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Abstract

Digital technologies have fundamentally altered the nature of organizing innovation and production leading to open collaboration ecosystems. Individuals self-organize in open, voluntary technology-enabled collectives to share their enhancements to the data or collaborate on analyzing, disseminating, or leveraging the data for many applications, from enterprise computing to mobile, consumer oriented applications. ‘Big data’ is an increasingly important ‘engine’ to better understand the complex ‘nervous system’ of open collaboration. However, we need to equip open collaboration researchers with new datasets that span different contexts, as well as novel computational models and analytical techniques. In this paper, we will elaborate on research questions concerning open digital collaboration and derive the data analytical challenges that need to be addressed to answer these research questions.

4. Concluding remarks

This paper has outlined research directions in the field of open collaboration. The increasing availability of datasets documenting on-line collaborations is making possible to provide answers to many research questions on a quantitative basis. However, just making available such datasets is not enough. We need new network models, data transformation techniques, data linkage techniques, and novel pattern analysis techniques to make possible to extract meaningful knowledge from such data. Capturing finegrained and high quality interaction and collaboration data is also another important challenge that needs to be tackled. As part of our future work, we plan to design and prototype novel cyberinfrastructure platforms addressing such needs.