Management and maintenance of research data by researchers in Zimbabwe | Emerald Insight

Abstract:  Purpose

The concept of research data management (RDM) is new in Zimbabwe and other developing countries. Research institutions are developing research data repositories and promoting the archiving of research data. As a way of creating awareness to researchers on RDM, the purpose of this paper is to determine how researchers are managing their research data and whether they are aware of the developments that are taking place in RDM.

Design/methodology/approach

A survey using a mixed method approach was done and an online questionnaire was administered to 100 researchers in thirty research institutions in Zimbabwe. Purposive sampling was done by choosing participants from the authors of articles published in journals indexed by Google Scholar, Scopus and Web of Science. Interviews were done with five top researchers. The data was analysed using NVIVO. The results were presented thematically. The questionnaire was distributed using the research offices of the selected 30 research institutions. There was a 75% response rate.

Findings

The findings indicated that all the researchers are aware of the traditional way of managing research data. A total of 70% of the respondents are not aware of the current trends in RDM services, as they are keeping their data on machines and external hard drives, while 97.3% perceive RDM services as useful, as it is now a requirement when applying for research grants. Librarians have a bigger role to play in creating awareness on RDM among researchers and hosting the data repositories for archiving research data.

Practical implications

Research institutions can invest in research data services and develop data repositories. Librarians will participate in educating researchers to come up with data management plans before they embark on a research project. This study also helps to showcase the strategies that can be used in awareness creation campaigns. The findings can also be used in teaching RDM in library schools and influence public policy both at institutional and national level.

Social implications

This study will assist in building capacity among stakeholders about RDM. Based on the findings, research institutions should prioritise research data services to develop skills and knowledge among librarians and researchers.

Originality/value

Few researches on RDM practices in Zimbabwe were done previously. Most of the papers that were published document the perception of librarians towards RDM, but this study focused mainly on researchers’ awareness and perception. The subject is still new and people are beginning to research on it and create awareness amongst the stakeholders in Zimbabwe.

Practices and Tools of Open Science

The series will be conducted online via Zoom. All are welcome to participate, and participation is free of charge. We do require participants to complete a brief registration via a Google Form. A Zoom link will be sent to you the evening before each scheduled event.

Who we are

The Leibniz Institute for Psychology (ZPID) is the supra-regional research support facility for psychology in German-speaking countries. PsyFaKo (Bundesfachschaftentagung der Psychologiestudierenden) is the representative body of all psychology students in the German-speaking countries.

Content recording

All sessions will be recorded and made available on PsychArchives approximately 2-3 weeks later, unless specifically requested otherwise by the session presenters.

 

Research Data Management Framework for Australian Universities Open for Consultation – ARDC

“Institutional Underpinnings is a collaborative project between 25 of Australia’s universities to develop a shared approach to university research data management in the form of a nationally-agreed framework.

The program aims to increase Australian universities’ capability in research data management and encourage collective problem-solving and alignment across the sector.

The draft Research Data Management Framework is now open for consultation. The Framework was developed by the 25 participating universities, with more than 90 experts contributing to working groups to identify and develop the key elements that are included….”

Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets

Open-source science builds on open and free resources that include data, metadata, software, and workflows. Informed decisions on whether and how to (re)use digital datasets are dependent on an understanding about the quality of the underpinning data and relevant information. However, quality information, being difficult to curate and often context specific, is currently not readily available for sharing within and across disciplines. To help address this challenge and promote the creation and (re)use of freely and openly shared information about the quality of individual datasets, members of several groups around the world have undertaken an effort to develop international community guidelines with practical recommendations for the Earth science community, collaborating with international domain experts. The guidelines were inspired by the guiding principles of being findable, accessible, interoperable, and reusable (FAIR). Use of the FAIR dataset quality information guidelines is intended to help stakeholders, such as scientific data centers, digital data repositories, and producers, publishers, stewards and managers of data, to: i) capture, describe, and represent quality information of their datasets in a manner that is consistent with the FAIR Guiding Principles; ii) allow for the maximum discovery, trust, sharing, and reuse of their datasets; and iii) enable international access to and integration of dataset quality information. This article describes the processes that developed the guidelines that are aligned with the FAIR principles, presents a generic quality assessment workflow, describes the guidelines for preparing and disseminating dataset quality information, and outlines a path forward to improve their disciplinary diversity.

