# Scientific Workflows and Provenance: Introduction and Research Opportunities

arXiv: https://arxiv.org/abs/1311.4610 · HTML: https://mlsanity.com/paper/1311.4610/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Nov 2013.

## Built on by (most cited first, 1 of 1)

- [Silent Failures in Agent-Tool Interaction: An Audit of ToolUniverse](https://mlsanity.com/paper/2609.26836/) (2026)

## Abstract (arXiv)

Scientific workflows are becoming increasingly popular for compute-intensive and data-intensive scientific applications. The vision and promise of scientific workflows includes rapid, easy workflow design, reuse, scalable execution, and other advantages, e.g., to facilitate "reproducible science" through provenance (e.g., data lineage) support. However, as described in the paper, important research challenges remain. While the database community has studied (business) workflow technologies extensively in the past, most current work in scientific workflows seems to be done outside of the database community, e.g., by practitioners and researchers in the computational sciences and eScience. We provide a brief introduction to scientific workflows and provenance, and identify areas and problems that suggest new opportunities for database research.