scholarly journals OceanNETs Data Management Plan

2020 ◽  
Author(s):  
Lisa Paglialonga ◽  
Carsten Schirnick
Keyword(s):  
Data Management ◽  
Scientific Community ◽  
Management Plan ◽  
Research Data ◽  
Data Handling ◽  
Research Project ◽  
Project Duration ◽  
Data Output ◽  
Close Cooperation

This is the data management plan for the research project OceanNETs. It compiles OceanNETs research data output and describes the data handling during and after the projects duration with the aim to make OceanNETs research data FAIR – sustainably available for the scientific community. This data management plan is a living document; it will be continously developed in close cooperation with the consortium members throughout the project duration.

scholarly journals ITB Research Data Management Plan

2018 ◽  
Author(s):  
Dasapta Erwin Irawan
Keyword(s):  
Data Management ◽  
Management Plan ◽  
Research Data ◽  
Team Members ◽  
Research Data Management ◽  
Project Level

Here's the official ITB Research Data Management Plan. We use this plan as a template to design more detailed project-level RDMP. The document came from the work of ITB Repository Team that I lead. Team members: Sparisoma Viridi, Rino Mukti (I will add this list later). I invite everyone to re-use this document for their project-level RDMP.

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 D8.1 Data Management Plan

2021 ◽  
Author(s):  
C. Soriano ◽  
R. Rossi ◽  
Q. Ayoul-Guilmard
Keyword(s):  
Open Access ◽  
Data Management ◽  
European Commission ◽  
Management Plan ◽  
Research Data ◽  
Scientific Publications ◽  
Horizon 2020 ◽  
Open Research ◽  
Data Program

The ExaQUte project participates in the Pilot on Open Research Data launched by the European Commission (EC) along with the H2020 program. This pilot is part of the Open Access to Scientific Publications and Research Data program in H2020. The goal of the program is to foster access to research data generated in H2020 projects. The use of a Data anagement Plan (DMP) is required for all projects participating in the Open Research Data Pilot, in which they will specify what data will be kept for the longer term. The underpinning idea is that Horizon 2020 beneficiaries have to make their research data findable, accessible, interoperable and re-usable (FAIR), to ensure it is soundly managed.

scholarly journals Researchers at Arab Universities Hold Positive Views on Research Data Management and Data Sharing

2020 ◽  
Vol 15 (2) ◽  
pp. 168-170
Author(s):  
Jennifer Kaari
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Data Privacy ◽  
Management Practices ◽  
Open Data ◽  
Scientific Progress ◽  
Management Plan ◽  
Research Data ◽  
Data Repository ◽  
Research Data Management

A Review of: Elsayed, A. M., & Saleh, E. I. (2018). Research data management and sharing among researchers in Arab universities: An exploratory study. IFLA Journal, 44(4), 281–299. https://doi.org/10.1177/0340035218785196 Abstract Objective – To investigate researchers’ practices and attitudes regarding research data management and data sharing. Design – Email survey. Setting – Universities in Egypt, Jordan, and Saudi Arabia. Subjects – Surveys were sent to 4,086 academic faculty researchers. Methods – The survey was emailed to faculty at three Arab universities, targeting faculty in the life sciences and engineering. The survey was created using Google Docs and remained open for five months. Participants were asked basic demographic questions, questions regarding their research data and metadata practices, and questions regarding their data sharing practices. Main Results – The authors received 337 responses, for a response rate of 8%. The results showed that 48.4% of respondents had a data management plan and that 97% were responsible for preserving their own data. Most respondents stored their research data on their personal storage devices. The authors found that 64.4% of respondents reported sharing their research data. Respondents most frequently shared their data by publishing in a data research journal, sharing through academic social networks such as ResearchGate, and providing data upon request to peers. Only 5.1% of respondents shared data through an open data repository.  Of those who did not share data, data privacy and confidentiality were the most common reasons cited. Of the respondents who did share their data, contributing to scientific progress and increased citation and visibility were the primary reasons for doing so. A total of 59.6% of respondents stated that they needed more training in research data management from their universities. Conclusion – The authors conclude that researchers at Arab universities are still primarily responsible for their own data and that data management planning is still a new concept to most researchers. For the most part, the researchers had a positive attitude toward data sharing, although depositing data in open repositories is still not a widespread practice. The authors conclude that in order to encourage strong data management practices and open data sharing among Arab university researchers, more training and institutional support is needed.

