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have been short-lived, as caught criminals learn fast. Short after the police suc-
cessfully started to act on the hypothesized pattern, criminals adapted their modus
operandi, creating new patterns that were slow to appear through the analysis of
Police Report collections, if at all. Instead, criminal investigations, interrogation of
caught drug-traffickers, qualitative analysis of Police Reports (rather than statisti-
cal), and common sense (read: experience) led to new understandings of criminal
modus operandi. The result of the augmented reality experiment was that six from
the ten selected vehicles deemed 'worth inspection' contained more then 1kg
drugs - an unprecedented success for the Dutch police.
This being said, we do not claim that quantitative analysis of large data-
collections is ineffective or of minor importance. To the contrary. We assert, how-
ever, that it is far from sufficient. At most it is complementary. For example, in
the drug-trafficking case combining data sources and conducting social network
analyses shed light on parts of the organizational structure that would have been
overlooked otherwise (e.g. shared phone numbers, addresses, bank accounts). This
effort contributed to the success of the operations because the analysts collabo-
rated with the investigations team in a parallel fashion (Puonti 2007).
9.4.3 Developing an Ubiquitous Sensor-Network
As we have illustrated, augmented reality may already function with as few as 3 to
4 networked sensors. This augmented reality, however, can be extended substan-
tially if more sensors can be used. This is not a matter of buying and deploying
more sensors per se, as many (if not most) locations are already equipped with
suitable sensors. Most of these sensors are government-owned, but few are inter-
connected. As a consequence one may observe that many locations are equipped
with multiple systems, one for each governmental authority. We expect it to be a
matter of time and economical sense before these sensors become interconnected.
Rather than fighting the rear-guard, we suggest to start thinking about formulat-
ing access and use regulations. As food for thought we suggest one initial
measure. In contrast with current practice, in our view it would make sense to dis-
tinguish between the sensor, the data it produces, and the governmental authorities
that are allowed to use the data (preferably in a real-time fashion, as we did).
Where the format of the data and the physical location are determined by the sen-
sor, the data-stream may be managed in terms of activation period and retention-
time, while the use of the data by governmental authorities is determined by their
legal mandate.
The governing principles of proportionality, subsidiarity, and linkage between
ends and means (hereafter: the ruling juridical principles), rule out unrestricted ac-
cess to and use of the network. Indeed, the ruling juridical principles signify that
the means (i.e. mandates, resources, action) deployed by the police have to be
proportional in relation to the offense, that there are no other means available with
less impact, and that the means are deployed to reach a specified goal (e.g. restore
order, catch the criminal). These ruling juridical principles imply that the use of
means is always context-specific, never generic. Thus, when deploying a sensor-
network to augment reality to combat (a specific form of) crime, all sensors that
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