Why do open data platforms Fail? – A revised conceptual model with mitigations actions

• Open data platforms face challenges and limitations that may lead to their failure. • Usability challenges and limitations are the most highlighted in the literature. • Technical limitations are the most critical when considering open data platforms. • Open data platforms should support operations effectively. Data is seen as a key driver for digital transformation. In this context, Open Data Platforms (ODP) have the potential to offer opportunities for the public, private, and civic sectors to connect and share information. Despite these platforms’ rapid proliferation, significant limitations and challenges associated with their use and development may jeopardise ODP’s effectiveness. There is a lack of studies exploring these platforms’ challenges and limitations. Moreover, mitigation actions are needed to reduce relieve the potential for failure of ODP. This research aims to understand why ODP fails, by conducting, a careful and comprehensive analysis, which included a systematic literature review, was performed to identify the critical challenges and limitations that may affect the performance of an open data platform. A conceptual model from the literature is updated with a categorization of the different limitations and challenges relating to ODP. This model groups the topics created by the researchers into five main categories of challenges and limitations: Technical, Institutional, End-users, Data quality, and Legislative. Furthermore, several mitigation actions were proposed to deal with each category of the model. By identifying these challenges and limitations and categorizing them, it is possible to understand the potential causes that impact the performance of an open data platform. Furthermore, by proposing different mitigation actions, this research aims to help deal with ODP’s challenges and limitations, contributing to preventing potential failures.