scholarly journals Quality evaluation of data management plans at a research university

IFLA Journal ◽  
2017 ◽  
Vol 43 (1) ◽  
pp. 98-104 ◽  
Author(s):  
James E. Van Loon ◽  
Katherine G. Akers ◽  
Cole Hudson ◽  
Alexandra Sarkozy
Keyword(s):  
Data Management ◽  
National Science Foundation ◽  
Research University ◽  
Management Plan ◽  
Research Data ◽  
National Science Foundation Grant ◽  
Quality Of Data ◽  
National Science ◽  
Management Plans ◽  
Grant Proposals

With the emergence of the National Science Foundation requirement for data management plans, academic librarians have increasingly aided researchers in developing these plans and disseminating research data. To determine the overall quality of data management plans at Wayne State University, the Library System’s Research Data Services team evaluated the content of 119 plans from National Science Foundation grant proposals submitted between 2012 and 2014. The results of our content analysis indicate that, while most researchers understand the need to share data, many data management plans fail to adequately describe the data generated by the project, how data will be managed during the project, or how data will be preserved and shared after the completion of the project. Our results also show that data management plan deficiencies vary across academic units, suggesting the need for differentiated outreach services to improve the strength of data management plans in future National Science Foundation grant proposals.

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 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. 

scholarly journals The Problematic Future of Research Data Management: Challenges, Opportunities and Emerging Patterns Identified by the DataRes Project

2013 ◽  
Vol 8 (2) ◽  
pp. 111-122 ◽  
Author(s):  
Martin Halbert
Keyword(s):  
Data Management ◽  
Academic Research ◽  
The United States ◽  
Research Data ◽  
University Of North Texas ◽  
Research Data Management ◽  
Management Plans ◽  
Institutional Transitions ◽  
Grant Proposals ◽  
The University

This paper describes findings and projections from a project that has examined emerging policies and practices in the United States regarding the long-term institutional management of research data. The DataRes project at the University of North Texas (UNT) studied institutional transitions taking place during 2011-2012 in response to new mandates from U.S. governmental funding agencies requiring research data management plans to be submitted with grant proposals. Additional synergistic findings from another UNT project, termed iCAMP, will also be reported briefly.This paper will build on these data analysis activities to discuss conclusions and prospects for likely developments within coming years based on the trends surfaced in this work. Several of these conclusions and prospects are surprising, representing both opportunities and troubling challenges, for not only the library profession but the academic research community as a whole.

Radon and You

2010 ◽  
Author(s):  
David Fisher
Keyword(s):  
Radioactive Contamination ◽  
National Science Foundation ◽  
National Science Foundation Grant ◽  
The Sun ◽  
Bunsen Burner ◽  
Alpha Radiation ◽  
Firing Squad ◽  
National Science ◽  
Grant Proposals ◽  
To Come

A review for one of my National Science Foundation grant proposals began “He isn’t the world’s greatest experimentalist, but …” I couldn’t argue with that. In fact, once I nearly destroyed the Brookhaven chemistry building. I had been working nearly thirtysix hours straight and was a bit tired. When I finally left, with the sun not quite rising, I forgot to turn off the Bunsen burner. Not only that, but I had left it with its rubber feed tube twisted a bit. Evidently the strain on the tubing later pulled the burner around and tipped it over. When it fell, the flame went out but the gas kept right on flowing through, and a few hours later when our lab tech, Johnny Densieski (who was always the first person to come in every morning), opened the doors he was nearly knocked over by the smell. Ordinarily he would have been more than just nearly knocked over, but for some reason the lit cigarette that was always dangling from his lips was absent that day, saving his life and the chemistry building from instant demolition. Johnny was loyally close-mouthed about it, but the story did get around. So when a routine exam of our lab showed radioactive contamination, everyone’s eyes naturally turned to me. I have to admit I thought it probably was my fault until a spectrometric examination of the evidence showed that it was alpha radiation, and all my work was done with beta radionuclides. The health physicists conducting the investigation didn’t believe me, of course, and so they tested lab counters and desks everywhere I had been, and found more and more radioactivity. They were about to put me in front of a firing squad until, being more thorough, they began to test areas where I had never been and found the same radioactive contamination, which they identified as polonium-218.

