scholarly journals Data management plan

2021 ◽  
Author(s):  
J. García-Espinosa ◽  
C. Soriano
Keyword(s):  
Data Management ◽  
European Commission ◽  
Data Storage ◽  
Computational Models ◽  
Management Plan ◽  
Research Data ◽  
Horizon 2020 ◽  
Open Research ◽  
Technical Solutions ◽  
Term Data

This document presents the deliverable D8.1 – the Data Management Plan (DMP) of work package 8 of the prodPhD project. It aims to present the plan for the management, generation, collection, security, preservation and sharing of data generated through the prodPhD project. The DMP is a key element for organizing the project’s data. It provides an analysis of the data, which will be collected, processed and published by the prodPhD consortium. The project embraces the initiatives of the European Commission to promote the open access to research data, aiming to improve and maximize access to and reuse of research data generated by Horizon 2020 projects. In this sense prodPhD will adhere to the Open Research Data Pilot (ORD Pilot) fostered by the European Commission, and this DMP will be developed following the standards of data storage, access and management. This plan will detail what data will be generated through the project, whether and how it will be made accessible for the verification and reuse and how it will be curated and preserved. In this context, the term data applies to the information generated during the different experimental campaigns carried out in the project, and specifically to the data, including associated metadata, to be used to validate the computational models and the technical solutions to be developed in the project. This document is the first version of the DMP and may be updated throughout the project, if significant changes (new data, changes in consortium policies, changes in consortium composition, etc.) arise.

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 Lessons Learnt from Engineering Science Projects Participating in the Horizon 2020 Open Research Data Pilot

Data ◽  
2021 ◽  
Vol 6 (9) ◽  
pp. 96
Author(s):  
Timothy Austin ◽  
Kyriaki Bei ◽  
Theodoros Efthymiadis ◽  
Elias P. Koumoulos
Keyword(s):  
Open Access ◽  
Best Practices ◽  
Data Management ◽  
Open Data ◽  
Research Programme ◽  
Research Data ◽  
Good Effect ◽  
Process Data ◽  
Horizon 2020 ◽  
Open Research

Trends in the sciences are indicative of data management becoming established as a feature of the mainstream research process. In this context, the European Commission introduced an Open Research Data pilot at the start of the Horizon 2020 research programme. This initiative followed the success of the Open Access pilot implemented in the prior (FP7) research programme, which thereafter became an integral component of Horizon 2020. While the Open Access phenomenon can reasonably be argued to be one of many instances of web technologies disrupting established business models (namely publication practices and workflows established over several centuries in the case of Open Access), initiatives designed to promote research data management have no established foundation on which to build. For Open Data to become a reality and, more importantly, to contribute to the scientific process, data management best practices and workflows are required. Furthermore, with the scientific community having operated to good effect in the absence of data management, there is a need to demonstrate the merits of data management. This circumstance is complicated by the lack of the necessary ICT infrastructures, especially interoperability standards, required to facilitate the seamless transfer, aggregation and analysis of research data. Any activity aiming to promote Open Data thus needs to overcome a number of cultural and technological challenges. It is in this context that this paper examines the data management activities and outcomes of a number of projects participating in the Horizon 2020 Open Research Data pilot. The result has been to identify a number of commonly encountered benefits and issues; to assess the utilisation of data management plans; and through the close examination of specific cases, to gain insights into obstacles to data management and potential solutions. Although primarily anecdotal and difficult to quantify, the experiences reported in this paper tend to favour developing data management best practices rather than doggedly pursue the Open Data mantra. While Open Data may prove valuable in certain circumstances, there is good reason to claim that managed access to scientific data of high inherent intellectual and financial value will prove more effective in driving knowledge discovery and innovation.

scholarly journals Research Data Management Practices: A Snapshot in Time

2015 ◽  
Vol 10 (2) ◽  
pp. 69-95 ◽  
Author(s):  
Mary Anne Kennan ◽  
Lina Markauskaite
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Management Practices ◽  
Management Plan ◽  
Research Data ◽  
Project Completion ◽  
Research Data Management ◽  
Secure Storage ◽  
South Wales ◽  
Research Organisations

There is increasing pressure from funders, publishers, the public, universities and other research organisations for researchers to improve their data management and sharing practices. However, little is known about researchers’ data management and sharing practices and concerns. The research reported in this paper seeks to address this by providing insight into the research data management and sharing practices of academics at ten universities in New South Wales, Australia. Empirical data was taken from a survey to which 760 academics responded, with 634 completing at least one section. Results showed that at the time of the survey there were a wide variety of research data in use, including analogue data, and that the challenges researchers faced in managing their data included finding safe and secure storage, particularly after project completion, but also during projects when data are used (and thus stored) on a wide variety of less-than-optimal temporary devices. Data sharing was not widely practiced and only a relatively small proportion of researchers had a research data management plan. Since the survey was completed much has changed: capacities and communities are being built around data management and sharing and policies, and guidelines are being constructed. Data storage and curation services are now more freely available. It will be interesting to observe how the findings of future studies compare with those reported here.

scholarly journals The on-premise data sharing infrastructure e!DAL: Foster FAIR data for faster data acquisition

