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Buneman, P., & Tan, W.-C. (2019). Data provenance: What next. ACM SIGMOD Record, 47(3), 5–16. 
Resource type: Journal Article
BibTeX citation key: Buneman2019
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Categories: Artificial Intelligence, Cognitive Science, Computer Science, Data Sciences, Decision Theory, General, Mathematics, Medical science
Subcategories: Analytics, Big data, Decision making, Deep learning, Informatics, Machine learning, Psychology of human-AI interaction
Creators: Buneman, Tan
Publisher:
Collection: ACM SIGMOD Record
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Abstract
Research into data provenance has been active for almost twenty years. What has it delivered and where will it go next? What practical impact has it had and what might it have? We provide speculative answers to these questions which may be somewhat biased by our initial motivation for studying the topic: the need for provenance information in curated databases. Such databases involve extensive human interaction with data; and we argue that the need continues in other forms of human interaction such as those that take place in social media.
  
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