Aktives Forschungsdatenmanagement

ABI-Technik ◽  
2018 ◽  
Vol 38 (1) ◽  
pp. 55-64
Author(s):  
Heike Neuroth ◽  
Claudia Engelhardt ◽  
Jochen Klar ◽  
Jens Ludwig ◽  
Harry Enke
Keyword(s):  
Data Management ◽  
National Science Foundation ◽  
Research Data ◽  
Horizon 2020 ◽  
Europäische Kommission ◽  
Research Data Management ◽  
National Science ◽  
It Support ◽  
Deutsche Forschungsgemeinschaft

ZusammenfassungForschungsdatenmanagement und damit einhergehend Forschungsdatenmanagementpläne nehmen national und international an Bedeutung zu. Nicht nur, dass verschiedene Förderorganisationen wie die National Science Foundation (USA), der Schweizerische Nationalfonds (SNF), die Deutsche Forschungsgemeinschaft (DFG) sowie die Europäische Kommission mit Horizon 2020 (H2020) bereits bei Projektanträgen Auskunft über den Umgang mit den nachgenutzten oder erstellten Forschungsdaten verlangen, es beschäftigen sich auch mehr und mehr Initiativen wie zum Beispiel international die Research Data Alliance oder in Deutschland die DINI/nestor-Arbeitsgruppe Forschungsdaten mit dem Thema. International setzt sich dabei mehr und mehr die Erkenntnis durch, dass es im Umgang mit Forschungsdaten nicht mit einem einmaligen Erstellen eines Forschungsdatenmanagementplans getan ist, sondern dass sich die Pläne aktiv dem Verlauf des Forschungsprozesses anpassen und für verschiedene Bedarfe zur Verfügung gestellt werden müssen. So kann es sinnvoll und notwendig sein, weitere Beteiligte wie zum Beispiel IT-Support oder übergeordnete Datenmanager beim Erstellen und Aktualisieren eines Forschungsdatenmanagementplans zu berücksichtigen. Daher muss ein Werkzeug zur Unterstützung von diesen Plänen über das bloße Ausfüllen von Vorlagen der Förderorganisation hinaus weitere Aufgaben erfüllen und so den gesamten Prozess des Forschungsdatenmanagements unterstützen. Der Research Data Management Organiser (RDMO) ist ein solches Werkzeug, das im Rahmen eines DFG-Projektes entwickelt und mit Hilfe unterschiedlicher Gruppen von Nutzenden getestet wurde. Das RDMO-Tool ist multilingual, flexibel an Community- und Organisationsanforderungen anpassbar und unterstützt verschiedene Aufgaben wie zum Beispiel unterschiedliche Export-Funktionen oder die Erledigung zeitlich gebundener Tasks. In einem DFG-Nachfolgeprojekt, das Ende 2017 gestartet ist, werden in RDMO wichtige Erweiterungen sowohl technischer Art als auch bezogen auf verschiedene Aspekte der Nachhaltigkeit vorgenommen.

scholarly journals Using Data Management Plans to Explore Variability in Research Data Management Practices Across Domains

2016 ◽  
Vol 11 (1) ◽  
pp. 53-67 ◽  
Author(s):  
Susan Wells Parham ◽  
Jake Carlson ◽  
Patricia Hswe ◽  
Brian Westra ◽  
Amanda Whitmire
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Management Plan ◽  
Library Services ◽  
Complete Understanding ◽  
National Science ◽  
Management Plans ◽  
Using Data ◽  
Insight Into

This paper describes an investigation into how researchers in different fields are interpreting and responding to the U.S. National Science Foundation’s data management plan (DMP) requirement. As documents written by the researchers themselves, DMPs can provide insight into researchers’ understanding of the potential value of their data to others; the environment in which their data are developed and prepared; and their willingness and ability to ensure the data are available to others now and in the long-term. With support from the Institute of Museum and Library Services, the authors conducted a content analysis of DMPs generated at their respective institutions using a shared rubric. By developing and testing a rubric designed to understand and evaluate the content of DMPs, the authors intend to develop a more complete understanding, at a larger scale, of how researchers plan for managing, sharing, and archiving their data. 

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.

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