions. However, when for example lots of people are seated in a conference room, then many of them are near each other, even though there is no real social interaction going on. In the old movie this is clearly visible. It shows a highly connected network, almost as if everybody is interacting with everybody else at the same time. While perhaps visually pleasing, it is not a truthful representation of reality.
In the new movie on the other hand, there are significantly fewer contact edges. This is because participants now also need to face each other for a contact to be detected. These contacts are therefore a much more reliable proxy of actual social interactions. This seems to be confirmed by the fact that there are now less contacts during the presentations in Sala A than during the breaks, as one would expect, or at least hope for. This particular observation is, by the way, discussed in more detail in the previous post.
