scholarly journals Curadoria de dados de pesquisa em repositórios de ensaios clínicos: uma revisão de escopo | Curating research data in clinical trial repositories: a scoping review

2019 ◽  
Vol 15 (2) ◽  
Author(s):  
Fabiana De Melo Amaral Gonçalves Pinto ◽  
Janaynne Carvalho Do Amaral ◽  
Melina De Brito Dos Santos
Keyword(s):  
Clinical Trial ◽  
Data Management ◽  
Open Science ◽  
Research Data ◽  
Science Data ◽  
Data Description ◽  
Research Data Management ◽  
Management Policies ◽  
Science Movement ◽  
Clinical Research Data

RESUMO O artigo investiga a prática da curadoria de dados de pesquisa em repositórios de ensaios clínicos. Propõe reflexões sobre a informação e seus múltiplos formatos no domínio da saúde e sugere uma definição para dados de pesquisa clínicos. Apresenta o conceito de curadoria de dados de pesquisa e fomenta novos estudos que priorizam a discussão sobre a gestão de dados de pesquisa e o movimento da Ciência Aberta no domínio da saúde. Aponta para a necessidade de implantação de políticas de gestão de dados de pesquisa que assegurem critérios de descrição, sistematização, compartilhamento, recuperação, interoperabilidade, preservação e reuso de dados. Como reflexão final, ressalta o desafio de discutir e implementar a prática de curadoria de dados de pesquisa produzidos por ensaios clínicos e evidencia o vasto e oportuno campo a ser explorado, tanto para pesquisadores quanto para profissionais da informação.Palavras-chave: Curadoria de Dados; Dados de Pesquisa; Ensaio Clínico; Ciência Aberta; Reuso de Dados.ABSTRACT The article investigates the practice of curating research data in clinical trial repositories. That proposes reflections on health information and its multiple formats and suggests the definition for clinical research data. It introduces the concept of research data curation and promotes new studies, which prioritize the discussion about research data management and the Open Science movement in the health domain. The article brings points to the need to implement research data management policies that ensure criteria for data description, systematization, sharing, retrieval, interoperability, preservation and reuse. As a final reflection, it highlights the challenge of discussing and implementing the practice of curating research data produced by clinical trials and highlights the vast and timely field to be explored for both researchers and information professionals.Keywords: Data Curator; Research data; Clinical Trial; Open Science; Data Reuse.Lista 

scholarly journals A collective challenge: Open Science from the perspective of Science Europe

2019 ◽  
Vol 72 (2) ◽  
pp. 424-430
Author(s):  
Marie Timmermann
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Open Science ◽  
Research Data ◽  
Major Research ◽  
Research Data Management ◽  
Management Policies ◽  
Good Research ◽  
Quality Of Research

Open Science aims to enhance the quality of research by making research and its outputs openly available, reproducible and accessible. Science Europe, the association of major Research Funding Organisations and Research Performing Organisations, advocates data sharing as one of the core aspects of Open Science and promotes a more harmonised approach to data sharing policies. Good research data management is a prerequisite for Open Science and data management policies should be aligned as much as possible, while taking into account discipline-specific differences. Research data management is a broad and complex field with many actors involved. It needs collective efforts by all actors to work towards aligned policies that foster Open Science.

scholarly journals Data Papers as a New Form of Knowledge Organization in the Field of Research Data

2019 ◽  
Vol 46 (8) ◽  
pp. 622-638
Author(s):  
Joachim Schöpfel ◽  
Dominic Farace ◽  
Hélène Prost ◽  
Antonella Zane
Keyword(s):  
Business Models ◽  
Open Science ◽  
Research Data ◽  
Data Driven ◽  
Academic Publishing ◽  
Science Data ◽  
Research Data Management ◽  
Fair Principles ◽  
New Form ◽  
Machine Readable

Data papers have been defined as scholarly journal publications whose primary purpose is to describe research data. Our survey provides more insights about the environment of data papers, i.e., disciplines, publishers and business models, and about their structure, length, formats, metadata, and licensing. Data papers are a product of the emerging ecosystem of data-driven open science. They contribute to the FAIR principles for research data management. However, the boundaries with other categories of academic publishing are partly blurred. Data papers are (can be) generated automatically and are potentially machine-readable. Data papers are essentially information, i.e., description of data, but also partly contribute to the generation of knowledge and data on its own. Part of the new ecosystem of open and data-driven science, data papers and data journals are an interesting and relevant object for the assessment and understanding of the transition of the former system of academic publishing.

