GPS drawings to interpret the urban environment

Drawing with Satellites is a “GPS project” carried out at the Edinburgh School of Architecture and Landscape Architecture by Chris Speed, Esther Polak, Ross Cruickshanks, Karlyn Sutherland and second year Architecture students. The project led to this intriguing PDF booklet.

The brief engaged participants in exploring “how they might draw the city of Edinburgh“. They were asked to do follow various strategies (work with 2 lines, relocate an existing, meaningful route, draw a spiral) which should all be meaningful walking patterns.

In response to this activity, the participated created various drawings represented in the booklet. Each of the drawings correspond to different ways to interpret the urban environment:

• Social Practices tended to use the habitual journeys of people, whose Edinburgh is defined by professional, institutional and occupational routines. Following people, or carrying out processes that adhere to centers of employment or practice, these works offer an insight into the city as a container for production.
• Temporal Projects: the GPS receiver tends to concentrate the user on time: the time that it takes to walk routes, the time between way points, the time between partners.
• Code Controlled: a series of drawings used Code to
  inform their development. Following rule bases that were developed, written down and then performed across the city, drawings that used Code tended to reveal the city’s structural properties, and less the social.
• Ludic: the drawings that embody a Ludic quality that negotiated the landscape through amusement and fun.”

Why do I blog this? Even after few years following GPS drawing and the locative media meme, I’m still fascinated about its relevance to analyze urban behaviors. What’s interesting IMHO is also to put the drawings next to each other and compare them as represented in the picture above.

Back Track : mark it, go anywhere, get back

People talk a lot about location-based services these days. GPS car navigation system is quite mainstream for a while, geosocial services such as Foursquare or Facebook places are more and more adopted, and media attention is still focusing on the promises of location-based marketing (even though users in Europe seem to be wary about them).

However, there is less focus on more niche products based on similar technologies. My neighbor recently lent me one of these curious location-based service. It’s called “BackTrack” and can be defined as a “personal location finder”. It’s advertised with the following elements:

“BackTrack utilizes GPS technology in its most basic format, BackTrack has only two buttons and stores up to three locations – just mark it and forget it until it’s time to return. At the end of the day, select your location and the BackTrack displays direction and distance to travel. Use it to find your car in a crowded parking lot, your treestand or the trailhead, even to rendezvous with your group.“

Or, as described in a very succinct way: “AS EASY AS 1-2-3 Mark it – Go Anywhere – Get Back”. The idea is quite good and the interface is very basic (2 buttons, very limited information on the display), which makes it quite easy to use. However, getting GPS signals is sometimes very difficult in the narrow streets of Paris and Geneva (where I tested it). Using it “on the way back” to your reference point, the experience is curious, as you do not necessary take the same route: you then walk, look at the display and check how to move around with the compass. It was not that efficient to find my way back to my hotel in Paris but I enjoyed having these sort of “location-awareness” information. It told me how far how I was from my apartment in Geneva when spending one week in Paris. Not very useful indeed but surely evocative and close to what I expect to encounter in the 21st Century. Accessing this kind of information without specific ideas in mind about how it can be useful, that was intriguing.

Besides, what’s interesting here is that the idea is very close to a project I blogged about last year, called “Address necklace by Mouna Andraos and Sonali Sridhar:

““Address is a handmade electronic jewelry piece. When you first acquire the pendant, you select a place that you consider to be your anchor – where you were born, your home, or perhaps the place you long to be. Once the jewelry is initialized, every time you wear the piece it displays how many kilometers you are from that location, using a GPS component built into the pendant. As you take Address around the world with you, it serves as a personal connection to that place, making the world a little smaller or maybe a little bigger.““

The Address necklace is of course different, more poetic and evocative than the use cases mentioned for BackTrack (“at the mall and stadium parking lots, at the outdoor festival, the park, for travel or you next outdoor adventure“)… and you can set the location only one time (which makes it very precious and important).

