Information Technology Reference
In-Depth Information
Here, the users of the app reveal their location by giving informed consent, in turn
receiving information about the event they are visiting.
Whereas some promising solutions have been proposed for safeguarding user pri-
vacy in location-based services (LBS), in applications where the analysis of move-
ment data is the primary goal, much less convincing privacy handling prevails. CMA
must devise analytical frameworks that allow the inference of useful knowledge
but at the same time safeguard the privacy of the tracked people. Strategies include
anonymity
,
spatial
or
temporal degradation
,or
delay
(Krumm
2009
). Similar to
Laube et al. (
P11
.
2010
) where privacy was traded for quality of service in a LBS
scenario, CMA must develop techniques where quality of insights can be balanced
with the level of privacy.
5.5 Improving Recognition
So far, CMA remains a bit a “scientists' science”, comparable to modal jazz some-
times being called “musicians' music”, that is, music mainly for musicians and hence
inaccessible to non-musicians. Even though several community activities, including
a series of workshops
1
and even a EU-funded COST action (COST Action IC0903
MOVE) specifically aimed at bringing together methods and application scientists,
the prevailing pattern is that application experts from government and industry rarely
participate. Clearly, this is more than a challenge, this is an urgent problem to be
solved.
One way of improving the visibility and recognition of CMA as a research field,
is seeking publication of CMA work not only in GIScience outlets but also in related
fields such as core computer science, ecology, or transportation research. There is no
point in complaining that the established GIScience theory is ignored by computer
scientists “reinventingGIS” in the course of the rapid development of mobile ICT and
location-based apps. It is the responsibility of researchers active in GIScience (and
hence CMA) to seek the widest possible visibility. Clearly, close collaboration with
problem-driven application experts helps in producing work appealing to a wider
audience.
Second, and perhaps more difficult, is the establishment of one or two killer
applications underlining the socio-economic relevance of CMA. This is surely more
difficult as such success also depends on external constraints (for example, the estab-
lished GIScience concept LBS only became a commercial success when app-stores
became popular). Nevertheless, again only targeted collaboration on application-
close problems have the potential to produce such relevance in the first place.
1
Dagstuhl Seminars #08451 (2008), #10491 (2010) #12512 (2012), on Representation, Analysis
and Visualization of Moving Objects; First Workshop on Movement Pattern Analysis (MPA'10),
09/2010, Zurich, Switzerland; Workshop on Analysis and Visualization of Moving Objects, Lorentz
Centre, 06/2011, Leiden, NL; Workshop on Progress in Movement Analysis—Experiences with
Real Data, 09/2012, University of Zurich, Switzerland.
