Identifying and Implementing Relevant Research Data Management Services for the Library at the University of Dodoma, Tanzania

Authors : Gilbert Exaud Mushi, Heila Pienaar, Martie van Deventer

Research Data Management (RDM) services are increasingly becoming a subject of interest for academic and research libraries globally – this is also the case in developing countries.

The interest is motivated by a need to support research activities through data sharing and collaboration both locally and internationally. Many institutions, especially in the developed countries, have implemented RDM services to accelerate research and innovation through e-Research but extensive RDM is not so common in developing countries.

In reality many African universities and research institutions are yet to implement the most basic of data management services. We believe that the absence of political will and national government mandates on data management often hold back the development and implementation of RDM services. Similarly, research funding agencies are not yet applying sufficient pressure to ensure that Africa complies with the requirement to deposit research data in trusted repositories.

While the context was acknowledged the University of Dodoma library staff realized that it is urgent to prepare for the inevitable – the time when RDM will be a requirement for research funding support.

This paper presents the results of research conducted at the University of Dodoma, Tanzania. The purpose of the research was to identify and report on relevant RDM services that need to be implemented so that researchers and university management could collaborate and make our research data accessible to the international community.

This paper presents findings on important issues for consideration when planning to develop and implement RDM services at a developing country academic institution. The paper also mentions the requirements for the sustainability of these initiatives.

URL : Identifying and Implementing Relevant Research Data Management Services for the Library at the University of Dodoma, Tanzania


Publishing computational research — A review of infrastructures for reproducible and transparent scholarly communication

Authors : Markus Konkol, Daniel Nüst, Laura Goulier

Funding agencies increasingly ask applicants to include data and software management plans into proposals. In addition, the author guidelines of scientific journals and conferences more often include a statement on data availability, and some reviewers reject unreproducible submissions.

This trend towards open science increases the pressure on authors to provide access to the source code and data underlying the computational results in their scientific papers.

Still, publishing reproducible articles is a demanding task and not achieved simply by providing access to code scripts and data files. Consequently, several projects develop solutions to support the publication of executable analyses alongside articles considering the needs of the aforementioned stakeholders.

The key contribution of this paper is a review of applications addressing the issue of publishing executable computational research results. We compare the approaches across properties relevant for the involved stakeholders, e.g., provided features and deployment options, and also critically discuss trends and limitations.

The review can support publishers to decide which system to integrate into their submission process, editors to recommend tools for researchers, and authors of scientific papers to adhere to reproducibility principles.


Research Data Management in a Cultural Heritage Organisation

Author : Tom Drysdale

Research is a core function of cultural heritage organisations. Inevitably, the undertaking of research by galleries, libraries, archives and museums (the GLAM sector) leads to the creation of vast quantities of research data.

Yet despite growing recognition that research data must be managed if it is to be exploited effectively, and in spite of increasing understanding of research data management practices and needs, particularly in the higher education sector, knowledge of research data management in cultural heritage organisations remains extremely limited.

This paper represents an attempt to address the limited awareness of research data management in the cultural heritage sector. It presents the results of a data management audit conducted at Historic Royal Palaces (HRP) in 2018.

The study reveals that research data management at HRP is underdeveloped, while highlighting some causes for optimism.

The results of the study are compared to the results of similar studies conducted in UK higher education institutions (HEIs), highlighting the many discrepancies in the ways that research data is managed at HRP and in the HE sector.

Recognition of these differences and similarities, it is argued, is necessary for the development of better research data management practices and tools for the heritage sector.

URL : Research Data Management in a Cultural Heritage Organisation


Les données scientifiques face aux enjeux de la recherche en Sciences, Technologie et Médecine : enquête exploratoire à l’Université de Strasbourg

Auteur/Author : Violaine Rebouillat

Nous étudions la place des données scientifiques dans les pratiques de recherche à travers l’analyse de six projets du domaine des Sciences, Technologie, Médecine.

