Open Collaborative Data as an Innovation Platform for Machine Learning Applications

The project aims to explore the potential of companies sharing data with others for machine learning , similar to sharing open source software. The cost of collecting, quality assuring and maintaining data is expected to rise and for data that does not contribute to competitive advantages, we mean that open data collaboration is a way to save costs and resources can be used to develop competitive and innovative aspects of company products and services, similar to the way open source software has revolutionized e.g. mobile world.

The project has three main parts:
1. A study of how sharing open data can be organized. We use Open Street Map as an example of how data is collected through different channels (crowdsourcing), organized, and used in various applications. We compare how open source communities work, such as Gerrit and Jenkins as we previously studied in Sony's Android Development.
2. A survey of Swedish companies and public sector needs for data for different machine learning applications, if open data collaboration can address these needs. The mapping takes place in the partners' business networks, as well as in collaboration with networks like Mobile Heights and Swedsoft.
3. A validation of the conclusions in the form of an open workshop

The project partners are suitable for the project through their combination of solid, applied research on open innovation and the availability of relevant corporate networks to investigate broadly the suitability of the employee for the Swedish business and public sector.