Using Domain Requirements to Achieve Science-Oriented Provenance

Abstract

Abstract. The US Department of Energy (DOE) Atmospheric Radiation Measurement Program (ARM) is adopting the use of formalized provenance to support observational data products produced by ARM operations and relied upon by researchers. Because of the diversity of needs in the climate community provenance will need to be conveyed in a domain-oriented context. This paper explores a use case where semantic abstract workflows (SAW) are employed as a means to filter, aggregate, and contextually describe the historical events responsible for the ARM data product the scientist is relying upon.

On the Use of Semantic Abstract Workflows Rooted on Provenance Concepts

“…Semantic Abstract Workflows (SAWs) are useful to encode process knowledge from the perspective of domain experts [1] and the Proof Markup Language (PML) is useful to encode justifications about how information is produced [2]. This paper describes the integration of SAWs and PML, which results in two benefits: 1) Given that determining an adequate level of granularity to encode provenance is challenging [3], i.e, provenance at a very fine level may not be scalable and provenance at a very coarse level may not be useful, process knowledge captured from the perspective of domain experts serves as a guide to determine an adequate level of granularity; 2) Provenance languages such as PML utilize specialized terminology that may be unfamiliar to end users. The integration of these technologies has the benefit of having domain-specific terminology used to refer to a domain expert's understanding of a process that can be propagated to refer to provenance knowledge as well.…”