A provenance framework for data-dependent process analysis

A Provenance Framework for Data-Dependent Process Analysis

A data-dependent process (DDP) models an application whose control flow is guided by a finite state machine, as well as by the state of an underlying database. DDPs are commonly found e.g., in e-commerce. In this paper we develop a framework supporting the use of provenance in static (temporal) analysis of possible DDP executions. Using provenance support, analysts can interactively test and ex...

A Software Framework for Data Provenance

Data provenance refers to the historical record of the derivation of the data, allowing the reproduction of experiments, interpretation of results and identification of problems through the analysis of the processes that originated the data. Data provenance contributes to the evaluation of experiments. This paper presents a framework for data provenance using the W3C provenance data model, call...

A Semiotics Framework for Analyzing Data Provenance Research

Balboa: A Framework for Event-Based Process Data Analysis

Software process research has suffered from a lack of focussed data analysis techniques and tools. Part of the problem is the ad hoc and heterogeneous nature of the data, as well as the methods of collecting those data. While collection methods must be specific to their data source, analysis tools should be shielded from specific data formats and idiosyncrasies. We have built Balboa as a bridge...

Sheer Curation of Experiments: Data, Process, Provenance

This paper describes an environment for the “sheer curation” of the experimental data of a group of researchers in the fields of biophysics and structural biology. The approach involves embedding data capture and interpretation within researchers' working practices, so that it is automatic and invisible to the researcher. The environment does not capture just the individual datasets generated b...