Workflow matching using semantic metadata

Abstract

Workflows are becoming an increasingly more common paradigm to manage scientific analyses. As workflow repositories start to emerge, workflow retrieval and discovery becomes a challenge. Studies have shown that scientists wish to discover workflows given properties of workflow data inputs, intermediate data products, and data results. However, workflows typically lack this information when contributed to a repository. Our work addresses this issue by augmenting workflow descriptions with constraints derived from properties about the workflow components used to process data as well as the data itself. An important feature of our approach is that it assumes that component and data properties are obtained from catalogs that are external to the workflow system, consistent with current architectures for computational science.

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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 18 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.