Data innovation arena
||Carl Magnus Olsson
||Carl Magnus Olsson
||Patrik Berander, Paul Davidsson, Sara Leckner och Johan Holmberg
||BTH Innovation, LTH, Media Evolution, Mobile Heights, Netport, Blekingetrafiken, Skånetrafiken, Karlshamns kommun, Lunds kommun, Malmö kommun, 4IT, All Binary, Ericsson, Fujitsu, HIQ, Odd Hill, Sony Mobile Communications, Telia Sonera, Trivector
||2014-08-01 -- 2016-08-25
||Internet of Things and People Research Centre
||Fakulteten för teknik och samhälle, Institutionen för datavetenskap
Through open-innovation processes in close dialogue with users, the Data Innovation Arena project develops prototypes for improving public transport and other public-sector services.
Two primary challenges are recognized in this project.
The first is to address the potential for data driven innovation that improves and strengthens the role of public transportation as an alternative to cars. The goal is to contribute towards an attractive and optimized public transportation which supports regional interaction with the users of this service. These users are invited to contribute through workshop discussions and assessments of new service alternatives. Actively being involved in such interaction should provide added value for users, in order to further promote involvement and contribution through data generation through the use of these new services.
The second is to identify obstacles that remain to design and offer data driven services. Some of these obstacles include legacy IT systems, varying degrees of quality and precision in data that is collected, additional needs for storage and cloud services, security and integrity questions, lack of standardized communication and platforms, lock-in solutions, closed APIs, underdeveloped business models, and lack of political and legal support for collaborative innovation through shared open data. The practice perspective of the project holds close collaboration between the partners to develop specific solutions to these challenges as central, and subsequently strive towards establishing potential for generalization and contribution towards open data driven innovation beyond the project scope.