A survey of research quality in core facilities

Survey of Core Facilities shows the importance of communication and management for optimal research quality

10.1101/2020.08.19.256511 ◽

2020 ◽

Author(s):

IC Kos-Braun ◽

B Gerlach ◽

C Pitzer

Keyword(s):

Management Practices ◽

Academic Research ◽

Research Process ◽

Research Quality ◽

Central Position ◽

Underlying Causes ◽

Research Standards ◽

Core Facilities ◽

First Contact ◽

Good Research

AbstractRecently, it has become evident that academic research faces issues with the reproducibility of research data. It is critical to understand the underlying causes in order to remedy this situation. Core Facilities (CFs) have a central position in the research infrastructure and therefore they are ideally suited to promote and disseminate good research standards through their users. However, there are currently no clear guidelines directly applicable to academic CFs. To identify the most important factors for research quality, we polled 253 CFs across Europe about their practices and analysed in detail the interaction process between CFs and their users, from the first contact to the publication of the results. Although the survey showed that CFs are dedicated to train and advise their users, it highlighted the following areas, the improvement of which would directly increase research quality: 1) motivating users to follow the advice and procedures for best research practice, 2) providing clear guidance on data management practices, 3) improving communication along the whole research process and 4) clearly defining the responsibilities of each party.

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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 ◽

10.7710/2162-3309.2321 ◽

2021 ◽

Vol 9 (1) ◽

pp. 2321

Author(s):

Clara Llebot ◽

Hannah Gascho Rempel

Keyword(s):

Data Management ◽

Management Practices ◽

Research Data ◽

Research Teams ◽

Research Data Management ◽

Good Research

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How Does One “Open” Science? Questions of Value in Biological Research

Science Technology & Human Values ◽

10.1177/0162243916672071 ◽

2016 ◽

Vol 42 (2) ◽

pp. 280-305 ◽

Cited By ~ 26

Author(s):

Nadine Levin ◽

Sabina Leonelli

Keyword(s):

Life Sciences ◽

Research Process ◽

Open Science ◽

Biological Research ◽

Research Practice ◽

Research Practices ◽

Wide Range ◽

Semistructured Interviews ◽

Key Questions ◽

Science Policies

Open Science policies encourage researchers to disclose a wide range of outputs from their work, thus codifying openness as a specific set of research practices and guidelines that can be interpreted and applied consistently across disciplines and geographical settings. In this paper, we argue that this “one-size-fits-all” view of openness sidesteps key questions about the forms, implications, and goals of openness for research practice. We propose instead to interpret openness as a dynamic and highly situated mode of valuing the research process and its outputs, which encompasses economic as well as scientific, cultural, political, ethical, and social considerations. This interpretation creates a critical space for moving beyond the economic definitions of value embedded in the contemporary biosciences landscape and Open Science policies, and examining the diversity of interests and commitments that affect research practices in the life sciences. To illustrate these claims, we use three case studies that highlight the challenges surrounding decisions about how––and how best––to make things open. These cases, drawn from ethnographic engagement with Open Science debates and semistructured interviews carried out with UK-based biologists and bioinformaticians between 2013 and 2014, show how the enactment of openness reveals judgments about what constitutes a legitimate intellectual contribution, for whom, and with what implications.

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Research data management practices of chemistry researchers in federal universities of technology in Nigeria

Digital Library Perspectives ◽

10.1108/dlp-06-2020-0051 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Fatimah Jibril Abduldayan ◽

Fasola Petunola Abifarin ◽

Georgina Uchey Oyedum ◽

Jibril Attahiru Alhassan

Keyword(s):

