We propose a new way to represent data, information and, in particular, assertions in the form of nanopublications. A nanopubli- cation is essentially the smallest unit of publication: a single assertion, associating two concepts by means of a predicate in machine- readable format with proper metadata on provenance and context.
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Nanopublications support in silico knowledge discovery, tapping massive treasures of implicit information
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When reasoning over the associations represented in such a computer readable set of assertions a scientist may have reason to check—even to doubt—any particular assertion, in the graph. Ideally, the list of underpinning articles and other data sources supporting that claim should be just a click away, enabled by the nanopublication provenance. The researcher can now judge the validity of the claim in question much better by reading the articles than by trying to judge a rhetoric argument that is painfully distorted into machine-readable format.
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The provenance-linked nanopublications have the potential to increase the conventional cita- tion rate of the article and database as well as provide the potential for microattribution.