Scientific and Statistical Database Management

Volume 6809 of the series Lecture Notes in Computer Science pp 189-206

Knowledge Annotations in Scientific Workflows: An Implementation in Kepler

  • Aída GándaraAffiliated withCyber-ShARE, The University of Texas at El Paso
  • , George ChinJr.Affiliated withPacific Northwest National Laboratory
  • , Paulo Pinheiro da SilvaAffiliated withCyber-ShARE, The University of Texas at El Paso
  • , Signe WhiteAffiliated withPacific Northwest National Laboratory
  • , Chandrika SivaramakrishnanAffiliated withPacific Northwest National Laboratory
  • , Terence CritchlowAffiliated withPacific Northwest National Laboratory

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Scientific research products are the result of long-term collaborations between teams. Scientific workflows are capable of helping scientists in many ways including collecting information about how research was conducted (e.g., scientific workflow tools often collect and manage information about datasets used and data transformations). However, knowledge about why data was collected is rarely documented in scientific workflows. In this paper we describe a prototype system built to support the collection of scientific expertise that influences scientific analysis. Through evaluating a scientific research effort underway at the Pacific Northwest National Laboratory, we identified features that would most benefit PNNL scientists in documenting how and why they conduct their research, making this information available to the entire team. The prototype system was built by enhancing the Kepler Scientific Workflow System to create knowledge-annotated scientific workflows and to publish them as semantic annotations.


Scientific Workflows Knowledge Annotations Kepler