Exploring business models for public open data resources : insights and recommendations from the data.europa.eu campaign : 2024 summary paper

This summary paper, Exploring Business Models for Public Open Data Resources, is the second of two papers aimed at fostering the engagement of the public sector as reusers of open data. It sheds light on the results from the 1-year campaign featuring a first scoping paper on new business models for open data, a data.europa.eu academy webinar and a focus group on how business models are applied to the public sector and open data specifically. It incorporates the insights from the campaign, draws conclusions and provides policy recommendations on how data.europa.eu can enable and stimulate the application of business models for open data by public institutions across Europe. It explores the transformative potential of open data in fostering innovation, economic growth and a competitive advantage in the modern economy. While the general value of open data - publicly available datasets that can be freely used, modified and shared - is recognised, the specific mechanisms for generating significant economic value remain largely unexplored. The European Union has promoted open data accessibility and reuse through initiatives like the open data directive and the digital Europe programme. However, technical, legal and cultural barriers need to be addressed to fully realise the benefits of open data. The paper addresses the critical need for business models that transform open data from a resource into a catalyst for economic growth. The research is guided by the following question. How can sustainable business models for open public sector data resources be established and supported to maximise value creation and reuse across national and local levels in Europe? To foster the development and application of business models for open data, the following policy recommendations are proposed. 1. Promoting an ecosystem approach. Encourage public-private partnerships and support intermediary organisations to bridge gaps between data providers and users. 2. Implementing support mechanisms for public institutions. Invest in data literacy and analytical skills, provide robust technological infrastructure and establish clear data governance frameworks. 3. Encouraging user-centric data publication strategies. Engage with data users to understand their needs, prioritise high-value datasets and ensure data quality and usability.