B
! !
C
Building networks and building the experiment
After an experiment got in step A a ‘ Go !’ and an initial vision has been drafted , step B moves into the challenge of building up a network surrounding the experiment . This can be done by , for instance , by publishing the vision document , writing out a tender or by actively engaging with promising actors . The scope of partners is broad and inclusive : the living lab should serve as a platform for cooperation between public actors , universities , civil society actors , NGOs and private companies . This inclusion of a wide set of actors ensures rich perspectives on a good setup and to work further upon . The enrolment of more actors is an on-going process of expanding the resource base and injecting new ideas and innovative approaches to the already settled expectations and visions .
Once a thorough and defined actor network has formed around the experiment , questions such as “ who contributes with what ?” can be addressed and contracting can be started . This includes also explicating a refined set of goals , setting up a monitoring and evaluation scheme , planning how to expand the experiment , and making connections to other experiments . Once the framework is set , the exciting process of building the experiment can start . This entails many obstacles ; but instead of seeing them as blockades , they could be turned 180 ° and seen as possibilities for engaging in the city with innovative experiments .
Collecting learning processes
While building and running the experiment , many loops of feedback are generated in parallel . To gather these , draw relevant learnings from them , and where necessary , adjust the experiment accordingly , is often one of the hardest steps of all . And sometimes failing delivers even better learning goals , when diagnosing accurately and in time what is going wrong . A monitoring and evaluation scheme , which ensures that goals are reached and the experiment is developing on its various dimensions , is therefore a ‘ must ’ and should be designed very carefully . It will help all stakeholders to develop a good understanding of how the experiment performs best .
Here , the advantages of drawing on a rich network of actors play out strong ; e . g . partners from universities can perform an important part of the evaluation and use it to create new knowledge . Learning won ’ t stop at insights about the experiment itself . The notion of ‘ collecting ’ refers also to the monitoring system of the living laboratory ( phase 6 and 7 in part one ) and ensuring thereby learnings about the mobility system , and the users within , on a higher level .
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