Data Management ◽

Management Practices ◽

Management Practice ◽

Research Process ◽

Management Plan ◽

Research Data ◽

Content Type ◽

Data Preservation ◽

Research Data Management ◽

Research Findings

Purpose The purpose of this study was to understand the research data management practices of chemistry researchers in the five specialized federal universities of technology in Nigeria. Appropriate research data management practice ensures that research data are available for reuse by secondary users, and research findings can be verified and replicated within the scientific community. A poor research data management practice can lead to irrecoverable data loss, unavailability of data to support research findings and lack of trust in the research process. Design/methodology/approach An exploratory research technique involving semi-structured, oral and face-to-face interview is used to gather data on research data management practices of chemistry researchers in Nigeria. Interview questions were divided into four major sections covering chemistry researchers’ understanding of research data, experience with data loss, data storage method and backup techniques, data protection, data preservation and availability of data management plan. Braun and Clarke thematic analysis approach was adapted, and the Provalis Qualitative Data Miner (version 5) software was used for generating themes and subthemes from the coding framework and for presenting the findings. Findings Findings revealed that chemistry researchers in Nigeria have a good understanding of the concept of research data and its importance to research findings. Chemistry researchers have had several experiences of irrecoverable loss of data because of poor choice of storage devices, back-up methods and weak data protection systems. Even though the library was agreed as the most preferred place for long-term data preservation, there is the issue of trust and fear of loss of ownership of data to unauthorized persons or party. No formal data management plan is used while conducting their scientific research. Research limitations/implications The research focused on research data management practices of chemistry researchers in the five specialized federal universities of technology in Nigeria. Although the findings of the study are similar to perceptions and practices of researchers around the world, it cannot be used as a basis for generalization across other scientific disciplines. Practical implications This study concluded that chemistry researchers need further orientation and continuous education on the importance and benefits of appropriate research data management practice. The library should also roll out research data management programs to guide researchers and improve their confidence throughout the research process. Social implications Appropriate research data management practice not only ensures that the underlying research data are true and available for reuse and re-validation, but it also encourages data sharing among researchers. Data sharing will help to ensure better collaboration among researchers and increased visibility of the datasets and data owners through the use of standard data citations and acknowledgements. Originality/value This is a qualitative and in-depth study of research data management practices and perceptions among researchers in a particular scientific field of study.

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Using normative ethics for building a good evaluation of research practices: towards the assessment of researcher’s virtues

Scientometrics ◽

10.1007/s11192-020-03658-4 ◽

2020 ◽

Vol 125 (2) ◽

pp. 1053-1075

Author(s):

Cinzia Daraio ◽

Alessio Vaccari

Keyword(s):

Social Practice ◽

Assessment Process ◽

Normative Ethics ◽

Research Practice ◽

Self Assessment ◽

Research Practices ◽

Good Evaluation ◽

Starting Point ◽

Good Research Practice ◽

Good Research

AbstractIn this paper, we propose the adoption of moral philosophy and in particular normative ethics, to clarify the concept of “good” evaluation of “research practices”. Using MacIntyre (1985)’s notion of a practice we argue that research is a form of social practice. As a result of this characterization, we claim that research practice typically requires three typologies of researcher: the leader, the good researcher and the honest researcher. Reflecting on what is a “good” research practice and on what is the role of researchers in it provides insight into some aspects of both the self-assessment process and how this promotes individual improvement. Moreover, this kind of reflection helps us to describe the functions (missions) of the research practices. A “good” evaluation should take into account all the building constituents of a “good” research practice and should be able to discriminate between good and bad research practices, while enforcing the functions of good research practices. We believe that these reflections may be the starting point for a paradigm shift in the evaluation of research practices which replaces an evaluation centred on products with an evaluation focused on the functions of these practices. In the last sections of the paper, we introduce and discuss an important aspect for the implementation of the proposed framework. This relates to the assessment of the virtues of researchers involved in a good research practice. Some examples of questions and preliminary items to include in a questionnaire for the assessment of Virtues in Research Practices are also provided.

