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Provenance of Adaptation in Scientific and Business Workflows -- Literature Review

Ludwig Stage, Julia Dahlberg, Dimka Karastoyanova

TL;DR

This literature review surveys provenance in scientific and business workflows with a focus on provenance of adaptation. It analyzes how provenance is captured, used, and visualized, and evaluates existing tools and standards. The study finds a gap in support for adaptation-related provenance (especially ad-hoc provenance) and notes that most work centers on reproducibility, with limited integration across workflow management systems. It concludes that advancing an integrated framework for capturing, storing, and visualizing adaptation provenance is essential for robust reproducibility and trust in adaptive workflows.

Abstract

In the world of science new technology have opened up the possibility to rely on advanced computational methods and models to conduct and produce scientific research. An important aspect of scientific and business workflows is provenance - which refers to the information describing the production, history or lineage of an end product, which can also be data, digitalized processes and other not tangible artifacts. While there are already systems, tools and standards to capture provenance of data and workflows the provenance of adaptations/changes in workflows has not been addressed yet. In this paper we carry out a literature review to establish the state of the art on this topic and present our methodology and findings. Our findings confirm that provenance of adaptation has not been addressed adequately in the fields of business and scientific workflows. The two fields also have different motivation for recording the lineage of data or processes. While scientific workflows are interested in reproducibility and visualization, business workflows solutions are indirectly connected to compliance, exception handling and analysis. The adaptive nature of workflows in both fields is not reflected in the research on process provenance yet, as our results show. The use of standard provenance standards is also not wide spread.

Provenance of Adaptation in Scientific and Business Workflows -- Literature Review

TL;DR

This literature review surveys provenance in scientific and business workflows with a focus on provenance of adaptation. It analyzes how provenance is captured, used, and visualized, and evaluates existing tools and standards. The study finds a gap in support for adaptation-related provenance (especially ad-hoc provenance) and notes that most work centers on reproducibility, with limited integration across workflow management systems. It concludes that advancing an integrated framework for capturing, storing, and visualizing adaptation provenance is essential for robust reproducibility and trust in adaptive workflows.

Abstract

In the world of science new technology have opened up the possibility to rely on advanced computational methods and models to conduct and produce scientific research. An important aspect of scientific and business workflows is provenance - which refers to the information describing the production, history or lineage of an end product, which can also be data, digitalized processes and other not tangible artifacts. While there are already systems, tools and standards to capture provenance of data and workflows the provenance of adaptations/changes in workflows has not been addressed yet. In this paper we carry out a literature review to establish the state of the art on this topic and present our methodology and findings. Our findings confirm that provenance of adaptation has not been addressed adequately in the fields of business and scientific workflows. The two fields also have different motivation for recording the lineage of data or processes. While scientific workflows are interested in reproducibility and visualization, business workflows solutions are indirectly connected to compliance, exception handling and analysis. The adaptive nature of workflows in both fields is not reflected in the research on process provenance yet, as our results show. The use of standard provenance standards is also not wide spread.

Paper Structure

This paper contains 22 sections, 2 figures, 7 tables.

Figures (2)

  • Figure 1: Workflow Provenance types taxonomy id:20_herschel_2017id:17_2023id:6_LACK_2023
  • Figure 2: Use cases in the literature