Why do I blog this? Testing the Long Tail of location-based services is always interesting to sense what sort of insights these devices can bring us. It also helps to show that there are different ways to use such technologies.

User’s involvement in location obfuscation with LBS

Exploring End User Preferences for Location Obfuscation, Location-Based Services, and the Value of Location is an interesting paper written by Bernheim Brush, John Krumm, and James Scott from Microsoft Research. The paper presents the result from a field study about people’s concerns about the collection and sharing of long-term location traces.

To do so, they interviewed 32 person from 12 households as part of a 2-month GPS logging study. The researchers also investigated how the same people react to location “obfuscation methods”:

• “Deleting: Delete data near your home(s): Using a non-regular polygon all data within a certain distance of your home and other specific locations you select. This would help prevent someone from discovering where you live.
• Randomizing: Randomly move each of your GPS points by a limited amount. The conditions below ask about progressively more randomization. This would make it harder for someone else to determine your exact location.
• Discretizing: Instead of giving your exact location, give only a square that contains your location. Your exact location could not be determined, only that you were somewhere in the square. This would make it difficult for someone to determine your exact location.
• Subsampling: Delete some of your data so there is gap in time between the points. Anyone who can see your data would only know about your location at certain times.
• Mixing: Instead of giving your exact location, give an area that includes the locations of other people. This means your location would be confused with some number of other people.”

Results indicate that;

“Participants preferred different location obfuscation strategies: Mixing data to provide k-anonymity (15/32), Deleting data near the home (8/32), and Randomizing (7/32). However, their explanations of their choices were consistent with their personal privacy concerns (protecting their home location, obscuring their identity, and not having their precise location/schedule known). When deciding with whom to share with, many participants (20/32) always shared with the same recipient (e.g. public anonymous or academic/corporate) if they shared at all. However, participants showed a lack of awareness of the privacy interrelationships in their location traces, often differing within a household as to whether to share and at what level.“

Why do I blog this? Gathering material about location-based services, digital traces and privacy for a potential research project proposal. What is interesting in this study is simply that the findings show that end-user involvement in obfuscation of their own location data can be an interesting avenue. From a research point of view, it would be curious to investigate and design various sorts of interfaces to allow this to happen in original/relevant/curious ways.

Geosocial/Location-based services usage according to PEW (#techusage)

The PEW Internet&American life project has a new report about usage of location-based services. As usual, it’s mostly quantitative data (phone survey) and it’s focused on Americans but it’s full of interesting material for people who follow this domain.

Before heading to the results, let’s stop first at how they define the focus of their research. In this research, they only zero in a specific category of LBS: the so-called “geo-social” applications:

“Location-based services such as Foursquare and Gowalla use internet-connected mobile devices’ geolocation capabilities to let users notify others of their locations by “checking in” to that location. Location-based services often run on stand-alone software applications, or “apps,” on most major GPS- enabled smartphones or other devices.“

This is important because it means that the focus is not on car navigation assistant or smartphone GPS platforms.

Now, about the main results:

• “7% of adults who go online with their mobile phone use a location-based service.
• 8% of online adults ages 18-29 use location-based services, significantly more than online adults in any other age group.

10% of online Hispanics use these services – significantly more than online whites (3%) or online blacks (5%).

• 6% of online men use a location-based service such as Foursquare or Gowalla, compared with 3% of online women.
• The current number shows little change from the first time this question was asked, in a May 2010 survey, when 5% of adult internet users said they had used such a site.”

Some more tables:

Why do I blog this? It’s interesting to see the stats for geosocial applications (I’d be curious to compare to broader use of location-based services, such as navigation systems) and the results are fairly in line with my understanding of the situation right now. Important figures to keep in mind when talking about the adoption of such apps.

