Using ReproZip for Reproducibility and Library Services


  • Vicky Steeves New York University
  • Rémi Rampin New York University
  • Fernando Chirigati New York University



Reproducibility, data management, repository management, digital libraries, digital archiving, software preservation


Achieving research reproducibility is challenging in many ways: there are social and cultural obstacles as well as a constantly changing technical landscape that makes replicating and reproducing research difficult. Users face challenges in reproducing research across different operating systems, in using different versions of software across long projects and among collaborations, and in using publicly available work. The dependencies required to reproduce the computational environments in which research happens can be exceptionally hard to track – in many cases, these dependencies are hidden or nested too deeply to discover, and thus impossible to install on a new machine, which means adoption remains low. In this paper, we present ReproZip , an open source tool to help overcome the technical difficulties involved in preserving and replicating research, applications, databases, software, and more. We will examine the current use cases of ReproZip , ranging from digital humanities to machine learning. We also explore potential library use cases for ReproZip, particularly in digital libraries and archives, liaison librarianship, and other library services. We believe that libraries and archives can leverage ReproZip to deliver more robust reproducibility services, repository services, as well as enhanced discoverability and preservation of research materials, applications, software, and computational environments.

Author Biographies

Vicky Steeves, New York University

Vicky Steeves is Librarian for Research Data Management and Reproducibility, Division of Libraries & Center for Data Science, New York University.

Rémi Rampin, New York University

Rémi Rampin is PhD Candidate, Tandon School of Engineering, New York University,. 

Fernando Chirigati, New York University

Fernando Chirigati is Research Engineer, Center for Data Science, New York University.




How to Cite

Steeves, V., Rampin, R., & Chirigati, F. (2017). Using ReproZip for Reproducibility and Library Services. IASSIST Quarterly, 42(1), 14.