scholarly journals VARIABILITY IN CLINICAL RESEARCH DATA MANAGEMENT PRACTICES: LESSONS FROM THE MALARIA COMMUNITY

2017 ◽  
Vol 2 (Suppl 2) ◽  
pp. A19.1-A19
Author(s):  
Amélie Julé ◽  
Hazel Ashurst ◽  
Laura Merson ◽  
Piero Olliaro ◽  
Vicki Marsh ◽  
...  
Keyword(s):  
Clinical Research ◽  
Data Management ◽  
Management Practices ◽  
Research Data ◽  
Research Data Management ◽  
Clinical Research Data

scholarly journals Challenges and Practices of Research Data Management in Selected Iraq Universities

2019 ◽  
Vol 39 (06) ◽  
pp. 308-314
Author(s):  
Mahdi Salah Mohammed ◽  
Rafea Ibrahim
Keyword(s):  
Data Management ◽  
Research Data ◽  
Faculty Members ◽  
Data Repositories ◽  
Postgraduate Students ◽  
Research Data Management ◽  
Research Findings ◽  
Management Policies ◽  
Research Organisations

Research emphasises the fundamental role of research data management (RDM) in enhancing academic and scientific research. This paper intended to examine RDM in Iraqi Universities, identify the current challenges of RDM and propose influential RDM practices. Data collection employed a self-administered questionnaires distributed to 155 postgraduate students and 20 faculty members from five universities in Iraq. Research findings revealed that there is a lack of proper RDM. Postgraduate students and researchers were managing their own research data. Main challenges of maintaining a good RDM involve lack of guidelines on effective RDM practices, insufficient of adequate human resources, technological obsolescence, insecure and inefficient infrastructure, lack of financial resources, absence of research data management policies and lack of support by institutional authorities and researchers negatively influenced on research data management. Postgraduate students and researchers recommend building research data repositories and collaboration with other universities and research organisations.

scholarly journals eLabFTW as an Open Science tool to improve the quality and translation of preclinical research

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 292
Author(s):  
Michael Hewera ◽  
Daniel Hänggi ◽  
Björn Gerlach ◽  
Ulf Dietrich Kahlert
Keyword(s):  
Data Management ◽  
Open Source ◽  
Academic Research ◽  
Open Data ◽  
Open Science ◽  
Research Data ◽  
Preclinical Research ◽  
Research Data Management ◽  
New Methods ◽  
Set Up

Reports of non-replicable research demand new methods of research data management. Electronic laboratory notebooks (ELNs) are suggested as tools to improve the documentation of research data and make them universally accessible. In a self-guided approach, we introduced the open-source ELN eLabFTW into our lab group and, after using it for a while, think it is a useful tool to overcome hurdles in ELN introduction by providing a combination of properties making it suitable for small preclinical labs, like ours. We set up our instance of eLabFTW, without any further programming needed. Our efforts to embrace open data approach by introducing an ELN fits well with other institutional organized ELN initiatives in academic research.

scholarly journals Plano de gestão de dados fair: uma proposta para a Fiocruz | Fair data management plan: a proposal for Fiocruz

2019 ◽  
Vol 15 (2) ◽  
Author(s):  
Viviane Santos de Oliveira Veiga ◽  
Patricia Henning ◽  
Simone Dib ◽  
Erick Penedo ◽  
Jefferson Da Costa Lima ◽  
...  
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Open Science ◽  
Management Plan ◽  
Research Data ◽  
Research Institutions ◽  
Research Data Management ◽  
Management Plans ◽  
Fair Principles

RESUMO Este artigo trás para discussão o papel dos planos de gestão de dados como instrumento facilitador da gestão dos dados durante todo o ciclo de vida da pesquisa. A abertura de dados de pesquisa é pauta prioritária nas agendas científicas, por ampliar tanto a visibilidade e transparência das investigações, como a capacidade de reprodutibilidade e reuso dos dados em novas pesquisas. Nesse contexto, os princípios FAIR, um acrônimo para ‘Findable’, ‘Accessible’, ‘Interoperable’ e ‘Reusable’ é fundamental por estabelecerem orientações basilares e norteadoras na gestão, curadoria e preservação dos dados de pesquisa direcionados para o compartilhamento e o reuso. O presente trabalho tem por objetivo apresentar uma proposta de template de Plano de Gestão de Dados, alinhado aos princípios FAIR, para a Fundação Oswaldo Cruz. A metodologia utilizada é de natureza bibliográfica e de análise documental de diversos planos de gestão de dados europeus. Concluímos que a adoção de um plano de gestão nas práticas cientificas de universidades e instituições de pesquisa é fundamental. No entanto, para tirar maior proveito dessa atividade é necessário contar com a participação de todos os atores envolvidos no processo, além disso, esse plano de gestão deve ser machine-actionable, ou seja, acionável por máquina.Palavras-chave: Plano de Gestão de Dados; Dado de Pesquisa; Princípios FAIR; PGD Acionável por Máquina; Ciência Aberta.ABSTRACT This article proposes to discuss the role of data management plans as a tool to facilitate data management during researches life cycle. Today, research data opening is a primary agenda at scientific agencies as it may boost investigations’ visibility and transparency as well as the ability to reproduce and reuse its data on new researches. Within this context, FAIR principles, an acronym for Findable, Accessible, Interoperable and Reusable, is paramount, as it establishes basic and guiding orientations for research data management, curatorship and preservation with an intent on its sharing and reuse. The current work intends to present to the Fundação Oswaldo Cruz a new Data Management Plan template proposal, aligned with FAIR principles. The methodology used is bibliographical research and documental analysis of several European data management plans. We conclude that the adoption of a management plan on universities and research institutions scientific activities is paramount. However, to be fully benefited from this activity, all actors involved in the process must participate, and, on top of that, this plan must be machine-actionable.Keywords: Data Management Plan; Research Data; FAIR Principles; DMP Machine-Actionable; Open Science.

