As our digital world continues to shift, "openness" has grown into something far bigger than just sharing open-source code and data. Open Knowledge Ecosystems: Governance, Standards, AI and Ethics breaks down how open data, clever technical standards, and AI are reshaping how we share and put knowledge to work today. Whether your focus is computer science, public policy, or business, this collection connects technology, real-world practice, and ethical choices. You will get a clear look at the tools powering modern data systems, including open-source Large Language Models and Data Lakehouses, and see how people use them to make government data truly practical and accessible. At the same time, it looks well beyond code and data pipelines. The authors dive into the messy realities, ethical calls, and political questions behind open data. You will tackle issues like "openwashing", where organizations claim to be open while keeping key details out of reach, and look at what responsible data governance actually takes. Real-world case studies bring it all together, showing how AI, tailored data tools, and open standards operate across public administration, healthcare, and education. Designed as an approachable guide for students, researchers, and future digital leaders, this book gives you both the context and the practical insight needed to help shape where open data goes next. What You Will Find Inside: ¿ Real context analysis on how semantic standards and open systems developed, alongside a direct look at challenges like openwashing. ¿ Practical tech insights on how open-source LLMs and modern data architectures operate in practice. ¿ Ethical and responsible ways to build trustworthy AI and handle sensitive data carefully, especially in domains like health and education.
