Augmenting PROV with Plans in P-PLAN: Scientific Processes as Linked Data

نویسندگان

  • Daniel Garijo
  • Yolanda Gil
چکیده

Provenance models are crucial for describing experimental results in science. The W3C Provenance Working Group has recently released the PROV family of specifications for provenance on the Web. While provenance focuses on what is executed, it is important in science to publish the general methods that describe scientific processes at a more abstract and general level. In this paper, we propose P-PLAN, an extension of PROV to represent plans that guided the execution and their correspondence to provenance records that describe the execution itself. We motivate and discuss the use of P-PLAN and PROV to publish scientific workflows as Linked Data.

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تاریخ انتشار 2012