Anamaria Buda, Jolien Ubacht, Marijn Janssen, Robert-Jan Sips The open data trend is considered to be a robust driver for innovation. The expectation is that open datasets will stimulate benefits across a variety of sectors (public, private, academia etc.), such as greater transparency, innovation and the rise of new business models (European Commission, 2011; Davies, 2010). Although they are one of the primary users of governmental open datasets, private sector companies themselves are not very active yet in opening the massive amount of data they produce (Bonina, 2013; Herzberg 2014). A variety of barriers hold back this potential, such as privacy issues, data security, proprietary interests and data protectionism (Verhulst 2014, Ponte 2015). Therefore our objective was to develop a decision support framework that offers an overview of the various steps required for such an action, taking the barriers and the benefits into account. We followed a design science approach in which we conducted a literature review on the concept of business open data, performed an in-depth analysis of seven empirical case studies of well-known examples such as Nike, Syngenta and IBM, and we conducted expert interviews. We thus developed a prototype of the decision support framework, based on the concept of open data ecosystems (Heimstädt et al, 2014; Ponte, 2015). The framework was evaluated by high-level experts in the field. We not only identified the main business drivers for private sector companies to open up datasets, such as community building, promotion, business innovation, and new revenue streams. We also addressed the key challenges encountered by the private organizations.