@inproceedings{01GMVAZ64ZBWZ98K07MPH656EF,
  abstract     = {{The world is complex and full of challenges. To overcome those challenges progress is needed. Progress is often facilitated by serendipity -- an unplanned and fortunate discovery. Luck, so to speak. But is it possible to plan serendipity? To remove the luck out of the equation? To simply find the information we need to overcome a challenge? The world is full of information. And it is becoming ever more. So much that it is impossible to look through all of it. We use machines to help with information discovery. They are good at connecting information, comparing facts, and structuring it as Knowledge Graphs. But machines are also shallow. They don't feel and think, don't understand human opinions and emotions. They only care about facts and throw away all the human complexities. The world is full of information, but machines don't understand half of it. They simply are not yet ready to help us. How do we make this hidden information visible? How do we make it searchable? Is it possible that the secret of serendipity lies in opinions and emotions? That there exists a hidden 'human graph' above the world of facts (KG)? A graph full of opinions and emotions, not understandable by machines? A graph that connects all the seemingly unrelated facts in a logical way? And we just need to follow it to find 'serendipity'? There already exist approaches to add annotations and metadata to existing KGs, for example property graphs and RDF*. But how do we describe opinions, how do we formalize emotions? Can RDF be used to construct a 'human graph'? To answer these questions, I will investigate how human opinions, emotions and complexities can be captured in KGs using RDF* and/or property graphs.}},
  author       = {{Steinbach, Jonas}},
  booktitle    = {{Faculty of Engineering and Architecture Research Symposium 2022 (FEARS 2022), Abstracts}},
  language     = {{eng}},
  location     = {{Ghent, Belgium}},
  pages        = {{1}},
  title        = {{Capturing human opinions, emotions and complexities with Knowledge Graphs}},
  url          = {{http://doi.org/10.5281/zenodo.7437935}},
  year         = {{2022}},
}

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