Provenance Research Line

Summary:

The Provenance research in our group places emphasis on enabling the provenance of data and computation logic adaptation. Our research work is on defining and developing the necessary concepts and realization technologies to support reproducibility and provenance of adaptation in computing systems and applications, the data they are using and related information. There are several sub-topics we address:

• Provenance of Adaptive Trusted Choreographies
• Provenance of Data and Code Change in data processing pipelines
• Architecture of Flexible Information Systems with Built-in Provenance Support
• Provenance models and visualization applied for social network data analysis

Participants

• Dimka Karastoyanova
• Mirela Riveni
• Ludwig Stage
• Students:
  • Edser Apperloo: MSc Thesis Tracking provenance of change in data science pipelines. Focus on tracking evolution of code and configuration.
  • Mark Timmerman: MSc Thesis Tracking provenance of change in data science pipelines. Focus on tracking evolution of data.
  • Andrei Stoica

Publications

• Karastoyanova, D., & Stage, L. (2019). Provenance Holder: Bringing Provenance, Reproducibility and Trust to Flexible Scientific Workflows and Choreographies. In Proceedings of Second Workshop on Security and Privacy-enhanced Business Process Management at BPM 2019 IEEE.
• Karastoyanova, D., & Stage, L. (2018). Towards Collaborative and Reproducible Scientific Experiments on Blockchain. 144-149. Paper presented at CAiSE 2018, Tallinn, Estonia. https://doi.org/10.1007/978-3-319-92898-2_12