It is called “Towards Reducing the Social-Technical Gap in Location-Aware Computing” and the abstract goes as follow:

Abstract: Along in their history, humans never ceased to create techniques and tools for observing their environment and locate themselves in the physical environment. This attests our necessity to be aware of who and what is where and when – a concept that we term location awareness. Nowadays, the democratization of mobile and wireless technologies increases people’s awareness of their whereabouts. However, it also their interaction with the physical environment and by consequence impacts the social interactions and work practices.

Building ubiquitous applications that exploit location requires integrating underlying infrastructure for linking sensors with high-level representation of the measured space to support human activities. However, the real world constraints limit the efficiency of location technologies. The inherent spatial uncertainty embedded in mobile and location systems constantly challenges the coexistence of digital and physical spaces. Consequently, the technical mechanisms fail to match the highly flexible, nuanced, and contextual human spatial activities. These discrepancies generate a social-technical gap between what should be socially supported and what can be technically achieved. This thesis contributes to the research in the field of Computer Supported Cooperative Work (CSCW) and ubiquitous computing by exploring, and hopefully reducing this gap in the context of location-aware systems.

Our preliminary work reports on complementary studies of some of the aspects of the social-technical gap. This preliminary and current work, takes very different perspectives on the use of location-aware applications. These views highlight the role of the spatial context and technological limitations in the use of the systems features. First, we explored the impact of the technical limitations in collaborative tasks experienced in the form of a location-aware game. It allowed us to define the sources of spatial uncertainty perceived by the users while interacting with the system. Then, we investigated the social requirements of linking information to space. In particular, we report on the influence of space in the use of location granularity to share and retrieve photos. Finally, we describe an ongoing ethnographic study of the evolution of taxi drivers practices with the introduction of location-aware and navigation systems in their work. This work reveals the ways positioning technologies influence the work practice of mobile workers. For instance, some drivers access the geospatial information as in a “funnel”. They start a ride with a general idea of an area surrounding the destination. As they enter the targeted area they access detailed information for the specific destination with location-aware application.

The extensive review of the domains of ubiquitous computing and CSCW shows that more of the research in those fields focus on optimizing the accuracy of location sensing and providing seamless interaction. On the other hand, limited work has been pursued to understand the social-technical issued in real-word settings and provide solutions to match the visions of supporting people’s everyday life activities. In consequence, we suggest research perspectives that should contribute to this agenda. Through real-world field studies, we aim at providing solutions for the design of collaborative location-aware systems that take into account the spatial uncertainty inherent to ubiquitous technologies.

Keywords: location-aware computing, spatial uncertainty, CSCW, location-awareness.

Relation to thesis: More than half-way through the PhD… I hope.

My work-in-progress submission entitled “Place this Photo on a Map: A Study of Explicit Disclosure of Location Information” has been accepted to the 9th International Conference on Ubiquitous Computing, 16-19 September 2007, Innsbruck, Austria.

Abstract. This paper reports on the early results from an ongoing study of the use of popular photo-sharing platform. We specifically focus our investigation on the factors influencing the accuracy users choose to link their photos to the physical world. We believe that modeling these mechanism can impact the design of ubiquitous systems that support sharing and retrieval of location-enhance information. For instance, it could suggest guidelines to match people’s expectations of granularity in location information. Our early results reveal that while familiarity with a place does not seem to influence the accuracy of the disclosed location, the city and type of urban landscape impact the use of coarse and fine-grained location information.

The reviewers’ feedback are positive about the pertinence of this work and the approach. They mention “relevant to ubicomp”, “the concepts and the writing are generally good”, “the problem is important and the early findings are interesting”, “good problem formulation and research methodology”, “the authors have taken the proper first steps by looking at a real-world data set”. However, they question the early analysis:

• I concentrate on how people tag, rather than what is actually done with those tags. So I won’t be able to know about the usefulness of granularity.
• More depth analysis and logic should be supplied to make the Barcelona results believable.
• Application of arbitrary boundaries (why 2 months to seperate between resident and tourists. I could have let the categories emerge.
• Why familiarity with the environment was the only metrics chosen.
• Some more depth to the results, even in a few more sentences
• The results might be strongly tied to Flickr, thus I need to validate the findings by cross-checking different platforms.

Relation to my thesis: A final extended abstract to help me validate Tracing the Visitor’s Eye.

