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Fictitious Entries
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Fictitious Entries
Include minor deliberate errors in large reference content/data sets to help identify plagiarized work and copyright infringements. === What Problem This Solves === Third-parties are making your dataset available or using it without permission, and you can't prove that yours is the original. === When to Use This Pattern === Use this pattern when you have a valuable large set of reference data or content that can be copied and re-used without permission, and you need to protect it from wholesale copyright infringement === What's The Solution? === Include a deliberate error/entry in the dataset that can be proven incorrect; "''By including a trivial piece of false information in a larger work, it is far easier to demonstrate that someone has plagiarized that work: they will presumably copy the fictitious entry along with other articles.''" ([http://en.wikipedia.org/wiki/Fictitious_entry#Motivations_for_creation source]) === Why Use This Pattern === Data is a valuable commodity on the web, copyright infringement is rife, and digital data/content is simple to copy. Although fictitious entries may not be enough to prove ownership in a legal battle, the pattern remains a useful mechanism for detecting infringements. === References === #[http://en.wikipedia.org/wiki/Fictitious_entry Fictitious entries (Wikipedia)] === Examples Gallery === [[Image:Moat-lane-fictitious-entry.jpg|thumb|left|Moat Lane, North London: a fictitious entry (or Trap Street) in Google Maps data]]<br> === Categories<br> === [[Category:Lifecycle]]
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