Beyond treasure hunt: locative games 2010 and the near future

Being interviewed by a French media about the state of location-based gaming, I took this opportunity as a way to frame my recent thoughts about this:

Adoption

An important adoption factor for social-locative games is simply… the players: lots of problems described by Dan Hon in his talk “Everything you know about ARG is wrong” can also apply to location-based games: games never have enough players, people who play are not “mainstream”, etc. Above all, the main issue with player is simply the the lack of critical mass… it’s never very funny and engaging to play alone. LBGs really suffer from not reaching networks effect, a situation that Kati London in her talk at Where2.0 referred to as “The empty room effect”.

Gamification, again

At the same time, it’s intriguing to see that game mechanics (in general, but also the one present in early instances of location-based games) have been instrumental in the adoption of a broader category of applications: mobile social software such as Foursquare or Gowalla… which are not games per se. Having lots of discussion with people in the mobile guide/signage/urban discovery/tourism business, it’s funny to see how these persons dismiss a service such as Foursquare as being only “a game”. Different cultures, different perspectives It’s also a good occasion for them to dismiss such application as not relevant for their field (to which of course I object that they’re entirely wrong).

On the shoulder of “giants”

Interestingly, platforms such as Foursquare (today/tomorrow) or Facebook Places (tomorrow) could be an opportunity to develop third-party games. See for example how City Warfare has been built on top of Foursquare:

“You check into your local pub/coffee-shop/train station using FourSquare (as normal).
2) You open City Warfare in your phone’s browser.
3) You place waterballoons, shoot passers-by with your waterpistol etc.
4) While you are away, those balloons remain where you placed them and will burst when the timer runs out or you detonate them remotely.
5) The aim is to try to get as many people wet as possible. You earn credits which can be used to buy better waterbombs etc.“

Location-based game genres

Concerning the challenges and purposes of these games, the types ranges from very focused goals (treasure hunts, people hunting, object collection) to less-defined goals (SCVNGR is interesting in the sense that it lets people defining the challenges). Compared to the past, location-based games have also been influenced by rampant gamification: the emphasis has been made on social comparisons (points, badges, leading boards, etc.)… and of course such games have been included in the toolbox of Media planners and digital communication agencies.

The location-based narrative/storytelling trope has never been huge BUT it less suffered from waves of interest/disillusion. Observers have noted that even standard mobile social software such as Whrrl have implemented collective location-based storytelling. And of course, platforms such as 7 Scenes also offer good possibilities for “mobile storytelling”.

Besides games, there has been a surge in the development of “game engines” to enable people to create their own games. See for example what Playground (that we saw at this Lift seminar in Lyon) or Gbanga are doing.

Phones, rather than game consoles

Speaking about platforms, the de facto device for location-based games is definitely the mobile phone. Although the video game consoles such as the Nintendo DS (with games such as Treasure World) or the Sony PSP (with this Golf game), playful location-based activities are fairly limited.

In terms of technologies, the increasing number of smartphones and App stores (such as the Apple Store) have definitely eased the possibility to try and play. It’s far less complicated than the past, in which we had to download weird software on Tablet PCs, PDAs and cell-phones with tiny displays + low computing power

In addition, on the sensor side, we will see an increasing use of various data beyond players’ location: the usual suspects are of course the number of footsteps (and other accelerometer-based data),… plus self-declared information. Foursquare/Gowalla/Facebook Places check-in are pretty standard here but the use of pictures (taken with a camera) is also common. See for example Foodspotting (which uses “location to augment their own reality-based game“).

So, what did we learn?

• Geolocation is only one kind of data that can be employed and LBG should be framed in a broader context: ARG or pervasive games. Coupled to pertinent and original forms of storytelling and game mechanics, the articulation of data such as location, pictures, SMS, tweets, or the ones generated by touch sensors (NFC on iPhone?), accelerometers, have the potential to lead to curious interactions.
• In terms of innovation, the video game industry is definitely not the right actor here. Rather digital communication agency, small interaction design boutiques and digital studio who work on interactive fictions seems more willing to push the envelope. Curiously, the new media art community has slowed down on the “locative media” meme. I have to admit that I haven’t seen a lot of projects in the field in the 1-2 years (which correlated with the release of “Spook Country by William Gibson).
• I haven’t mentioned Augmented Reality, I don’t know what to think about AR and location-based games.