scholarly journals Teaching Practical Research Data Management Skills through Online Training and Data Management Plan Creation

2019 ◽  
Author(s):  
Beth Montague-Hellen ◽  
Holly Ranger
Keyword(s):  
Data Management ◽  
Academic Research ◽  
Management Plan ◽  
Research Data ◽  
Early Career ◽  
Research Data Management ◽  
Effective Manner ◽  
Management Concepts ◽  
Design Paradigm ◽  
Professional Support Staff

Introduction: Research Data Management is growing in importance as a field as the amount of data which researchers must manage increases. It is important to ensure that postgraduate researchers are trained through engaging courses which practically prepare them to fulfil the data management requirements of funders and Universities, and to carry out their research in a transparent and effective manner. Description of program: We present a case study of the development and delivery of a new Research Data Management (RDM) online course for postgraduates and early career researchers. The course implements pedagogical theory and a reverse design paradigm in the development of library training provision enabling the creation of a course vastly more relevant to academic research practice than our previous offering. The course uses a simplified Data Management Plan to introduce students to Research Data Management Concepts, and by asking them to apply this knowledge, lifts the course from one which simply asks students to remember knowledge to one which shows them how to apply this knowledge in a way that is applicable to their own research. The course has been evaluated for effectiveness and student engagement at 3 months. Next steps: Although some analysis of the effectiveness of the new course has been undertaken, the course will continue to be evaluated. Although the course was developed for PGRs it has been popular with ECRs and Professional support staff and we will investigate how we can further meet the needs of these groups. The platform used will allow for the topics most often accessed to be identified and the course, and the University’s training provision will be adjusted based on this evidence. We hope that other institutions will be able to learn from our experience and implement similar courses.

scholarly journals Promoting data sharing among Indonesian scientists: A proposal of generic university-level Research Data Management Plan (RDMP)

2018 ◽  
Vol 4 ◽  
pp. e28163
Author(s):  
Dasapta Irawan ◽  
Cut Rachmi
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
National Level ◽  
Management Plan ◽  
Research Data ◽  
Scientific Practices ◽  
Research Data Management ◽  
University Level ◽  
Time And Energy ◽  
Backup Storage

Every researcher needs data in their working ecosystem, but despite of the resources (funding, time, and energy), that they have spent to get the data, only a few are putting more real attention to data management. This paper is mainly describing our recommendation of RDMP document at university level. This paper would be a form of our initiative to be developed at university or national level, which also in-line with current development in scientific practices mandating data sharing and data re-use. Researchers can use this article as an assessment form to describe the setting of their research and data management. Researcher can also develop more detail RDMP to cater specific project's environment. In this Research Data Management Plan (RDMP), we propose three levels of storage: offline working storage, offline backup storage and online-cloud backup storage, located on a shared-repository. We also propose two kinds of cloud repository: a dynamic repository to store live data and a static repository to keep a copy of final data. Hopefully, this RDMP could solve problems on data sharing and preservation, and additionally could increase researchers' awareness about data management to increase the value and impact of their researches.

scholarly journals Current Protocols: Open and Reproducible Research on OSF

2019 ◽  
Author(s):  
Ian Sullivan ◽  
Alexander Carl DeHaven ◽  
David Thomas Mellor
Keyword(s):  
Data Management ◽  
Open Source ◽  
Scientific Community ◽  
Management Plan ◽  
Version Control ◽  
Reproducible Research ◽  
Research Practices ◽  
Share Data

By implementing more transparent research practices, authors have the opportunity to stand out and showcase work that is more reproducible, easier to build upon, and more credible. The scientist gains by making work easier to share and maintain within their own lab, and the scientific community gains by making underlying data or research materials more available for confirmation or making new discoveries. The following protocol gives the author step by step instructions for using the free and open source OSF to create a data management plan, preregister their study, use version control, share data and other research materials, or post a preprint for quick and easy dissemination.

