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Our summer reading list: dive into the world of open data and more!

Discover eight insightful readings on open data, analytics, AI and more for your summer holidays

Whether you are traveling the world or enjoying the comforts of home, the summer holidays provide the perfect opportunity to finally finish that book and explore new stories. Are you looking for engaging reads? Data.europa.eu has compiled a list of eight insightful readings, including articles and books, to help you discover unique stories related to open data, analytics, AI and more!

  1. Open data and AI: A symbiotic relationship for progressData is a critical component of AI systems. This data story highlights the connection between open data and AI performance with real-life use cases.
  2. To promote collaboration and become truly data-driven, the City of Salinas aims to make data a central part of its operations. Read their success story published by to learn how they ensure up-to-date, relevant information is shared, contributing to increased transparency and more effectiveness.
  3. High-value datasets – tourism in the Tourism is a vital part of the ’s economy . Data can provide essential insights, which you will learn more about in this data story.
  4. Open data can support the physical infrastructure of cities to optimise transportation. Read this blog to find out how data sharing increases transparency, collaboration and efficiency, enabling smart city mobility.
  5. In this article, technology and science journalist Clive Thompson delves into the environmental impact of AI. He examines the water used to cool the large data centers required for training and operating the machines.
  6. Data and analytics can be used to increase competitiveness in sports, for example by spotting player injuries in real time. Read about this and the related security and privacy issues in the .
  7. Humans are seen as a data resource which can be converted into datasets and therefore impact the human subjects involved. Read this blog summarizing the challenges faced by human data subjects in computer vision datasets.
  8. High-value datasets – greenhouse gas emissions in the Learn how datasets on earth observation can support the , for example by tracking greenhouse gas emissions.

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