And what are the possibilities ahead?

• To avoid the empty room problem there is a need to design for single-usage, then for collective usage. We can expect platforms like these in the near future.
• Focus not only on geolocation but also other types of data. There will be games that combine the different sorts of data that can be captured or collected. Of course the most simple forms of data (self-declared such as check-ins, pictures taken with the camera) are the most likely candidate.
• Location-based games with scenarios that are too disruptive and complex for daily usage will continue to remain niches. Will people change their route to go to work in the morning? it’s a bit unlikely.
• There is still some room in different urban activities: think about urban sport (skateboard, rollerblade, fixie/bike ride, parkour, etc.). The articulation of location-based games with these types of sport is an original idea that can produce good possibilities.

Foursquare data analysis about users activities

Bitsybot has an interesting set of visualizations about Foursquare usage. Called Foursquare Trends, it shows users’ behavior over time by visualizing a week’s worth of Foursquare checkins. Bitsybot is interested in using this to “develop a suite of similar tools to help small brick and mortar businesses understand their micro market landscapes“:

Why do I blog this? another type of material that is relevant for our study of Foursquare usage. This type of graph is relevant as a way to show rythms and usage patterns. The example above is based on activity analysis (each activity actually corresponds to a certain set of places).

For us at Liftlab, it’s also interesting to compare this to our current musings about spatial occupancy analysis. See for instance Fabien’s work about:

“We retrieved a couple of months of records produced by 5 Bluetooth scanners, deployed by the Mobility Service of the city of Barcelona on light poles and traffic poles in the Barcelona city center in the Plaza Catalunya – Puerta del Angel – Rambla – Cathedral area. BitCarrier’s solution aggregated over 4 millions non-unique devices (about 1 million unique devices) into periods of 15 minutes, and we discarded the periods with less than 100 detected devices. The database provided a first understanding of the cyclical nature of passing Bluetooth traffic at the nodes and routes forming a connected graph of sensors.“

Motivations for “off the grid check-in” on Foursquare

TechCrunch is generally not a website I follow that much, but there’s an interesting article by a Guest Author about “Off the Grid” check-ins on Foursquare. Following up on the blogpost about automatic location capture I wrote last week, I think it’s worth having a look at this survey mentioned in the TC article.

The survey was about the purpose of using the “OTG” feature, i.e. the possibility on Foursquare to avoid disclosing the location where you checked-in to your contacts. Being “off the grid” however enable to gain points, badges and compete for mayorship. Although the methodology may be a bit rough in terms of sampling (I wonder less about the quantity of peeps who participated than the stratification), here are the conclusions I found interesting:

• “The single largest reason for OTG was hiding from friends [46%]. People gave a variety of motivations [examples: buying a gift for girlfriend, on a date, avoiding someone in particular, hiding one’s poor eating habits from friends, and seeing a doctor.]
• 60% of respondents cited the desire to keep track of where they’ve been for their own future reference. (…) your Foursquare History is a flat set of your check ins but the user interest here points to the opportunity for a much more robust feature. (…) loyalty programs and offers; customer acquisition and retention instruments.
• 34% of respondents used OTG to check into a location that could have been considered confidential or sensitive to their job.
• Mayor stalking was the surprise motivation for many OTG check ins since they count towards mayorships but don’t display your name associated with the venue.
• Only 15% of users report using OTG to signal a “check out” — leaving a venue and not wanting to publish location out of concern friends will arrive to find you departed.
• 26% of people utilize OTG for repeat check ins at a location over the course of a few days (such as a hotel). These could easily be public but collapsed into a single line. Or subsequent check ins might be public, but not published as alerts.”

Why do I blog this? Simply because we (Lift Lab) are currently conducting a short user study of Foursquare with both lead users and people who abandoned using it after a while. Our approach is much more open-ended and based on visualization of spatial data (such as the one generated with where do you go). The TC data will allow to triangulate our qualitative data with this quantitative insights.

