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Data is the key to understanding and solving challenges such as the loss of biodiversity, predicting recurring weather phenomena, or the fragmentation and loss of context of our cultural heritage. For this, vast amounts of data from many different sources need to be interpreted. Due to advances in computer power and the increasing availability of data spanning longer periods of time, historical data is becoming more important to include. Unfortunately, many AI tools are not well-suited to deal with this type of data and integrating contemporary and historical data streams is a complex problem. In this workshop, we bring together computer scientists, digital humanities researchers, and cultural heritage professionals to create a whitepaper detailing the challenges for AI-assisted integration of heterogeneous and asynchronous data streams from contemporary and historical sources.
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