Archives des mots-clés : research data management

Data Services Librarians’ Responsibilities and Perspectives on Research Data Management

Posté le par

Authors : Bradley Wade Bishop, Ashley M. Orehek, Christopher Eaker, Plato L. Smith

This study of data services librarians is part of a series of studies examining the current roles and perspectives on Research Data Management (RDM) services in higher education. Reviewing current best practices provides insights into the role-based responsibilities for RDM services that data services librarians perform, as well as ways to improve and create new services to meet the needs of their respective university communities.

Objectives

The objectives of this article are to provide the context of research data services through a review of past studies, explain how they informed this qualitative study, and provide the methods and results of the current study.

This study provides an in-depth overview of the overall job responsibilities of data services librarians and as well as their perspectives on RDM through job analyses.

Methods

Job analysis interviews provide insight and context to the tasks employees do as described in their own words. Interviews with 10 data services librarians recruited from the top 10 public and top 10 private universities according to the 2020 Best National University Rankings in the US News and World Reports were asked 30 questions concerning their overall job tasks and perspectives on RDM.

Five public and five private data services librarians were interviewed. The interviews were recorded and transcribed. The transcriptions were analyzed in NVivo using a grounded theory application of open, axial, and selective coding to generate categories and broad themes based on the responses using synonymous meanings.

Results: The results presented here provide the typical job tasks of data services librarians that include locating secondary data, reviewing data management plans (DMPs), conducting outreach, collaborating, and offering RDM training. Fewer data services librarians assisted with data curation or manage an institutional repository.

Discussion

The results indicate that there may be different types of data services librarians depending on the mix of responsibilities. Academic librarianship will benefit from further delineation of job titles using tasks while planning, advertising, hiring, and evaluating workers in this emerging area. There remain many other explorations needed to understand the challenges and opportunities for data services librarians related to RDM.

Conclusions

This article concludes with a proposed matrix of job tasks that indicates different types of data services librarians to inform further study. Future job descriptions, training, and education will all benefit from differentiating between the many associated research data services roles and with increased focus on research data greater specializations will emerge.

URL : Data Services Librarians’ Responsibilities and Perspectives on Research Data Management

DOI : https://doi.org/10.7191/jeslib.2022.1226

The research data life cycle, legacy data, and dilemmas in research data management

Posté le par

Authors : Jenny Bossaller, Anthony J. Million

This paper presents findings from an interview study of research data managers in academic data archives. Our study examined policies and professional autonomy with a focus on dilemmas encountered in everyday work by data managers.

We found that dilemmas arose at every stage of the research data lifecycle, and legacy data presents particularly vexing challenges. The iFields’ emphasis on knowledge organization and representation provides insight into how data, used by scientists, are used to create knowledge.

The iFields’ disciplinary emphasis also encompasses the sociotechnical complexity of dilemmas that we found arise in research data management. Therefore, we posit that iSchools are positioned to contribute to data science education by teaching about ethics and infrastructure used to collect, organize, and disseminate data through problem-based learning.

URL : The research data life cycle, legacy data, and dilemmas in research data management

DOI : https://doi.org/10.1002/asi.24645

Research data management and services: Resources for different data practitioners

Posté le par

Author : Gilbert Mushi

The emergence of data-driven research and demands for the establishment of Research Data Management (RDM) has created interest in academic institutions and research organizations globally.

Some of the libraries especially in developed countries have started offering RDM services to their communities. Although lagging behind, some academic libraries in developing countries are at the stage of planning or implementing the service. However, the level of RDM awareness is very low among researchers, librarians and other data practitioners.

The objective of this paper is to present available open resources for different data practitioners particularly researchers and librarians.

It includes training resources for both researchers and librarians, Data Management Plan (DMP) tool for researchers; data repositories available for researchers to freely archive and share their research data to the local and international communities.

A case study with a survey was conducted at the University of Dodoma to identify relevant RDM services so that librarians could assist researchers to make their data accessible to the local and international community.

The study findings revealed a low level of RDM awareness among researchers and librarians. Over 50% of the respondent indicated their perceived knowledge as poor in the following RDM knowledge areas; DMP, data repository, long term digital preservation, funders RDM mandates, metadata standards describing data and general awareness of RDM.

Therefore, this paper presents available open resources for different data practitioners to improve RDM knowledge and boost the confidence of academic and research libraries in establishing the service.

URL : Research data management and services: Resources for different data practitioners

DOI : https://doi.org/10.29173/iq995

To protect and to serve: developing a road map for research data management services

Posté le par

Authors: Andrea Chiarelli, Neil Beagrie, Lotte Boon, Ruth Mallalieu, Rob Johnson, Amy Warner May, Rowan Wilso

Research Data Management (RDM) has become a major issue for universities over the last decade. This case study outlines the review of RDM services carried out at the University of Oxford in partnership with external consultants between November 2019 and November 2020.

It aims to describe and discuss the processes in undertaking a university-wide review of services supporting RDM and developing a future road map for them, with a strong emphasis on the design processes, methodological approaches and infographics used. The future road map developed is a live document, which the consulting team handed over to the University at the end of the consultation process.

