1. Challenges of Mobile Phone-Based,
GPS-Dependent Gaming for Citizen
Science
Abstract
Citizen Science (CS) projects involve the public in data
collection for a range of goals, from scientific to social
health. Context aware gaming, where location-based
information is used to inform gaming elements, can be
leveraged to engage players in CS activities, attract
new players, and act as quality assurance for data
collected. Here we describe the challenges faced
during development of the mobile phone-based CS
game of Floracaching that uses the GPS sensor to grant
players access to gaining points based on their physical
location. Problems with the accuracy of GPS have been
demonstrated to reduce player confidence in the
functionality of the game and have led to abandonment
of further play and data collection. We introduce a
method for manually overcoming the GPS-based
location inaccuracy in urban environments and
evaluated its effectiveness on a university campus.
Author Keywords
Participatory Sensing; climate change; plant phenology
ACM Classification Keywords
J.3 LIFE AND MEDICAL SCIENCES; D.m
MISCELLANEOUS; H.5.4 Hypertext/Hypermedia; H.5.2
User Interfaces
Copyright is held by the author/owner(s).
CSCW’12, February 11–15, 2012, Seattle, Washington, USA.
ACM 978-1-4503-1051-2/12/02.
Eric A. Graham, Dylan Vassallo, Sophie Gerrick,
Kyungsik Han, Jinha Kang, Nancy Hsieh
Center for Embedded Networked Sensing
University of California, Los Angeles
Los Angeles, California
egraham@ucla.edu, dylanv@ucla.edu, slgerrick@gmail.com,
zenithhan@gmail.com, jinhakang@ucla.edu,
nancyhsieh@ucla.edu
Figure 1. The home screen for
BudBurst Mobile with access to the
Floracaching game.

2. General Terms
Human Factors; Design; Measurement; Reliability;
Verification
Introduction
Citizen Science and Project BudBurst
Citizen Science (CS) and Participatory Sensing projects
are research collaborations that enable non-scientist
members of the public to assist with scientific provide
substantial and unique datasets that have the potential
for greatly increasing the volume of observational data
for research, and include, for example, projects that
ask participants to classify photographs of galaxies [1],
report bird sighting data for ornithological research [2],
or plant sunflowers and observe bee pollination [3].
Public engagement in scientific and technological issues
has exploded in popularity in recent years [4].
Project BudBurst1
is a national CS program that
involves non-scientists dedicated to recording the
timing of life stages (phenology) of plants (e.g., the
date when a plant first leafs out) and how this relates
to environmental conditions. Data from phenological
studies are increasingly relevant for addressing applied
environmental and sustainability issues [5].
BudBurst Mobile (Figure 1) is the mobile phone-based
extension to Project BudBurst. Although BudBurst
Mobile was developed primarily as a record-keeping
tool for Project BudBurst, it is also an example of a
technology that supports civic engagement in issues
that are of social concern [6, 7], and is thus an ideal
platform for testing methods of engagement to
participate [8]. Additionally, BudBurst Mobile is a
1
http://budburst.org
context-aware application, in that it leverages the
location-based services available on the Android
platform (GPS, WiFi location) in order to automatically
send data collection parameters to the server.
Games and Floracaching
Games have been used in CS projects to increase
participation and the amount of data collected or
processed [e.g., 1]. Indeed, games are natural
extension for CS projects because often participation is
based on enjoyment, with secondary motivations
involving identification with the goals of the project [9].
Floracaching2
is a game within BudBurst Mobile that is
similar to geocaching3
, in that locations have been
identified using GPS coordinates that players must find.
In Floracaching, a plant occurs at the published location
that players search for. Finding a Floracache (the
plant) consists of being within 10 m, as determined by
the GPS sensor on the mobile phone, and then
subsequently using BudBurst Mobile to capture a photo
and record the plant phenophase (e.g., first leaf, first
flower, etc.).
It is desirable to allow volunteers to start contributing
to CS projects through even low-level tasks [9]. Thus,
finding one type of Floracache can be accomplished
relatively easily, through a live map interface (Figure
2). Two other types of Floracaches are more
challenging to find: a medium- difficulty level, with a
compass direction and distance indication, and hard
level, with only a description of the location of the plant
that offers the most points per capture. Ranks or levels
2
http://floracaching.org
3
http://www.geocaching.com
Figure 2. The Map level for
locating Floracaches. Note the
messages indicating that the player
is not within range after trying to
capture the Floracache.