I like to introduce Plazes to highlight the importance of granularity in to communicate the timeliness and quality of location information.

The now classic slide on “Location information granularity” with the Geneva airport in the Rhone river and me at the train station (while I took the screenshot in another city)

I might have to update my slides. The new version of Plazes came up with a “My World” view that (I think) has some intentions to take into consideration the granularity in space of the “trazes” I left recently. Drawing a circle is an obvious way to communicate the uncertainty in the location sighting (as modeled by Leonhardi and Rothermel).

No recollection of a trip to the midwest…

Relation to my thesis: Collecting example of visualization location information granularity

Today, I presented to the SENSEable City Lab team my past projects and my line of research on location-awarness at the crossroad of ubicomp, HCI and urban studies. This purpose was to provide a rather detailed awareness of my research agenda to maybe find synergies for the future. The slides and notes are available here.

The feedbacks were rather positive with many questions and discussions around the shift from location-based services and location-enhanced services (e.g. location is not at the center of attention). Carlo Ratti questioned the overall coherence of my different studies. For example, he was puzzled by the case study of a study of a system such as Flickr, designed by somebody else to then evaluated my own design in the field. I am aware (and concerned) that I will need to find relations between studies, but so far the several advisors who have seen my work at CHI and Pervasive confirmed me that if was fine. However, I surely will need to find a stronger focus (e.g. study of one/two specific spatial activity) and define the audience and part of the system (e.g. interface visualization, interaction, middleware) I would like to influence. My claim is that I am in a funnel and that this summer case studies will lead me to study and evaluate more specific issues as the one I described today.

The written feedback I received for my accepted paper for the Pervasive 2007 Doctoral Colloquium are rather encouraging and reveal similar suggestions and advices given at CHI. My research focus and strategy is well grounded and accepted. One reviewer noticed that my work clearly starts where others (e.g. Benford, Chalmers) have stopped. However, now has come the time to be more specific on the methods to collect and analyze the data. Moreover, I still need to argument the ways I plan to evaluate the design strategies I will propose. I split the feedback as follow:

Scope
First my dissertation research is perceived has well grounded, well situated, and well motivated. My contribution would improve the state of the art. Yet, my early work is perceived as rather preliminary (very simple and obvious). Certaintly because a lot comes from the litterature that concures with what could be observed in CatchBob! Yet, I feel that I contributed into unifying the state of different domains such as context-aware computing, human-computer interaction, CSCW, urban computing, (humanistic) geography, geospatial visualization, transportation research to converge on the specific issue of spatial uncertainty. To my knowledge, the literature in location-aware computing and location-awareness has never profited from the ensemble of these different perspectives. My current contribution maybe lays more in that area, with my first field study acting as revelation and consolidator.

Research strategy
The approach of analyzing the current use of location information and then building and evaluating a location-aware system form an acceptable strategy. In addition, using location-based games has proved to be a feasible avenue of investigation. This strategy is a result of my overall motivation in this research. I believe it is important to study the pieces of the ubicomp of the present in their context and current us to understand how they can gradually be integrated at a larger scale. As a result, practically speaking, knowing how good in good enough in terms of location-awareness, can prevent the counterproductive aim for technological perfection.

Methods and data analysis
Now, how exactly will I tackle my research questions in a way that is not too expensive for a PhD. One reviewer mentions that two of the sub-questions might suffice for a good thesis. However, all this depends on the methods of investigation and support with the data analysis. For example, I might also pursue a collaboration within a larger project (this is my current intention).

Mixing field and case study seems fine, but I must be able to describe in greater details these two different approaches and the methods they imply. For instance, there is not clear definition of both approaches. My perception of a case study is that it is not controlled and very observational both from quantitative and qualitative data. On the other hand, a field study is more directed by the capture of the data from the variables to analyze. That implies a quasy-controlled environment propitious to targetted data collection and focused ethnography. A case study is a good way to explore behaviors and a field study allows to evaluate or demonstrate. Mention field experiment instead of field study for example. At this point I need much more thinking about collecting data and analizing it. Finally, while hard to accomplish and time/resource consuming triangulation of methods (mixed research) is always advisable. Therefore, I should find out which of the analysis methods suit best for my research question, resources (help from co-investigators? collaborate with social scientists) and abilities (improvement with supervision and training, reading about it is not enough).