scholarly journals Teaching Open Science

2020 ◽  
Author(s):  
Helene N. Andreassen ◽  
Erik Lieungh
Keyword(s):  
Open Access ◽  
Data Management ◽  
Teaching And Learning ◽  
Open Science ◽  
Research Data ◽  
Open Access Publishing ◽  
The Arctic ◽  
Learning Support ◽  
Research Data Management ◽  
The University

In this episode, we are discussing how to teach open science to PhD students. Helene N. Andreassen, head of Library Teaching and Learning Support at the University Library of UiT the Arctic University of Norway shares her experiences with the integration of open science in a special, tailor-made course for PhD's that have just started their project. An interdisciplinary, discussion-based course, "Take Control of Your PhD Journey: From (P)reflection to Publishing" consists of a series of seminars on research data management, open access publishing and other subject matters pertaining to open science. First published online February 26, 2020.

scholarly journals Laboratory Forensics for Open Science Readiness: an Investigative Approach to Research Data Management

2021 ◽  
Author(s):  
Armel Lefebvre ◽  
Marco Spruit
Keyword(s):  
Data Management ◽  
Information Quality ◽  
Open Science ◽  
Research Data ◽  
Digital Evidence ◽  
Research Data Management ◽  
Analysis Laboratory ◽  
Near Future ◽  
Conceptual Overview

AbstractRecently, the topic of research data management has appeared at the forefront of Open Science as a prerequisite for preserving and disseminating research data efficiently. At the same time, scientific laboratories still rely upon digital files that are processed by experimenters to analyze and communicate laboratory results. In this study, we first apply a forensic process to investigate the information quality of digital evidence underlying published results. Furthermore, we use semiotics to describe the quality of information recovered from storage systems with laboratory forensics techniques. Next, we formulate laboratory analytics capabilities based on the results of the forensics analysis. Laboratory forensics and analytics form the basis of research data management. Finally, we propose a conceptual overview of open science readiness, which combines laboratory forensics techniques and laboratory analytics capabilities to help overcome research data management challenges in the near future.

scholarly journals Clinical research data management in the United States: Where we've been and where we're going

2021 ◽  
Author(s):  
Mary Banach ◽  
Kaye H Fendt ◽  
Johann Proeve ◽  
Dale Plummer ◽  
Samina Qureshi ◽  
...  
Keyword(s):  
Clinical Research ◽  
Data Management ◽  
Clinical Data ◽  
Management Practices ◽  
The United States ◽  
Research Data ◽  
Fda Guidance ◽  
Research Data Management ◽  
Challenges And Opportunities ◽  
Clinical Research Data

With the focus of the COVID-19 pandemic, we wanted to reach all stakeholders representing communities concerned with good clinical data management practices. We wanted to represent not only data managers but bio-statisticians, clinical monitors, data scientists, informaticians, and all those who collect, organize, analyze, and report on clinical research data. In our paper we will discuss the history of clinical data management in the US and its evolution from the early days of FDA guidance. We will explore the role of biomedical research focusing on the similarities and differences in industry and academia clinical research data management and what we can learn from each other. We will talk about our goals for recruitment and training for the CDM community and what we propose for increasing the knowledge and understanding of good clinical data practice to all – particularly our front-line data collectors i.e., nurses, medical assistants, patients, other data collectors. Finally, we will explore the challenges and opportunities to see CDM as the hub for good clinical data research practices in all of our communities.We will also discuss our survey on how the COVID-19 pandemic has affected the work of CDM in clinical research.

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