Digging into data management in public‐funded, international research in digital humanities

Authors : Alex H. Poole, Deborah A. Garwood

Path‐breaking in theory and practice alike, digital humanities (DH) not only secures a larger public audience for humanities and social sciences research, but also permits researchers to ask novel questions and to revisit familiar ones. Public‐funded, international, and collaborative research in DH furthers institutional research missions and enriches networked knowledge.

The Digging into Data 3 challenge (DID3) (2014–2016), an international and interdisciplinary grant initiative embracing big data, included 14 teams sponsored by 10 funders from four nations.

A qualitative case study that relies on purposive sampling and grounded analysis, this article centers on the information practices of DID3 participants. Semistructured interviews were conducted with 53 participants on 11 of the 14 DID3 projects.

The study explores how Data Management Plan requirements affect work practices in public‐funded DH, how scholars grapple with key data management challenges, and how they plan to reuse and share their data. It concludes with three recommendations and three directions for future research.

DOI : https://doi.org/10.1002/asi.24213

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


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.


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.


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.


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.


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