Replicable Services for Reproducible Research: A Model for Academic Libraries

Authors : Franklin Sayre, Amy Riegelman

Over the past decade, evidence from disciplines ranging from biology to economics has suggested that many scientific studies may not be reproducible. This has led to declarations in both the scientific and lay press that science is experiencing a “reproducibility crisis” and that this crisis has consequences for the extent to which students, faculty, and the public at large can trust research.

Faculty build on these results with their own research, and students and the public use these results for everything from patient care to public policy. To build a model for how academic libraries can support reproducible research, the authors conducted a review of major guidelines from funders, publishers, and professional societies. Specific recommendations were extracted from guidelines and compared with existing academic library services and librarian expertise.

The authors believe this review shows that many of the recommendations for improving reproducibility are core areas of academic librarianship, including data management, scholarly communication, and methodological support for systematic reviews and data-intensive research.

By increasing our knowledge of disciplinary, journal, funder, and society perspectives on reproducibility, and reframing existing librarian expertise and services, academic librarians will be well positioned to be leaders in supporting reproducible research.

URL : Replicable Services for Reproducible Research: A Model for Academic Libraries

DOI : https://doi.org/10.5860/crl.80.2.260

Data Management Practices in Academic Library Learning Analytics: A Critical Review

Author : Kristin A Briney

INTRODUCTION

Data handling in library learning analytics plays a pivotal role in protecting patron privacy, yet the landscape of data management by librarians is poorly understood.

METHODS

This critical review examines data-handling practices from 54 learning analytics studies in academic libraries and compares them against the NISO Consensus Principles on User’s Digital Privacy in Library, Publisher, and Software-Provider Systems and data management best practices.

RESULTS

A number of the published research projects demonstrate inadequate data protection practices including incomplete anonymization, prolonged data retention, collection of a broad scope of sensitive information, lack of informed consent, and sharing of patron-identified information.

DISCUSSION

As with researchers more generally, libraries should improve their data management practices. No studies aligned with the NISO Principles in all evaluated areas, but several studies provide specific exemplars of good practice.

CONCLUSION

Libraries can better protect patron privacy by improving data management practices in learning analytics research.

URL : Data Management Practices in Academic Library Learning Analytics: A Critical Review

DOI : https://doi.org/10.7710/2162-3309.2268