Knowledge Annotations in Scientific Workflows: An Implementation in Kepler

Abstract

Abstract. 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.

The Identification Problem: A Description

“…In [9] scientific workflows are annotated. Enabling the re-utilisation of workflows and the documentation of the why and how of different scientific artefacts.…”

Search and result presentation in scientific workflow repositories

“…Related Work. Much effort [7,17,32] has been made recently to annotate scientific workflows to enable keyword search. As observed in [25], since scientific workflows are usually modeled as a three-dimensional graph structure when considering the expansions of composite modules (dashed edges in Figure 1), results on searching relational and XML data [5,24,35] or graph data [9,18,20,34] can not be easily extended.…”