3. are obtained after accumulating sufficient points in the
game and badges are assigned as a reward.
Challenges of Using GPS in Floracaching
Problems with the accuracy of GPS in urban
environments are not uncommon [10] and can be due
to both temporary blockage of signals by buildings and
terrain and also reflections off the sides of buildings,
resulting in multi-path fading. The effect has been
termed the GPS signal “near far” effect [11]. Forested
areas with an appreciable canopy can also significantly
block satellite signals [12].
The Floracaching game has been previously evaluated
for performance and user experience using groups of
volunteers [13]. During a more recent test of the
game, 64% of the 22 volunteers indicated that while
trying to find a Floracache their phone’s GPS sensor
located them incorrectly. Erroneous GPS-based location
data was common enough to delay or prevent the
capturing of Floracaches for most of the players, even
though they indicated that they had physically found
the Floracache. Anecdotal information gathered from
volunteers indicated that if a GPS error was
encountered during their initial attempts to find a
Floracache, the player was more likely to abandon the
game than to continue.
Solutions for Reducing Location Errors
Many hardware [e.g., 14] and software [e.g.,15]
solutions to reducing GPS errors on mobile phones have
been investigated. Using the reported GPS error has
also been used to trigger feedback to a user. In one
study, a mean error of about 15 m forced a context
aware mobile application to use other information to
remove positioning uncertainty [16].
We found that on the ULCA campus we could not rely
on the system-reported GPS “accuracy” value from the
mobile phone, which is calculated in part using the
number of visible satellites and may be incorrect due to
multipath errors [17]. Additionally, a backwardly
compatible solution that is available to all smartphones
that can run the Budburst Mobile application was
desired.
Thus, we implemented a manual solution for players to
adjust their locations using a pop-up map if they feel
that they have found the Floracache but their GPS-
based location indicates that they are outside the 10 m
range (Figure 3). If the player is within 30 m of the
Floracache, he or she is presented with a notice that
they can adjust their location via a map (with no visible
Floracaches) with the center being the current GPS-
based location. The latitude and longitude are then
calculated from the map and those coordinates are
used for determining if the player is within range.
In most urban and suburban situations, there are
sufficient landmarks (buildings and roads) for a player
to be able to accurately indicate on a map where they
are currently positioned. Problems may occur in parks
or in more rural areas where landmarks may not be
nearby.
Players may easily “game” the system using the pop-up
map during the capture of the mapped Floracaches
because the location will be easily remembered when
the pop-up map is triggered. Gaming the system is
more difficult in the two harder levels. Photo
verification is required during any floracache capture,
which may also reduce cheating.
Figure 3. Pop-ups used for refining
GPS location: (top) indication that a
player is close and (bottom)
touchable map that allows a radius
of possible adjustment, indicated by
a blue circle. The revised location
is indicated as a flag.

4. During a test of this manual solution for adjusting the
GPS-based location for finding a Floracache, 6
volunteers each attempted to capture 25 Floracaches
on the UCLA campus. Volunteers were instructed to
stand within 3 m of the plant and attempt to capture
the Floracache. Data on GPS-based location
performance is presented as successful or failed
captures (Table 1). Every volunteer needed to use the
manual adjustment at least once during the trial.
Results varied considerably depending upon the device
used. For example, one volunteer using a Motorola
Droid successfully captured all Floracaches and required
the manual location adjustment for 2 of the 25
attempted Floracache captures. However, a second
volunteer using a Samsung Vibrant, which is known to
have GPS sensor issues4
, required the manual
adjustment 36% of the time and completely failed to
capture 4 Floracaches due to inaccurate GPS-based
location beyond the 30 m limit for manual adjustment.
For all failed Floracache captures, the average GPS-
reported distance away the volunteer was located from
the Floracache was 43.8 ± 3.9 m, even though the
player was always within 3 m.
Conclusion
Games using on mobile phone GPS-based location may
be confounded in areas near buildings because of
inaccurately reported location. In order to not
discourage players in Citizen Science-related activities,
who may abandon the game if they initially encounter
such errors, manual adjustment of location may
provide a solution.
4
http://www.samsungvibrantforum.com
Acknowledgements
We thank all the volunteers who participated in testing
the Floracaching game and BudBurst Mobile application
and Sandra Henderson from Project BudBurst for
continued collaboration. We also thank the growing list
of people who have contributed to the BudBurst Mobile
Android and server code. Work was supported by NSF
grant #CNS-0627084.
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Location Adjustment
None After
Captured
75.2 ±
22.7%
18.2 ±
15.3%
Failed
6.5 ±
8.8%
0.5 ±
1.2%
Table 1. Average percentage of
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S.D.; n=25 Floracaches, 6 attempts
each).

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