Recommendations for Discipline-Specific FAIRness Evaluation Derived from Applying an Ensemble of Evaluation Tools

Abstract:  From a research data repositories’ perspective, offering research data management services in line with the FAIR principles is becoming increasingly important. However, there exists no globally established and trusted approach to evaluate FAIRness to date. Here, we apply five different available FAIRness evaluation approaches to selected data archived in the World Data Center for Climate (WDCC). Two approaches are purely automatic, two approaches are purely manual and one approach applies a hybrid method (manual and automatic combined).

The results of our evaluation show an overall mean FAIR score of WDCC-archived (meta)data of 0.67 of 1, with a range of 0.5 to 0.88. Manual approaches show higher scores than automated ones and the hybrid approach shows the highest score. Computed statistics indicate that the test approaches show an overall good agreement at the data collection level.

We find that while neither one of the five valuation approaches is fully fit-for-purpose to evaluate (discipline-specific) FAIRness, all have their individual strengths. Specifically, manual approaches capture contextual aspects of FAIRness relevant for reuse, whereas automated approaches focus on the strictly standardised aspects of machine actionability. Correspondingly, the hybrid method combines the advantages and eliminates the deficiencies of manual and automatic evaluation approaches. Based on our results, we recommend future FAIRness evaluation tools to be based on a mature hybrid approach. Especially the design and adoption of the discipline-specific aspects of FAIRness will have to be conducted in concerted community efforts.

Examining Wikidata and Wikibase in the context of research data management applications | TIB-Blog

For several months now, our team at the Open Science Lab has been working with Wikibase to provide research data management services for the NFDI4Culture community. We have already shown its advantages when it comes to real world data with a specific use case for architectural and art historical data [1, 2]. At the monthly NFDI InfraTalk last week, there was an interesting question at the end of the session regarding the potential of Wikidata to be used as an application for science and research. We take this as an opportunity to expand the answer to this question with some more details about Wikidata, its potential applications, its relation to standalone Wikibase instances, and what Wikibase can offer in its own right.

23 Scholarly Communication Things | QUT Library

23 Scholarly Communication Things by Queensland University of Technology is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License, except where otherwise noted.

 

Introduction

I. Foundations of Scholarly Communication

Research Integrity

Jennifer Hall; Eileen Salisbury; and Catherine Radbourne

Copyright and Creative Commons

Katya Henry; Rani McLennan; and David Cohen

Author Profiles

Paula Callan; Tanya Harden; and Brendan Sinnamon

II. Research Data Management

Managing research data

Philippa Frame

Publishing research data

Philippa Frame and Stephanie Jacobs

Licensing research data

Philippa Frame and Stephanie Jacobs

III. Open Access

Open Access organisations and developments – National and international

Sandra Fry

Open Access Models

Ginny Barbour; Paula Callan; and Stephanie Jacobs

Open Research

Alice Steiner

Open Educational Resources (OERs)

Katya Henry; Kate Nixon; and Sarah Howard

IV. Publishing

Which journal or book publisher to publish with

Paula Callan and Catherine Radbourne

Avoiding deceptive and vanity journals/conferences

Stephanie Jacobs; Catherine Radbourne; and Ginny Barbour

1. Persistent identifiers (PIDs)

Stephanie Jacobs; Paula Callan; Tanya Harden; and Brendan Sinnamon

Preprints, Preprint servers and Overlay journals

Ginny Barbour; Stephanie Jacobs; and Catherine Radbourne

Promoting research

Kate Harbison; Paula Callan; and Tanya Harden

V. Publication Metrics

Responsible use of metrics

Catherine Radbourne and Tanya Harden

Citation counts, author level metrics and journal rankings

Alice Steiner and Tanya Harden

Databases for metrics

Catherine Radbourne

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

Abstract:  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.

 

DataCite webinar – FORAGE: the hunt for existing data citations, Mar 17, 2022, 5 pm (CET)

Make Data Count (MDC) is a scholarly change initiative, made up of researchers and open infrastructure experts, building and advocating for evidence-based open data metrics. Throughout MDC’s tenure, various areas key to the development of research data assessment metrics have been identified. Please join a Spring seminar and discussion series centered around priority work areas, adjacent initiatives to learn from, and steps that can be taken immediately to drive diverse research communities towards assessment and reward for open data.