scholarly journals Solving legal puzzles is not easy – supporting creating Data Management Plans in three scientific disciplines: chemistry, economics, and civil engineering

2020 ◽  
Author(s):  
Magdalena Szuflita-Żurawska ◽  
Anna Wałek
Keyword(s):  
Data Management ◽  
Civil Engineering ◽  
Academic Staff ◽  
Open Science ◽  
Management Plan ◽  
Research Data ◽  
Academic Community ◽  
Legal Issues ◽  
Scientific Disciplines ◽  
Management Plans

Open Science Competence Center at the Gdańsk University of Technology Library was established upon the Bridge of Data project at the end of 2018. Our main goals include providing support for the academic community for broad issues associated with Open Science, especially with Open Research Data. Our team of professionals help researchers in many topics such as: "what kinds of data you need to share", "how to make your data openly available to others", or "how to create a Data Management Plan" – that recently has been the most popular and demanding service.  One of the main challenges to support academic staff with Data Management Plans is dealing with the legal impediments to provide open access and reusing of research data for publicly funded scientific projects. The lack of understanding the legal issues in opening research is a significant barrier to facilitate Open Science. Much public-funded research requires to prepare a Data Management Plan that, among other items, provides information about ownership and user rights. One of the most common activity for scholars is choosing which license (if any) they are supposed to use in terms of the dissemination the scientific output. However, in many cases, resolving the right license for research data is not enough. Academic staff faces many tensions with a lack of clarity around legal requirements and obstacles. The increasing researchers' need for understanding and describing conflicting issues (e.g. patenting) results in looking for professional and knowledgeable support at the university. We examine the most frequent legal issues arising among DMPs from the three scientific disciplines: chemistry (e.g. ethical papers), economics (e.g. data value cycle), and civil engineering (e.g. complexity of construction data). In our presentation, we would like to introduce the main identified problems and show how mapping and benchmarking occurring problems among those disciplines help us to establish more efficient legal support for researchers. 

Research Data Management Among Researchers in Higher Learning Institutions of Sub-Saharan Africa

2020 ◽  
pp. 479-488 ◽  
Author(s):  
Neema Florence Mosha ◽  
Edith Talina Luhanga ◽  
Mary Vincent Mosha ◽  
Janeth Jonathan Marwa
Keyword(s):  
Data Management ◽  
Information And Communication Technologies ◽  
Management Plan ◽  
Research Data ◽  
Sub Saharan Africa ◽  
Quality Data ◽  
Research Data Management ◽  
Information And Communication ◽  
Sub Saharan ◽  
Learning Institutions

Advancement in information and communication technologies has made it easier for researchers to capture and store myriad data at a higher level of granularity. Higher education institutions (HEIs) worldwide are incorporating research data management (RDM) services to enable researchers to work with their data properly. This chapter focuses on creating awareness amongst researchers on how researchers and HEIs can form strategies, design and restrict data management plan (DMP), integrate research data life cycle, and ensure quality data sharing, as well as integrate with developed RDM policies and guidelines to curb challenges prohibiting the practice of RDM in HEIs.

scholarly journals Foundational Practices of Research Data Management

2020 ◽  
Vol 6 ◽  
Author(s):  
Kristin Briney ◽  
Heather Coates ◽  
Abigail Goben
Keyword(s):  
Data Analysis ◽  
Best Practices ◽  
Data Management ◽  
Management Practices ◽  
Research Data ◽  
Data Reuse ◽  
Data Handling ◽  
Good Data ◽  
Research Data Management ◽  
The Future

The importance of research data has grown as researchers across disciplines seek to ensure reproducibility, facilitate data reuse, and acknowledge data as a valuable scholarly commodity. Researchers are under increasing pressure to share their data for validation and reuse. Adopting good data management practices allows researchers to efficiently locate their data, understand it, and use it throughout all of the stages of a project and in the future. Additionally, good data management can streamline data analysis, visualization, and reporting, thus making publication less stressful and time-consuming. By implementing foundational practices of data management, researchers set themselves up for success by formalizing processes and reducing common errors in data handling, which can free up more time for research. This paper provides an introduction to best practices for managing all types of data.

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