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Between administration and research - Understanding data management practices in a mid-sized technical university

10.31235/osf.io/75ac6 ◽

2020 ◽

Author(s):

Stefan Reichmann ◽

Thomas Klebel ◽

Ilire Hasani-Mavriqi ◽

Tony Ross-Hellauer

Keyword(s):

Data Management ◽

Management Practices ◽

The State ◽

Data Sets ◽

Data Archiving ◽

Research Institution ◽

University Of Technology ◽

Data Collection And Analysis ◽

Administrative Task ◽

Good Research

Research Data Management (RDM) promises to make research outputs more transparent, findable, and reproducible. Strategies to streamline data management across disciplines are of key importance. This paper presents the results of an institutional survey (N=258) at Graz University of Technology, supplemented with interview data (N=18), to give an overview of the state-of-play of RDM practices across faculties and disciplinary contexts. RDM services are on the rise but remain somewhat behind leading countries like the Netherlands and UK, showing only the beginnings of a culture attuned to RDM. There is considerable variation between faculties and institutes with respect to data amounts, complexity of data sets, data collection and analysis, and data archiving. Data sharing practices within fields tend to be inconsistent. RDM is predominantly regarded as an administrative task, to the detriment of considerations of good research practice. Problems with RDM fall in two categories: Generic problems transcend specific research interests, infrastructures, and departments while discipline-specific problems need a more targeted approach. The paper extends the state-of-the-art on RDM practices by combining in-depth qualitative material with quantified, detailed data about RDM practices and needs. The findings should be of interest to any comparable research institution with a similar agenda.

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Data management and sharing: Practices and perceptions of psychology researchers

PLoS ONE ◽

10.1371/journal.pone.0252047 ◽

2021 ◽

Vol 16 (5) ◽

pp. e0252047

Author(s):

John A. Borghi ◽

Ana E. Van Gulick

Keyword(s):

Data Management ◽

Management Practices ◽

New Technologies ◽

Research Process ◽

Data Organization ◽

Scholarly Output ◽

Data Practices ◽

Data Collection And Analysis ◽

Human Participants

Research data is increasingly viewed as an important scholarly output. While a growing body of studies have investigated researcher practices and perceptions related to data sharing, information about data-related practices throughout the research process (including data collection and analysis) remains largely anecdotal. Building on our previous study of data practices in neuroimaging research, we conducted a survey of data management practices in the field of psychology. Our survey included questions about the type(s) of data collected, the tools used for data analysis, practices related to data organization, maintaining documentation, backup procedures, and long-term archiving of research materials. Our results demonstrate the complexity of managing and sharing data in psychology. Data is collected in multifarious forms from human participants, analyzed using a range of software tools, and archived in formats that may become obsolete. As individuals, our participants demonstrated relatively good data management practices, however they also indicated that there was little standardization within their research group. Participants generally indicated that they were willing to change their current practices in light of new technologies, opportunities, or requirements.

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Data Management and Sharing: Practices and Perceptions of Psychology Researchers

10.31234/osf.io/7g3ae ◽

2020 ◽

Author(s):

John Borghi ◽

Ana Van Gulick

Keyword(s):

Data Management ◽

Management Practices ◽

New Technologies ◽

Research Process ◽

Data Organization ◽

Scholarly Output ◽

Data Practices ◽

Data Collection And Analysis ◽

Human Participants

Research data is increasingly viewed as an important scholarly output. While a growing body of studies have investigated researcher practices and perceptions related to data sharing, information about data-related practices throughout the research process (including data collection and analysis) remains largely anecdotal. Building on our previous study of data practices in neuroimaging research, we conducted a survey of data management practices in the field of psychology. Our survey included questions about the type(s) of data collected, the tools used for data analysis, practices related to data organization, maintaining documentation, backup procedures, and long-term archiving of research materials. Our results demonstrate the complexity of managing and sharing data in psychology. Data is collected in multifarious forms from human participants, analyzed using a range of software tools, and archived in formats that may become obsolete. As individuals, our participants demonstrated relatively good data management practices, however they also indicated that there was little standardization within their research group. Participants generally indicated that they were willing to change their current practices in light of new technologies, opportunities, or requirements.

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