For decades good governance scholarship has focused attention on the importance of government openness [26], [34]. Since the 1960s, Freedom of Information (FOI) legislation has formed the backbone of institutional support for opening information and documents [76] and participatory processes [4], [79]. However, FOI represents a passive approach to releasing information. Persons or organizations must still request the information they want, referred to casually, as freedom of information requests. Since the 1990s, publishing documents on websites or using communication technologies to engage citizens in participation processes has signaled a more proactive approach to releasing government information and political engagement. Since 2003, governments have re-envisioned their passive and proactive approaches to include an open data agenda, [18], [62], where publishing documents and data in open formats, [35], [63] is the preferred way. Collectively, these developments have forged the basis for what has been commonly referred to as the open government and data movements [30]. Open data practices and policies are praised for their potential to generate public value, particularly through innovation, economic growth, and transparency, [5], [9], [18], [21], [81]. The nature and character of open data has been hailed for its innovative capacity and transformative power [19], [35], [40], [45], [80]. Various studies have confirmed that proactively releasing public and private data in open formats creates considerable benefits for citizens, researchers, companies and other stakeholders, such as business creation or having the ability to understand public or private problems in new ways through advanced data analytics, [5], [9], [18], [21], [81]. Only a handful of articles examine both the unintended consequences and negative side effects of opening data, [33] and the underlying causal mechanisms that actually lead to the desired open data benefits [5]. Open data research is still in its infancy, and as a result, the extant literature uses limited application and development of theory toward understanding the open data phenomenon. While scholars acknowledge diverse perspectives, it is not clear which theories are most relevant, nor whether a single or integrated theory is needed. This special issue is part of a series of two special issues about open data. This issue focuses on the relationship between innovation and open data, while the second special issue emphasizes research on open data related to transparency and open data policies. To realize the practical benefits of this transformative practice and to develop theory, more research needs to focus on understanding how innovation occurs through open data activities. The papers in this special issue begin to address this gap. The introductory article discusses the state-of-the-art with respect to understanding the context of open data innovation, developments, challenges and barriers, presents an overview of open data research and outlines emerging research directions.