=Paper=
{{Paper
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|storemode=property
|title=
|pdfUrl=https://ceur-ws.org/Vol-640/paper3.pdf
|volume=Vol-640
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https://ceur-ws.org/Vol-640/paper3.pdf
Can we Trust Information? - The Case of
Volunteered Geographic Information
Mohamed Bishr1 and Krzysztof Janowicz2
1
m.bishr@uni-muenster.de
Institute for Geoinformatics, University of Muenster , Germany
2
jano@psu.edu
Department of Geography, The Pennsylvania State University, USA
Abstract. In this paper we take a fresh look at the problem of informa-
tion quality for user contributed content. We assert that the traditional
quality criteria for assessing the quality of geographic information are
difficult to apply to Volunteered Geographic Information. The notion of
informational trust is introduced and linked to the established notion of
interpersonal trust. We then propose to use informational trust and rep-
utation as proxy measures for information quality and outline the spatial
and temporal dimensions of trust that have to be considered.
1 Introduction
For the vision of a Digital Earth, user generated content is an essential repository
of up-to-date information ranging from maps and pictures, to local observations.
Such user generated geospatial information is collectively refered to as VGI [1].
However, its integration into Spatial Data Infrastructures, the Social Web, or
the Digital Earth comes at a price. As discussed in previous work [2], the volun-
tary contributors of such applications are not necessarily experts, have different
backgrounds, and varying motivations to contribute data. Therefore, not all pro-
vided information is valuable or may even be misleading. Given the tremendous
flow of VGI and the lack of knowledge about the traditional GI quality criteria
(completeness, lineage, accuracy, and consistency), the problem of information
quality is of increasing importance. To address these challenges, we proposed
trust as a potential proxy measure for the quality of geospatial information[2].
So far, most existing work on the notion of trust in social networks has ne-
glected the spatial and temporal dimension of trust and their implications on
user generated content. This paper outlines new insights on this proposal.
2 Trust and Reputation
Trust is a widely studied phenomenon, it has been a core resaerch topic in
sociology, political science, economics, philosophy, as well as computer science
[2–7]. In our discussion we refer to trust as a social phenomenon such as discussed
by Luhmann, Golembiewski, and others [8, 9]. In Sztompka [7], trust is defined
as a bet about the future contingent actions of others, which is also the definition
we adopt here. This definition has two components, belief and commitment. The
belief that a particular person will act in a favourable way and my commitment
to a certain action based on that belief. In this work, we particularly refer to
interpersonal trust [10] as a social tie between a trustor and a trustee.
Several researchers argue that trust holds only between people. Trusting a
company like Lufthansa to take you to your destination is, in fact, trusting the
people behind the company. Therefore, one could argue that trust in entities is
based on trust in the persons responsible for these entities. Following this ar-
gumentation, we propose the notion of people-object transitivity of trust which
differs from the trust transitivity commonly applied to Web-based social net-
works [6]. In our view, interpersonal trust implies the transition of trust from
the trustee to information entities conveyed by the trustee. The trustor can then
assert trust directly in the information conveyed by the trustee. We call this
informational-trust; where a trusting tie between a trustor and an information
entity such as VGI is mediated by interpersonal trust between the VGI originator
and the VGI consumer.
We further propose to extend this notion by spatial and temporal character-
istics of the trust phenomenon. In Buskens’ work [3] distance is used as a proxy
measure for social network density of buyers and suppliers’ networks. Partners in
proximity are always preferred partners [11], implying a higher degree of trust.
Buskens also asserts that the cost to the buyer as a result of abusing trust by
the trustee increases with distance. This means that the larger the distance the
more difficult it is to resolve problems which also leads to lower trust. A similar
conclusion is provided by Lyons [12] – distance has a positive effect on the prob-
ability of a subcontractor and a customer governing their relation by a formal
contract, such that the probability increases with distance, implying less trust.
A related explanation is provided by Lorenz [13], where the subjects indicated
that personal contact is important for establishing trust, and as such geographic
distance was necessary in easing this personal contact increasing trust with dis-
tance proximity. Also, it is intuitive to assert that trust decays and develops
over time, or that trust develops slowly, but can easily be tarnished if abused,
showing a temporal affinity to the concept of trust. Some researchers tried to
formalize this temporal effects on trust; see for example [14]. VGI is spatial and
temporal in nature - by extending the notion of trust with spatial and temporal
dimensions we can develop trust models that can be used for filtering and triage
of VGI and provide higher quality information to consumers.
Finally we briefly address the notion of reputation and relate it to trust. We
view reputation as the perception of trustworthiness of a person by a commu-
nity [15]. Reputation of a person does not belong to that person, but to the
community. It depends on many factors including previous behavior, commu-
nity perception of the person, the capacity of the community to sanction bad
behavior, and propagation through word of mouth. Reputation can then be used
to assert the degree of trust to be placed in a person. This is achieved because
reputation helps a trustor assess how likely is the trustee to honour trust. As
such, reputation is an additional factor in determining the trust of VGI.
3 Informational trust as a proxy measure of information
quality
In fact we have no objective measures of the accuracy of, say, google’s search
results and hardly any benchmarks to compare to, yet people continue to rely
on google. Our argument here is that the quality of google’s results is assessed
based on whether or not it fits the purpose of the users at a given time. This is an
intuitive assessment that most of us make in such a situation. Hence, information
quality always depends on the current context, e.g., a problem that needs to be
solved. If a larger group of people find some VGI fit for their purpose we can
assert that this VGI is of higher quality compared to others (at least for the
given purpose). The volunteers providing VGI can then act as markers for the
quality of their contributions. They mediate between the VGI consumers and
the consumed VGI so that if person A can identify the VGI contributor B as
having a reputation of being trustworthy, then A can assert that the VGI by B is
itself trustworthy. This does not contradict our theoretical understanding of trust
given the earlier discussion in section 2 on our proposed notion of informational
trust.