The first webinar titled “FORAGE: the hunt for existing data citations” will focus on the issue of finding and aggregating citations, how we can extend open citation initiatives to data, and how we can get known citations into a centralized open place.

Speakers include:
Julia Lane (Coleridge Initiative)
Silvio Peroni (Open Citations)
Carly Robinson (US Department of Energy, OSTI)
Stephanie van de Sandt (Vrije Universiteit Amsterdam)

The Open Handbook of Linguistic Data Management | MIT Press

Berez-Kroeker, McDonnell, Koller, and Collister (eds., 2022) The Open Handbook of Linguistic Data Management. The MIT Press.

A guide to principles and methods for the management, archiving, sharing, and citing of linguistic research data, especially digital data. “Doing language science” depends on collecting, transcribing, annotating, analyzing, storing, and sharing linguistic research data. This volume offers a guide to linguistic data management, engaging with current trends toward the transformation of linguistics into a more data-driven and reproducible scientific endeavor. It offers both principles and methods, presenting the conceptual foundations of linguistic data management and a series of case studies, each of which demonstrates a concrete application of abstract principles in a current practice.

Llebot | Why Won’t They Just Adopt Good Research Data Management Practices? An Exploration of Research Teams and Librarians’ Role in Facilitating RDM Adoption | Journal of Librarianship and Scholarly Communication

Abstract:  Adoption of good research data management practices is increasingly important for research teams. Despite the work the research community has done to define best data management practices, these practices are still difficult to adopt for many research teams. Universities all around the world have been offering Research Data Services to help their research groups, and libraries are usually an important part of these services. A better understanding of the pressures and factors that affect research teams may help librarians serve these groups more effectively. The social interactions between the members of a research team are a key element that influences the likelihood of a research group successfully adopting best practices in data management. In this article we adapt the Unified Theory of the Acceptance and Use of Technology (UTAUT) model (Venkatesh, Morris, Davis, & Davis, 2003) to explain the variables that can influence whether new and better, data management practices will be adopted by a research group. We describe six moderating variables: size of the team, disciplinary culture, group culture and leadership, team heterogeneity, funder, and dataset decisions. We also develop three research group personas as a way of navigating the UTAUT model, and as a tool Research Data Services practitioners can use to target interactions between librarians and research groups to make them more effective.

 

Wikidata for Digital Preservationists: New DPC Technology Watch Guidance Note now available on general release | Digital Preservation Coalition

The Digital Preservation Coalition (DPC) has made the next in its series of Technology Watch Guidance Notes, on Wikidata for Digital Preservationists by Katherine Thornton, available on general release today.

Wikidata for Digital Preservationists gives a brief introduction to Wikidata before continuing to provide practical advice on using, contributing, describing and curating data entries to enable storage and access to trusted data.

This new Technology Watch Guidance Note and the rest of the series complements the DPC’s popular Technology Watch Reports and is designed to be a ‘bite-sized’ paper that might contain information about a problem, a solution, or a particular implementation of digital preservation and will provide a short briefing on advanced digital preservation topics.

Attitudes and Experience of Sharing Research Data (survey targeted at UK-based researchers) | University of Nottingham

This survey aims to answer questions about researcher attitudes and experiences of sharing research data, and how these align to current research funder policies. Any researcher who is currently working in a UK context is encouraged to respond to the survey. This includes researchers in HE, governmental organisations, charities, and private industry or business sectors.

Understanding critical data literacy beyond data skills | Zenodo

Atenas, Javiera, Havemann, Leo, Khun, Caroline, & Timmermann, Cristian. (2021, August 3). Understanding critical data literacy beyond data skills. Zenodo. https://doi.org/10.5281/zenodo.5155667

Data literacy is normally understood as a set of abilities to read, understand, create, and communicate data as information. Much like literacy as a general concept, data literacy focuses on the competencies involved in working with data. 

However, data literacy can be also understood a mean to participate in the (datafied) society, thus the skills needed to work with data go beyond technicalities and have a strong social component, ergo, need to be grounded on the overarching principles of data ethics.

We suggest librarians and researchers get familiarised with a set of data skills that may help them work with data at management and research level, while being aware of the potential impact of data on individuals and the society, thus, handling data within an ethical and critical framework.