GigaScience ◽  
2020 ◽  
Vol 9 (10) ◽  
Author(s):  
Daniel Arend ◽  
Patrick König ◽  
Astrid Junker ◽  
Uwe Scholz ◽  
Matthias Lange
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Best Practice ◽  
Research Process ◽  
Research Data ◽  
Primary Data ◽  
Data Repository ◽  
Plant Genomics ◽  
Quality Of Data

Abstract Background The FAIR data principle as a commitment to support long-term research data management is widely accepted in the scientific community. Although the ELIXIR Core Data Resources and other established infrastructures provide comprehensive and long-term stable services and platforms for FAIR data management, a large quantity of research data is still hidden or at risk of getting lost. Currently, high-throughput plant genomics and phenomics technologies are producing research data in abundance, the storage of which is not covered by established core databases. This concerns the data volume, e.g., time series of images or high-resolution hyper-spectral data; the quality of data formatting and annotation, e.g., with regard to structure and annotation specifications of core databases; uncovered data domains; or organizational constraints prohibiting primary data storage outside institional boundaries. Results To share these potentially dark data in a FAIR way and master these challenges the ELIXIR Germany/de.NBI service Plant Genomic and Phenomics Research Data Repository (PGP) implements a “bring the infrastructure to the data” approach, which allows research data to be kept in place and wrapped in a FAIR-aware software infrastructure. This article presents new features of the e!DAL infrastructure software and the PGP repository as a best practice on how to easily set up FAIR-compliant and intuitive research data services. Furthermore, the integration of the ELIXIR Authentication and Authorization Infrastructure (AAI) and data discovery services are introduced as means to lower technical barriers and to increase the visibility of research data. Conclusion The e!DAL software matured to a powerful and FAIR-compliant infrastructure, while keeping the focus on flexible setup and integration into existing infrastructures and into the daily research process.

scholarly journals Tutkimusaineiston avoin jakaminen – tutkimusorganisaatioiden jäsenten käsityksiä, kokemuksia ja mielipiteitä

2018 ◽  
Vol 37 (4) ◽  
Author(s):  
Heidi Enwald
Keyword(s):  
Data Sharing ◽  
Data Storage ◽  
Online Survey ◽  
Open Science ◽  
Research Data ◽  
Research Field ◽  
Open Research ◽  
Research Organizations ◽  
Data Collection Instrument ◽  
In The Beginning

Open research data is data that is free to access, reuse, and redistribute. This study focuses on the perceptions, opinions and experiences of staff and researchers of research institutes on topics related to open research data. Furthermore, the differences across gender, role in the research organization and research field were investigated. An international questionnaire survey, translated into Finnish and Swedish, was used as the data collection instrument. An online survey was distributed through an open science related network to Finnish research organizations. In the end, 469 responded to all 24 questions of the survey. Findings indicate that many are still unaware or uncertain about issues related to data sharing and long-term data storage. Women as well as staff and researchers of medical and health sciences were most concerned about the possible problems associated with data sharing. Those in the beginning of their scientific careers, hesitated about sharing their data.

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 Research Data Management Initiatives at University of Edinburgh

2011 ◽  
Vol 6 (2) ◽  
pp. 232-244 ◽  
Author(s):  
Robin Rice ◽  
Jeff Haywood
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Academic Staff ◽  
Research Data ◽  
Lessons Learned ◽  
The Public ◽  
Research Data Management ◽  
Online Tools ◽  
University Of Edinburgh ◽  
Future Direction

During the last decade, national and international attention has been increasingly focused on issues of research data management and access to publicly funded research data. The pressure brought to bear on researchers to improve their data management and data sharing practice has come from research funders seeking to add value to expensive research and solve cross-disciplinary grand challenges; publishers seeking to be responsive to calls for transparency and reproducibility of the scientific record; and the public seeking to gain and re-use knowledge for their own purposes using new online tools. Meanwhile higher education institutions have been rather reluctant to assert their role in either incentivising or supporting their academic staff in meeting these more demanding requirements for research practice, partly due to lack of knowledge as to how to provide suitable assistance or facilities for data storage and curation/preservation. This paper discusses the activities and drivers behind one institution’s recent attempts to address this gap, with reflection on lessons learned and future direction.

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 Progress on Data Stewardship Wizard during BioHackathon Europe 2020

2020 ◽  
Author(s):  
Marek Suchánek ◽  
Rob W.W. Hooft ◽  
Konogan Bourhy
Keyword(s):  
Data Management ◽  
Management Plan ◽  
Knowledge Model ◽  
Horizon 2020 ◽  
Past Time ◽  
The Past ◽  
Europe 2020 ◽  
Questions And Answers ◽  
Data Stewardship ◽  
Multiple Languages

We used the Virtual BioHackathon Europe 2020 to work on a number of projects for improvement of the data stewardship wizard: (a) We made first steps to analysis of what is needed to make all questions and answers machine actionable (b) We worked on supporting the Horizon 2020 Data Management Plan Template (c) Several new integrations were made, e.g. to ROR and Wikidata (d) we made a draft plan for supporting multiple languages and (e) we implemented many suggestions for improvement of the knowledge model that had been suggested to us over the past time. Quickly after the BioHackathon, the adapted knowledge model, new integrations and the H2020 template have been made available to all users of the wizard.

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.

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