This process requires spatial and temporal aspects of trust and reputation
models for VGI triage. In previous work [16, 17], we have discussed models for
VGI quality assessment based on the spatial and temporal notion of trust and
reputation. The spatial and temporal dimensions of informational trust can be
used to make assertions such as that people in proximity of VGI observations
provide more accurate information (e.g. the locals know better, the proximate
spectator sees more, and so on) or that the trust in some VGI develop and
decay over time. One can postulate someone contributing VGI about a significant
change in her local urban area, and intuitively assume that her location (with
respect to the changed entity) as well as the observation time affect the trust we
might vest in her observation.
4 Example and Discussion
Our previous work [17] demonstrates the integration of space into the informa-
tional trust models. This model, however, does not include a temporal dimension.
The use case for the model is that of a newly urbanized area in Muenster, Ger-
many where we postulate that the urban modellers will depend on VGI to collect
information about urban growth volunteered by the local residents. The local
residents carry hand-held devices that can log their position while making obser-
vations about their urban environment. The system also stores social relations
between the residents where they assign trust ratings to each others in a social
network of contributors.
During reporting by volunteers the observed entities will naturally overlap.
So assume that volunteers n2 and n6 in figure 1 are making two separate obser-
vations, e.g. n2 observes that in this location a new building is being constructed,
let us call this observation m1a and n6 later makes another observation about
the same location with the same conclusion, let us call this observation m1b .
The system uses proximity of the location put by the volunteer on the map
and then suggests to the volunteer n6 that m1 a and his own observation m1b
might be identical. If the user confirms that both are identical, both m1a and
m1b are amalgamated so that the observed event m1 is recorded in the system
and is counted as reported twice by volunteers n2 and n6 . The resulting network
model is a hybrid model of a bipartite graph between volunteers and their con-
tributed observations about urban development and a social network among the
volunteers, see figure 1.
Fig. 1. An affiliation network of volunteers N and the VGI they contribute M with
links between a volunteer and VGI entities weighted by distance between the volun-
teers and the observed entity’s actual location. Links connecting N white nodes are a
separate agent-agent social network, making this model a hybrid affiliation-one mode
social network.
Equation 1 is one part of the trust model presented in previous work [17]
and used here to demonstrate the basic assumptions underlying our model. The
trust ratings of a member of M is denoted tmh and is computed by the given
equation where tng is the specific trust associated with a given volunteer. This
tng is computed through the model in earlier equations using trust ratings on
the social network and acts as an indicator of user reputations. While r(n,m)i
is the ith rating from one n to another m. Then the equation is weighted by
the distance ci using a log function to smooth the sharp variations resulting
from using raw distance. The resulting rating tmh is a rating of how much some
amalgamated observation m is to be trusted and is then used to sift through
the VGI entities and curate them by which ones are more trustworthy than
others. It is to be noted that trust ratings on a social network can be biased, so
that friends would rate each others higher regardless of the actual quality of the
contributions. This is a risk that needs to be mitigated in the system by opening
ratings of people to all other people in the social network to create a reputation
effect. Hence, the group dynamics resulting in overall user reputations would
make the system more resilient to individual biases.
k
� tng r(n,m)i
tm h = where ci > 1 (1)
i=1,g=1
log ci
We also postulate that the integration of the temporal dimension in this
model will enable us to evaluate the VGI based on temporal currency of the
information. For example, if two observations by two different volunteers about
the same phenomenon contradict each others then two scenarios could be pos-
sible: first, the time difference between both observations is sufficiently large
that the phenomenon could have potentially changed, or secondly the time dif-
ference is sufficiently small as to warrant doubt on the trustworthiness of one
or both observations. The temporal dimension is added in analogy to the spa-
tial distance presented in equation 1, and will require that we know how both
the spatial and the temporal distance interact. This needs to be determined by
human participants tests and simulations and is ongoing work.
We conclude by stating that the temporal and spatial dimensions then can
lead to a multitude of innovative trust and reputation solutions for VGI. To
elucidate, let us assume that in the presented examples some disaster or emer-
gency arises in the study area. In this case through the integration of the spatial
and temporal dimensions we can infer a new form of reputation which we call
event-reputation of volunteers using distance and time. In this case distance and
time become very important so that a volunteer close to an event (spatial di-
mension) at the time of the disaster’s occurrence (temporal dimension) is given
an event-reputation for a given period of time concerning reporting about this
event. This event-reputation is not only ephemeral, but can also be extended
further given crowed feedback on the quality of the reports from this particular
volunteer through the course of the disaster to make it a permanent reputation
for this volunteer about a certain local area.
5 Conclusions
In this paper we revisited our earlier proposal of using trust as a proxy measure
of the quality of user contributed content. Beyond the earlier proposal this pa-
per introduces the notion of informational trust as a derivative of interpersonal
trust. This approach resolves the ontological conflicts about the nature of trust
as a social tie and trust in information like VGI. We then extended this notion
of trust by a spatial and temporal dimension. One implication of this is that the
location of volunteers with respect to the observed phenomena in VGI impacts
the informational trust of their observations. The temporal dimension of infor-
mational trust plays a similar role where the time between different observations
of volunteers impacts informational trust.
6 Acknowledgements
The authors of this paper would like to thank Werner Kuhn for coining the
term proxy measure of quality as a way to describe the basic premise of this
work. We also thank Simon Scheider for his insightful suggestion on the notion
of informational trust. Some of the ideas in this paper were inspired through
a brief email exchange with some members of SwiftRiver and Ushahidi project
team.
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