Il s’agit de questionner l’influence des stratégies de recherche sur la gestion et l’ouverture des données. Nous décrivons le rôle joué par la quête de reconnaissance par les pairs dans la recherche fondamentale et appliquée.

Nous montrons que les projets de recherche fondamentale tendent à suivre une logique, selon laquelle la publication d’articles dicte les priorités, tandis que les projets de recherche appliquée consacrent une attention plus grande aux données, en raison des enjeux économiques sous-jacents.


A study of the impact of data sharing on article citations using journal policies as a natural experiment

Authors : Garret Christensen, Allan Dafoe, Edward Miguel, Don A. Moore, Andrew K. Rose

This study estimates the effect of data sharing on the citations of academic articles, using journal policies as a natural experiment. We begin by examining 17 high-impact journals that have adopted the requirement that data from published articles be publicly posted.

We match these 17 journals to 13 journals without policy changes and find that empirical articles published just before their change in editorial policy have citation rates with no statistically significant difference from those published shortly after the shift.

We then ask whether this null result stems from poor compliance with data sharing policies, and use the data sharing policy changes as instrumental variables to examine more closely two leading journals in economics and political science with relatively strong enforcement of new data policies.

We find that articles that make their data available receive 97 additional citations (estimate standard error of 34).

We conclude that: a) authors who share data may be rewarded eventually with additional scholarly citations, and b) data-posting policies alone do not increase the impact of articles published in a journal unless those policies are enforced.

URL : A study of the impact of data sharing on article citations using journal policies as a natural experiment


Resurfacing Historical Scientific Data: A Case Study Involving Fruit Breeding Data

Authors : Shannon L. Farrell, Lois G. Hendrickson, Kristen L. Mastel, Katherine Adina Allen, Julia A. Kelly


The objective of this paper is to illustrate the importance and complexities of working with historical analog data that exists on university campuses. Using a case study of fruit breeding data, we highlight issues and opportunities for librarians to help preserve and increase access to potentially valuable data sets.


We worked in conjunction with researchers to inventory, describe, and increase access to a large, 100-year-old data set of analog fruit breeding data. This involved creating a spreadsheet to capture metadata about each data set, identifying data sets at risk for loss, and digitizing select items for deposit in our institutional repository.


We illustrate that large amounts of data exist within biological and agricultural sciences departments and labs, and how past practices of data collection, record keeping, storage, and management have hindered data reuse.

We demonstrate that librarians have a role in collaborating with researchers and providing direction in how to preserve analog data and make it available for reuse. This work may provide guidance for other science librarians pursing similar projects.


This case study demonstrates how science librarians can build or strengthen their role in managing and providing access to analog data by combining their data management skills with researchers’ needs to recover and reuse data.

URL : Resurfacing Historical Scientific Data: A Case Study Involving Fruit Breeding Data


“Data Stewardship Wizard”: A Tool Bringing Together Researchers, Data Stewards, and Data Experts around Data Management Planning

Authors: Robert Pergl, Rob Hooft, Marek Suchánek, Vojtěch Knaisl, Jan Slifka

The Data Stewardship Wizard is a tool for data management planning that is focused on getting the most value out of data management planning for the project itself rather than on fulfilling obligations.

It is based on FAIR Data Stewardship, in which each data-related decision in a project acts to optimize the Findability, Accessibility, Interoperability and/or Reusability of the data.

The background to this philosophy is that the first reuser of the data is the researcher themselves. The tool encourages the consulting of expertise and experts, can help researchers avoid risks they did not know they would encounter by confronting them with practical experience from others, and can help them discover helpful technologies they did not know existed.

In this paper, we discuss the context and motivation for the tool, we explain its architecture and we present key functions, such as the knowledge model evolvability and migrations, assembling data management plans, metrics and evaluation of data management plans.

URL : “Data Stewardship Wizard”: A Tool Bringing Together Researchers, Data Stewards, and Data Experts around Data Management Planning