I still lack of a clear strategy on how to exploit the results of my studies and how to transfer the experience into appropriate solutions/strategies for developing location-aware applications. How will I evaluate the new proposed strategies. I’ll get back to John Creswell’s Research Design over the weekend to help me iterate one more time over my intentions and how to answer the questions of each of my proposed study. Then I’ll need to articulate them as a whole.

Contribution
My preliminary work (while basic and somehow obvious) show that I can meet the research goals. However, I will need to be careful to the extend the results I claim can be generalized across domains (but I guess this is every PhD student’s problem in the field of HCI).

Related avenues to consider
The reviewers suggest avenues that I actually considered in the past, but did not mention in the paper for the sack of … They mention that I should have a look at the positive aspect of uncertainty. For example: How do people exploit uncertainty (keep privacy, location disclosure) and as a way to appropriate ambiguit for one’s one purposes (e.g. Bill Gaver’s Ambiguity as Resource for Design). I should look at how people experience space (or place). There is a good litterature on that in the domaine of “humanistic geography” (so far, I inspired more from the works of Rapper and Mountain… Time geography). So instead of going too much in geography (geometric measurement of space) I should be more aware of the experience and meaningfulness of space.

I could address the privacy issues in addition, with the demand of spatial uncertainty (privacy policites to cloaking). Not to deliver information about the intentional spatial uncertainty. I read a rather technical article (based on a middleware approach) on that recently: Efficiently managing location information with privacy requirements in Wi-Fi networks: a middleware approach. The ideal would be to impact the design and logic of the middleware from a human-centered perspective as Tom Rodden suggested me 2 weekends ago.

Next step: Provide an answer to these feedback in my DC presentation on Sunday. Try to explain more clearly the questions/methodology/data analysis for each study. Then define the outcome of each study to articulate a coherent whole. Iterate, and iterate more…

Konomi, S., and Roussos, G. Ubiquitous computing in the real world: lessons learnt from large scale rfid deployments. Personal and Ubiquitous Computing (2006).

This article takes part of the train of thoughts on the inherent antagonisms of ubiquitous computing reality and the seamless calm computing vision advocated by some academic research. It does so by examining two fully operational Radio Frequency Identification-based systems: the Oyster card ticketing system used at the London Underground in the UK, and retail applications deployed at the Mitsukoshi departmental stores in Tokyo, Japan. Each case study is analyzed through the terms of technologies, user interactions, and their business and organizational context. As a result, the authors highlight that the real world has concerns that are rarely dealt with in research.

Ubiquitous computing in the real world has concerns that are rarely dealt with in research. Lengthy and costly preparation or upgrade of existing infrastructures; training of employees and users in the new ways of working; controlled introduction of new functionality; features and services to manage risk; unexpected behaviors due to the wider variety of possible real world situations; incremental approach to systems development so as to better identify successful aspects; regard for the economics of systems as a core requirement; and selection of open or closed systems, are all issues that are mostly outside the scope of current ubiquitous computing research, but seem to play a critical role in both case studies we consider here.

As a consequence, so far, the ubicomp of the present is made of isolated islands of functionality rather than a seamlessly connect whole. That brings the authors to define the challenges for ubicomp research around taking into consideration of the constraints of the real world but also in bringing a more user-oriented approach to research practices:

Therein lies the challenge for ubiquitous computing research: how not only to learn about the concerns of those developing systems in the real world but more importantly, how to translate principles, guidelines and models discovered in the context of research into useful tools for building ubiquitous computing systems in the real world. Bringing the two communities closer together and communicating lessons learnt in ubiquitous computing research so as to inform practical system design and development can have profound implications for the success or the failure of the ubiquitous computing vision.

Relation to my thesis: My research on spatial uncertainty revolves around the gap between practice and the state of the art in research. (That is in other words understanding both the concerns of the real world and the expectations of the users to build useful location aware application). This gap is well described by papers such as this one. I also ground my approach on the critique of researchers and technologies that absolve themselves for responsibilities for the present.