It provides a suggested RDM action plan for the University that will continue to evolve and be iterated in the light of additional internal costings, available resources and reprioritization in the budget cycle for each academic year.

It is hoped that the contents of this case study will be useful to other research-intensive universities with an interest in developing and planning RDM services to support their researchers.

URL : To protect and to serve: developing a road map for research data management services

DOI : http://doi.org/10.1629/uksg.566

Research data management systems and the organization of universities and research institutes: A systematic literature review

Posté le par

Author : Eva Katharina Donner

New technological developments, the availability of big data, and the creation of research platforms open a variety of opportunities to generate, store, and analyze research data. To ensure the sustainable handling of research data, the European Commission as well as scientific commissions have recently highlighted the importance of implementing a research data management system (RDMS) in higher education institutes (HEI) which combines technical as well as organizational solutions.

A deep understanding of the requirements of research data management (RDM), as well as an overview of the different stakeholders, is a key prerequisite for the implementation of an RDMS.

Based on a scientific literature review, the aim of this study is to answer the following research questions: “What organizational factors need to be considered when implementing an RDMS? How do these organizational factors interact with each other and how do they constrain or facilitate the implementation of an RDMS?”

The structure of the analysis is built on the four components of Leavitt’s classical model of organizational change: task, structure, technology, and people. The findings reveal that the implementation of RDMS is strongly impacted by the organizational structure, infrastructure, labor culture as well as strategic considerations.

Overall, this literature review summarizes different approaches for the implementation of an RDMS. It also identifies areas for future research.

URL : Research data management systems and the organization of universities and research institutes: A systematic literature review

DOI : https://doi.org/10.1177%2F09610006211070282

Do I Have To Be An “Other” To Be Myself? Exploring Gender Diversity In Taxonomy, Data Collection, And Through The Research Data Lifecycle

Posté le par

Authors : Ari Gofman, Sam A. Leif, Hannah Gunderman, Nina Exner

Objective

Existing studies estimate that between 0.3% and 2% of adults in the U.S. (between 900,000 and 2.6 million in 2020) identify as a nonbinary gender or otherwise gender nonconforming. In response to the RDAP 2021 theme of radical change, this article examines the need to change how datasets represent nonbinary persons and how research involving gender data should approach the curation of this data at each stage of the research lifecycle.

Methods

In this article, we examine some of the known challenges of gender inclusion in datasets and summarize some solutions underway. Using a critical lens, we examine the difference between current practice and inclusive practice in gender representation, describing inclusive practices at each stage of the research lifecycle from writing a data management plan to sharing data.

Results

Data structures that limit gender to “male” and “female” or ontological structures that use mapping to collapse gender demographics to binary values exclude nonbinary and gender diverse populations. Some data collection instruments attempt inclusivity by adding the gender category of “other,” but using the “other” gender category labels nonbinary persons as intrinsically alien.

Inclusive change must go farther, to move from alienation to inclusive categories. We describe several techniques for inclusively representing gender in data, from the data management planning stage, to collecting data, cleaning data, and sharing data.

To facilitate better sharing of gender data, repositories must also allow mapping that includes nonbinary genders explicitly and allow for ontological mapping for long-term representation of diverse gender identities.

Conclusions

A good practice during research design is to consider two levels of critique in the data collection plan. First, consider the research question at hand and remove unnecessary gendering from the data.

Secondly, if the research question needs gender, make sure to include nonbinary genders explicitly. Allies must take on this problem without leaving it to those who are most affected by it. Further, more voices calling for inclusionary practices surrounding data rises to a crescendo that cannot be ignored.

URL: Do I Have To Be An “Other” To Be Myself? Exploring Gender Diversity In Taxonomy, Data Collection, And Through The Research Data Lifecycle

DOI : https://doi.org/10.7191/jeslib.2021.1219

La gestion des données de la recherche agronomique : de la science ouverte à l’histoire des sciences

Posté le par

Auteur/Author : Guillaume Tuloup

L’Institut national de recherche pour l’agriculture, l’alimentation et l’environnement (INRAE) est engagé depuis plusieurs années dans le développement de la science ouverte.

Se positionnant aujourd’hui en fer de lance des mouvements d’ouverture, il œuvre à la rationalisation de la production, de la préservation et de la diffusion des données de la recherche afin de faire des sciences agronomiques des sciences impliquées, dans la société.

En effet, confrontée aux problématiques environnementales, sanitaires et alimentaires, la recherche agronomique est engagée dans une restructuration de la production des savoirs sur la nature et le vivant, à l’appui du numérique qui se fait environnement totalisant.

L’Institut étant particulièrement sensibilisé aux enjeux mémoriels et historiques, l’histoire des sciences peut restituer les conditions historiques de cette restructuration, en mobilisant elle-même les ressorts du numérique et de la science ouverte.

URL : La gestion des données de la recherche agronomique : de la science ouverte à l’histoire des sciences

Original location : https://www.enssib.fr/bibliotheque-numerique/notices/70173-la-gestion-des-donnees-de-la-recherche-agronomique-de-la-science-ouverte-a-l-histoire-des-sciences