Data Management: State-of-the-Practice at Open-Science Data Centers

2015 ◽  
pp. 1095-1108 ◽  
Author(s):  
Ritu Arora
Keyword(s):  
Data Management ◽  
Data Centers ◽  
Open Science ◽  
Science Data

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 

Data Management for Early Career Scientists – How to Tame the Elephant

2020 ◽  
Author(s):  
Laia Comas-Bru ◽  
Marcus Schmidt
Keyword(s):  
Data Management ◽  
Data Exchange ◽  
Early Stage ◽  
Open Science ◽  
Early Career ◽  
Data Repository ◽  
Science Data ◽  
Management Plans ◽  
Future Challenges ◽  
Researcher Network

<p>Data Management can be overwhelming, especially for Early Career Scientists. In order to give them a kick-start, the World Data System (WDS) organised a 3-day EGU-sponsored workshop on current achievements and future challenges in November 2019 in Paris. The purpose of the workshop was to provide Early Career Scientists with practical skills in data curation and management through a combination of practical sessions, group discussions and lectures. Participants were introduced to what are research data andcommon vocabulary to be used during the workshop. Later, a World Café session provided an opportunity to discuss individual challenges on data management and expectations of the workshop in small groups of peers. Lectures and discussions evolved around Open Science, Data Management Plans (DMP), data exchange, copyright and plagiarism, the use of Big Data, ontologies and cloud platforms in Science. Finally, the roles and responsibilities of the WDS as well as its WDS Early Career Researcher Network were discussed. Wrapping-up the workshop, attendees were walked through what is a data repository and how do they obtain their certifications.This PICO presentation given by two attendees of the workshop will showcase the main topics of discussion on data management and curation, provide key examples with special emphasis on the importance of creating a DMP at an early stage of your research project and share practical tools and advise on how to make data management more accessible.</p>

Ontologies and Life Science Data Management

2018 ◽  
pp. 2570-2574
Author(s):  
Robert Stevens ◽  
Phillip Lord
Keyword(s):  
Data Management ◽  
Life Science ◽  
Science Data

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 TrIAS, leveraging citizen science data to monitor invasive species in Belgium

2018 ◽  
Vol 2 ◽  
pp. e24749
Author(s):  
Quentin Groom ◽  
Tim Adriaens ◽  
Damiano Oldoni ◽  
Lien Reyserhove ◽  
Diederik Strubbe ◽  
...  
Keyword(s):  
Invasive Species ◽  
Alien Species ◽  
Citizen Science ◽  
Invasive Alien Species ◽  
Science Research ◽  
Open Science ◽  
Policy Support ◽  
Science Data ◽  
Common View ◽  
Indispensable Tool

Reducing the damage caused by invasive species requires a community approach informed by rapidly mobilized data. Even if local stakeholders work together, invasive species do not respect borders, and national, continental and global policies are required. Yet, in general, data on invasive species are slow to be mobilized, often of insufficient quality for their intended application and distributed among many stakeholders and their organizations, including scientists, land managers, and citizen scientists. The Belgian situation is typical. We struggle with the fragmentation of data sources and restrictions to data mobility. Nevertheless, there is a common view that the issue of invasive alien species needs to be addressed. In 2017 we launched the Tracking Invasive Alien Species (TrIAS) project, which envisages a future where alien species data are rapidly mobilized, the spread of exotic species is regularly monitored, and potential impacts and risks are rapidly evaluated in support of policy decisions (Vanderhoeven et al. 2017). TrIAS is building a seamless, data-driven workflow, from raw data to policy support documentation. TrIAS brings together 21 different stakeholder organizations that covering all organisms in the terrestrial, freshwater and marine environments. These organizations also include those involved in citizen science, research and wildlife management. TrIAS is an Open Science project and all the software, data and documentation are being shared openly (Groom et al. 2018). This means that the workflow can be reused as a whole or in part, either after the project or in different countries. We hope to prove that rapid data workflows are not only an indispensable tool in the control of invasive species, but also for integrating and motivating the citizens and organizations involved.

scholarly journals Analyzing academic mobility of U.S. professors based on ORCID data and the Carnegie Classification

2020 ◽  
Vol 1 (4) ◽  
pp. 1451-1467
Author(s):  
Erija Yan ◽  
Yongjun Zhu ◽  
Jiangen He
Keyword(s):  
United States ◽  
The United States ◽  
Open Science ◽  
Geographic Region ◽  
Science Data ◽  
Academic Mobility ◽  
Carnegie Classification ◽  
Research Intensity ◽  
Rural Institutions ◽  
Urban Institutions

This paper uses two open science data sources—ORCID and the Carnegie Classification of Institutions of Higher Education (CCIHE)—to identify tenure-track and tenured professors in the United States who have changed academic affiliations. Through a series of data cleaning and processing actions, 5,938 professors met the selection criteria of professorship and mobility. Using ORCID professor profiles and the Carnegie Classification, this paper reveals patterns of academic mobility in the United States from the aspects of institution types, locations, regions, funding mechanisms of institutions, and professors’ genders. We find that professors tended to move to institutions with higher research intensity, such as those with an R1 or R2 designation in the Carnegie Classification. They also tend to move from rural institutions to urban institutions. Additionally, this paper finds that female professors are more likely to move within the same geographic region than male professors and that when they move from a less research-intensive institution to a more research-intensive one, female professors are less likely to retain their rank or attain promotion.

scholarly journals Enabling petascale science: data management, troubleshooting, and scalable science services

2008 ◽  
Vol 125 ◽  
pp. 012068 ◽  
Author(s):  
A Baranovski ◽  
K Beattie ◽  
S Bharathi ◽  
J Boverhof ◽  
J Bresnahan ◽  
...  
Keyword(s):  
Data Management ◽  
Science Data
Sign in / Sign up

Export Citation Format

Share Document