Relation to my thesis: Embracing the Real World’s Messiness

The main problem for urban planers, traffic engineers, transport authorities to perform urban modeling is the lack of real mobility data. While car traffic is pretty easy to estimate with sensors (cameras) deployed on the main city crossroads, when there is not “real” data, the only options are to perform in-sitiu surveys or rely on rough estimations (e.g. based on the police estimations). But the resulting picture is often inadequate, expensive—or both. Experiments to automatize the process remains very scarce. For instance, Eamonn O’Neill and Vassilis Kostakos (University of Bath, UK, as part of the Cityware project) presented at Ubicomp last year, a study on the deployment of a Bluetooth scanning system at every key points in Bath (with only 7.5% of the pedestrians carrying a Bluetooth enabled mobile phone). On the other hand, the transportation research has been (painfully) processing logs of vehicles location data generated by GPS embedded in cars. Finally, the market research industry has been trying to guess how many eyeballs pass a billboard by providing panelists with GPS units.

In the recent years, the large deployment of GSM phones generated a massive increase in the volume of spatio-temporal data that can be used to infer individuals or groups spatio-temporal behaviors. The MIT SENSEable City Lab (recently featured in the “E”’s Technology Quarterly) has pioneered in the visualization of the movement dynamics of cellphone users and has rendered a real-time “pulse of a city” (video). The results take the form of luminous maps adorned with moving and colour-coded arrows, dots and patches of light that indicate the speed and population density of people in the city in question. Other example, IntelliOne developed TrafficAid that identifies congestion in real time by using cell phone location provided by GSM operators. The measurement system processes thousands of device locations per second, “snaps” each device to the road network, and monitors movement for a short period of time. Similarly, Timothy Sohn showed (also at ubicomp06) his mobility mode recognition experiment using everyday GSM traces. He used the logs generated by the everyday lives of three data collectors over a period of one month, yielding an overall average accuracy of 85%, and a daily step count number that reasonably approximates the numbers determined by several commercial pedometers.

MIT’s Real-time Rome: Crowd movement in Rome during the celebration of the World Cup victory.

I perceive 3 main domains of applicability of the processing and visualization of these massively collected personal logs, traces (i.e. history of previous locations)

• Provide urban planners, transport authorities and traffic engineers with data to refine their models of citizens spatio-temporal behaviors. For example, fine-grained “origin-destination” (OD) statistics allow to build more accurate traffic simulation.
• Bring new perspective for decision making and policies building. People-movement maps “will be invaluable” in planning housing and transport.
• Raise awareness and affect the discussion making of individuals or of a crowd. The above-mentioned TrafficAid system is one example. A step beyond, Intel Research Berkeley suggests the idea of Participatory Urbanism, AIR, or BioMapping . This feedback mechanism (urban awareness) is one fascinating aspect of such massive spatio-temporal data collection (this is probably what I would discuss if I get the chance to go to the upFing’07 Villes 2.0 workshop). In fact, Nicolas and I have been discussing quite a bit the use of asynchronous location awareness (traces) tools as a way to highlight social spaces inferred from the traces left in the environment .

Inferring spatio-temporal activities raise several issues that are at the core of my research. First, geographic information systems have limited ability to handle the temporal dimension. Then, the many sources of error and imprecision in the sensed data impact the quality and timeliness of the location data. The visualization might take into consideration the uncertainty in the delivered information (as raised by MacEachren et al in Visualizing Geospatial Information Uncertainty: What We Know and What We Need to Know). Finally, histories of location information mainly render a quantitative understanding of the city.

A visual log of physical presence

I have been with Radio-Frequency (i.e. WiFi and GSM) based positioning and mobility inference for the past 3+ years. Now, I explore a different approach to the collection and analysis of spatio-temporal activities. Based on a first experiment I called (inspired by Scott Smith) Tracing the Vistor’s Eye, I explore the potential of using user-generated geotagged content to infer activities. I have been relying on Flickr geotagged photo to define and confirm patterns of how tourists navigate the urban space (e.g. the elephant path along the Rambla, people do not walk to Gaudi’s Sagrada Familia). I believe that the richness of the collection and analysis of such data is that it carries a higher meaning that x;y;timesptamp location data. Taking, uploading, tagging and geotagging a picture can be interpreted as an act of communication rather than a pure implicit log of physical presence (Inspired by Nicolas’ work on automatic and manual location disclosure and The Error of our Ways: The experience of Self- Reported Position in a Location-Based Game. Therefore, my research agenda for this experiment is to:

• Build a framework that infers spatio-temporal activities in urban spaces based on user-generated content. Use tourists exploring cities as context
• Enrich quantitative spatio-temporal data with qualitative information embedded in images
• Integrate the notions of location information quality and timeliness in the data
• Analyze how Flickr users use the accuracy feature to geotag their images (where, what, when, history of use, overall usage over time). This is to provide a study on the quality of explicitly disclosed location information. In other words, what level of location information quality and timeliness must be delivered in order to be useful and relevant?
• Experiment with ways to visualize this type of spatio-temporal data with its uncertainty. Why not use the InfoScope. Here I aim to explore the parameters that influence successful uncertainty visualization.
• Evaluate the People-movement maps/visualizations. Maybe use the people of Barcelona Ecologia as expert users.
• (would be nice) Evaluate the completion of the “feedback control system”.

I have the core of the framework ready. It processed and generated KML files from test data of Barcelona, San Francisco, and Boston. I plan to collect data from the World’s Most Photographed Cities. As a next step, I will add the sense of origin and destination to visual representation of the traces. Moreover, I will infer the origin of the photographers as of being a tourist or a citizen. Finally, the photos will belong to several temporal categories (e.g. morning/afternoon/night, week day/weekend, special events) and location accuracy categories (e.g. street, neighborhood, city).

Early experiments with Flickr images taken in San Francisco between March 11 and March 25, 2007). The complete set of screenshots.

Relation to my thesis: I became acquainted of the multiple issues in collecting data collection during my discussions with the urban ecology agency “Barcelona Ecologia”, my readings in transportation research and the design and deployment of GSM-based personal mobility detection systems. This urban computing experiment is the first of the three experiment I plan to investigate my main research questions. It aims at providing clues to my sub-research questions 1) what level of location information quality and timeliness must be delivered in order to be useful and relevant? and 2) what parameters influence successful uncertainty visualization?

Ykä Huhtala and Jussi Kaasinen of Nokia Research recently offered for free download their Nokia Sports Tracker for S60 3rd edition phones. Nokia Sports Tracker uses a Bluetooth GPS device or an integrated GPSis a GPS based activity tracker that runs on S60 smartphones. Information such as speed, distance and time are automatically stored to your training diary.

I programmed a similar application in S60 Python a while ago. However I rapidly got annoyed by several things:
- the need to find an place to get good visibility to satellites for the GPS to warm-up and start running
- while running, the phone would sometimes lose the Bluetooth connection to the GPS without being able to automatically reconnect (possibly a S60 Python issue)
- I would often run in forests where I would get bad or no GPS signal impacting the measured distance.
- Wearing a mobile phone + GPS unit while running is a pain (e.g. straps that get loose).
- I ended up taking phone calls or reading/writing SMSs…

Relation to my thesis: There is a real interest in logging personal mobility and activity (i.e. traces) for health (pedometers, BioMapping, Nokia Sports Tracks, Nike+iPod) or social (Jaiku, Marc Hottinger’s dataSpaces) purposes. Such applications can provide valuable self-awareness and replay tools (such as in persuasive or healthcare systems). However, beyond the privacy and ethic issues, the way to integrate them in our daily lives, collect data and way to deliver them in a meaningful way is still at its infancy.

Courtesy of Bio Mapping

My paper for the Pervasive 2007 Doctoral Colloquium has been accepted. It is an extended version of the CHI’07 submission.

Bridging the Social-Technical Gap in Location-Aware Computing

Abstract. Building ubiquitous applications that exploit location requires integrating underlying infrastructure for linking sensors with high-level representation of the measured space to support human activities. However, the real world constraints limit the efficiency of location technologies. The inherent spatial uncertainty embedded in mobile and location systems constantly challenges the coexistence of digital and physical spaces. Consequently, the technical mechanisms fail to match the highly flexible, nuanced, and contextual human spatial activities. These discrepancies generate a social-technical gap between what should be socially supported and what can be technically achieved. My research aims at exploring, and hopefully reducing this gap in the context of location-aware computing.

Relation to my thesis: I am pretty glad that people like Shwetak Patel (Supporting Location and Proximity-Based Studies in Natural Settings) and Leif Oppermann (Extending Authoring Tools for Location-Aware Applications with an Infrastructure Visualisation Layer) will also present their work. Hopefully Leif will also talk about his location based mobile phone game Love City. Pervasive 2007 will take place on May 13-16 in Toronto, Ontario, Canada.