IEEE Technology and Society Magazine - Winter 2013 - 56

know which shop, museum,
library, or other building is
nearby. It also provides ratings
and comments to help users
determine the desirability of a
given site.
For local governments, the cost
of creating these three applications
was negligible; there is no way to
calculate what it would have cost
in time and financial resources if
the cities had needed to develop the
applications themselves.

Summary
Open Sensor datasets are startingto
be used in Open Data platforms.
This is something that can be sustained by the number of datasets that
are considered dynamic in the analyzed platforms, the Open Sensor
Data and the PublicData platforms.
Total numbers are for dynamic datasets 44 and 77, in front of the static
datasets, 110 to 17 000 respectively.
Of course now they seem meaningless, as the easiest thing to upload
into an Open Data platform is static
public data in a spreadsheet or pdf
document. The point is that with
projects like Open Cities we are
laying the foundation for increased
uploads of sensor data to public
Open Data platforms.
An example of an Open Sensor
Data platform based on open-source
code has been presented in this article. The success of its use has been
proved by launching a call for applications and measuring its impact.
An important social characteristic of Open Sensor Data is that it
will create new services that can be
shared among cities and regions,
thereby increasing the use and the
value of offering data in an open
way. The three examples shown here
in business, transport, and services
to the disabled, represent needs that
society will help develop through
crowdsourcing. we believe that they
represent a mechanism to innovate
and improve our day-to-day lives.
Today, we can only imagine
the revolution in Open Data as an

introduction to a real-time world
mashup with temperature, humidity, CO2 emission, transport, tourism attractions, events, water and
gas consumption, politics decisions,
emergencies, etc., and all of this
interacting with us to help improve
the future decisions we make in our
public and private lives.

Author Information
Albert Domingo, Boris Bellalta, Manuel Palacin, and Miquel
Oliver are with the Universitat
Pompeu Fabra, Barcelona, Spain.
Email:{name.surname}@upf.edu.
Esteve Almirall (Esteve.Almirall@esade.edu.) is with ESADE,
Barcelona, Spain.

Acknowledgment
The authors would like to thank
the Open Cities Project and its
entire consortium (Open Innovation mechanisms for Smart Cities, CIP-ICT-PSP-2010-4-270896).
This research has been partially
funded by CISNETS (Cooperative Intelligent Sensor Networks,
TEC2012-32354).

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IEEE TECHNOLOGY AND SOCIETY MAGAZINE

wINTEr 2013

https://www.twitter.com http://www.netflix.com/ http://www.w3.org/Tr/xlink11/ http://www.w3.org/ http://www.ckan.org http://www.acm.org/public http://red.gnoss.com/en/ http://http:// http://opencities.appcircus.com/competition/Open http://http:// http://www.publicdata.eu http://www.opencities.net https://www.xively.com

Table of Contents for the Digital Edition of IEEE Technology and Society Magazine - Winter 2013