Location-Based Social Media and the automation bias

Reading this blogpost left me wondering about some companies/people that do not understand the notion of “active check-in” on Foursquare (or now Facebook Places). See for yourself: “The active checkin requirement is one thing holding back location-based social networks (also called “geosocial” networks) from widespread adoption. (According to Forrester, only 4% of Internet users have ever used them.)“. It reminds of the opinion about Foursquare stated by this analyst: “It seems like the marketplace has taken a step back 5 years. All of a sudden people seem to be convinced that this kind of technology — where you have to actually remember to tell people where you are — is the best thing since sliced bread. (…) The crucial flaw with FourSquare et al., is that it’s based around manual push notifications.”

For this kind of analyst, an explicit interaction (doing a check-in) is perceived as backward and lame. In engineering circles, this sort of argument is highly common and I would refer to it as the “automation bias“, i.e. the firm belief in automating whatever human activity that can be transferred to computers/machines (which is grounded in strong positivist ideas about progress obviously). The comments I quoted above do not acknowledge the reason why interaction designers have chosen this solution over, say… CellID triangulation or a nearly magical GPS signal detection. Readers here have certainly read my opinion about this topic here, there (or in French). But I think it’s worth repeating the claims here:

1. Of course, decreasing users’ burden is an important adoption factor, I fully acknowledge it. However, automating this can be perceived as a threat by people who feel that they will loose control of their personal data. It can also be problematic for some individuals because this automatic feature will make explicit situations they don’t want to make public. Technologies should be “conservative of face” as described by Adam Greenfield some time ago: wherever possible they not unnecessarily embarrass, humiliate, or shame their users. See for example this comment in the original Mashable blogpost: “I go places that I am not always proud of (think Waffle House at 2:30am) and at that point (think less than sober) I can see myself forgetting to turn the auto check-in off. (…) there has to be a better way for it not to be obtrusive, but still controlled.“. Letting people doing manual check-in is more respectful of people’s habits and, above all, it enable people to lie (which has always been a good adoption factor). This is why the proposition to have an intermediary solution is interesting: “ the app would have some sort of pop up/notification that lets you know you are in a check-in-able location“
2. What is showed in my research: self-reporting one’s location has a value in itself. Declaring your whereabouts is not just a piece of information, there is also an intention attached to it. Say I’m in a Bar and the name of this place is sent to my colleague, it’s both a statement about where I am and an act of communication that tells others that they can act upon this information (to draw inferences about my availability or my willingness to interact socially for example).

Having said that, the problem is not about the manual check-in but instead, it’s about the extent to which people use this feature. I know “checkin fatigue” is important… but doing it manually means that the place where people check-in are more meaningful to others… since Foursquare removed the leaderboards (and hence the incentive to gain as many points as you can), users I have interviewed said that they stopped checking-in everywhere (supermarkets…) and only made their position available when they wanted to meet others or access to certain information. I am curious about this and we are currently launching a user study of Foursquare to understand this kind of issue.

Context-aware applications in 2010

Interestingly, location-based/Context-aware services are more and more present in the press. After the frenziness of 2004-2005 (and less interest afterwards), I see more and more article about the potential role of location and context as the starting point for complex scenarios. See for example the ideas described in this article:

• “My context device “knows” it’s noon. It also knows (via accelerometer data) that I haven’t moved from my desk for the last couple of hours. Because it “knows” I have a TBD lunch scheduled for 12:30 (it reads my tagged calendar entries), it will remind me I should leave. As soon as I move the device, it displays the list of places where I had lunch the last couple of weeks. Since most were Italian restaurants, it suggests Chinese or falafel and generates the latest consumer rating of the restaurants offered. At the same time, it also highlights restaurants located within walking distance that will allow me to be back in time for my scheduled 2 p.m. meeting.
• I am on a business trip to Madrid, have just finished my meetings and have three hours until my flight back to New York. My device “senses” I started moving and “knows” my schedule, therefore it asks me if I prefer to get a taxi to the airport, or if I prefer to stay in the city since the drive to the airport takes about 15 minutes. I choose the second option, slide the “ambient media streams” all the way from “privacy please” to “hit me with everything you’ve got,” and the device offers me all the tourist attractions around me, even a nearby coffee shop that has received exceptionally high ratings (I love coffee). I choose the coffee shop, and as I am drinking my second cup, the device alerts me that my flight has been delayed by an hour and will board through gate E32. I drink another cup of coffee and read from my device the history of Madrid until the next alert updates me that I should call a taxi — immediately providing me with an application that directly books one.
• I leave my office to interview someone at a nearby bar. My device “knows” it is a job interview (tagged in my calendar), therefore it automatically Googles the applicant, uploads his resume and image, and then provides me with a summary of the available information found about him from HR, the web and other social sources. As I approach the bar, my device turns itself into “meeting” mode, in which I can view a map that displays two dots approaching each other. As we meet, the device asks me if I would like to record the conversation and send it to HR.”

Why do I blog this? I am not sure I am convinced by these scenarios but it’s interesting to contrast them with the one we saw in 2004-2005. The move from location to context is interesting because it shows that the former is only a component of the latter. It also acknowledges the importance of taking into account the complexity of contextual information which cannot be limited to mere locational data.

Unlike the 3 stereotypical scenarios we had 5 years ago (friend-finding, location-based ads and geotagged post-its), the ones described here are a bit more complex and rely on the connection between “personalized social/behavioral data” and contextual information (location, time, etc.). Using algorithms, services would then be able to infer different things that can supposedly interest people, especially in urban environments.

Location-awareness sharing and affordances in the subway

Two recent articles about location-based platforms caught my eyes

Seeburger, J., & Schroeter, R. (2009, Nov 23-27). Disposable Maps: Ad hoc Location Sharing. In J. Kjeldskov, J. Paay & S. Viller (Eds.), Proceedings OZCHI 2009 (pp. 377-380). Melbourne, VIC: The University of Melbourne.

“The gathering of people in everyday life is intertwined with travelling to negotiated locations. As a result, mobile phones are often used to rearrange meetings when one or more participants are late or cannot make it on time. Our research is based on the hypothesis that the provision of location data can enhance the experience of people who are meeting each other in different locations. This paper presents work-in-progress on a novel approach to share one’s location data in real-time which is visualised on a web-based map in a privacy conscious way. Disposable Maps allows users to select contacts from their phone’s address book who then receive up-to-date location data. The utilisation of peer-to-peer notifications and the application of unique URLs for location storage and presentation enable location sharing whilst ensuring users’ location privacy. In contrast to other location sharing services like Google Latitude, Disposable Maps enables ad hoc location sharing to actively selected location receivers for a fixed period of time in a specific given situation. We present first insights from an initial application user test and show future work on the approach of disposable information allocation.“

(Thanks Antonio!)

Belloni, Nicolas and Holmquist, Lars Erik and Tholander, Jakob (2009)See you on the subway: exploring mobile social software. In: In Proceedings of the 27th international Conference Extended Abstracts on Human Factors in Computing Systems, 4-9 April 2009, Boston, USA.

“This project explores the social possibilities of mobile technology in transitional spaces such as public transport. Based on a cultural probes study of Stockholm subway commuters, we designed a location- based friend finder that displays only people in the same train as the user.
(…)
The interviews showed that the users did not always have an obvious idea for what actions to take once they realized that a friend was on the same train (…) This points to the complexity a social situation like this and the multitude of social layers that comes into play for designers of social services. In this case, it seems like the user didn‟t feel close enough to his work colleague for taking contact at this particular moment. (…) Adding the possibility to call the person or send a text message could be one of functionalities improving the user experience.“

Why do I blog this? Collecting material for current projects about location-based services. Both papers describe relevant studies about the user experience of location-awareness and the complexity of building social applications on top of it.