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 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 ELIXIR Software Management Plan for Life Sciences

2021 ◽  
Author(s):  
Renato Alves ◽  
Dimitrios Bampalikis ◽  
Leyla Jael Castro ◽  
José María Fernández ◽  
Jennifer Harrow ◽  
...  
Keyword(s):  
Data Management ◽  
Open Source Software ◽  
Open Science ◽  
Management Plan ◽  
Software Management ◽  
Research Software ◽  
Management Perspective ◽  
Management Plans ◽  
Machine Readable ◽  
Future Plans

Data Management Plans are now considered a key element of Open Science. They describe the data management life cycle for the data to be collected, processed and/or generated within the lifetime of a particular project or activity. A Software Manag ement Plan (SMP) plays the same role but for software. Beyond its management perspective, the main advantage of an SMP is that it both provides clear context to the software that is being developed and raises awareness. Although there are a few SMPs already available, most of them require significant technical knowledge to be effectively used. ELIXIR has developed a low-barrier SMP, specifically tailored for life science researchers, aligned to the FAIR Research Software principles. Starting from the Four Recommendations for Open Source Software, the ELIXIR SMP was iteratively refined by surveying the practices of the community and incorporating the received feedback. Currently available as a survey, future plans of the ELIXIR SMP include a human- and machine-readable version, that can be automatically queried and connected to relevant tools and metrics within the ELIXIR Tools ecosystem and beyond.

scholarly journals Information Integration for Machine Actionable Data Management Plans

2017 ◽  
Vol 12 (1) ◽  
pp. 22-35 ◽  
Author(s):  
Tomasz Miksa ◽  
Andreas Rauber ◽  
Roman Ganguly ◽  
Paolo Budroni
Keyword(s):  
Data Management ◽  
Information Integration ◽  
Open Science ◽  
Management Plan ◽  
Reproducible Research ◽  
Free Form ◽  
Text Documents ◽  
Data Repositories ◽  
Standard Data ◽  
Management Plans

Data management plans are free-form text documents describing the data used and produced in scientific experiments. The complexity of data-driven experiments requires precise descriptions of tools and datasets used in computations to enable their reproducibility and reuse. Data management plans fall short of these requirements. In this paper, we propose machine-actionable data management plans that cover the same themes as standard data management plans, but particular sections are filled with information obtained from existing tools. We present mapping of tools from the domains of digital preservation, reproducible research, open science, and data repositories to data management plan sections. Thus, we identify the requirements for a good solution and identify its limitations. We also propose a machine-actionable data model that enables information integration. The model uses ontologies and is based on existing standards.

scholarly journals The establishment of a Norwegian node in RDA

2019 ◽  
Author(s):  
Trond Kvamme ◽  
Philipp Conzett
Keyword(s):  
Data Management ◽  
Data Exchange ◽  
The United States ◽  
Open Science ◽  
Research Data ◽  
Sensitive Data ◽  
Data Repositories ◽  
Management Plans ◽  
Inclusive Approach ◽  
Processing And Storage

Norway has been selected as a new national node in RDA (Research Data Alliance). Until the end of the project in May 2020, the node will be engaging with research communities, supporting national agendas, and contributing to the EU Open Science Strategy to ensure capillary uptake of RDA principles and outputs. Moreover, they will be working to increase the participation in RDA nationally. The Norwegian RDA node (NO-RDA) will be run by a consortium of seven partners, each of them with specific roles in the activities around the node, and led by NSD - Norwegian Centre for Research Data. NO-RDA will focus on supporting the implementation of RDA outputs and recommendations and on areas of strategic importance for the Nordic region, such as Data Management Plans, FAIR Data Stewardship and management of sensitive data in research within the framework of current international and statutory regulations. In addition to NSD the node consists of NTNU, UiB, UiO, UiT, Unit og Uninett/Sigma2. The Research Data Alliance (RDA) was launched as a community-driven initiative in 2013 by the European Commission, the United States Government's National Science Foundation and National Institute of Standards and Technology, and the Australian Government’s Department of Innovation with the goal of building the social and technical infrastructure to enable open sharing and re-use of data. RDA has a grass-roots, inclusive approach covering all data lifecycle stages, engaging data producers, users and stewards, addressing data exchange, processing, and storage. It has succeeded in creating the neutral social platform where international research data experts meet to exchange views and to agree on topics including social hurdles on data sharing, education and training challenges, data management plans and certification of data repositories, disciplinary and interdisciplinary interoperability, as well as technological aspects.

scholarly journals Data management plans: time wasting or time saving?

2020 ◽  
Vol 42 (3) ◽  
pp. 38-39
Author(s):  
Alison Nightingale
Keyword(s):  
Data Management ◽  
Academic Staff ◽  
Research Data ◽  
Time Saving ◽  
Academic Researchers ◽  
Management Problems ◽  
Management Plans

As a Research Data Librarian, one of my responsibilities is to raise awareness about the requirements for academic researchers to write data management plans for their projects. These awareness activities, often in the form of a presentation at staff meetings or departmental seminars, are frequently followed by a sceptical response from the academic staff along the lines that “This is just something else for us to try to fit into our already over-busy lives”. My answer is usually: “Yes, but it might prevent data management problems slowing up your project”. So, what are data management plans and how can they be of value to your project?

Research Data Management Support at Kaunas University of Technology

2021 ◽  
pp. 52-71
Author(s):  
Ieva Cesevičiūtė ◽  
Gintarė Tautkevičienė
Keyword(s):  
Open Access ◽  
Data Management ◽  
National Level ◽  
Open Science ◽  
Research Data ◽  
Management Support ◽  
Research Data Management ◽  
University Of Technology ◽  
Management Plans ◽  
The Baltic

Kaunas University of Technology is one of the largest technical universities in the Baltic region. The university staff has been involved in different Open Access- and Open Science-related activities for more than a decade. Different initiatives have been implemented: stand-alone and series of training and awareness-raising events, promotion of Open Access and Open Science ideas so that institutions develop their Open Access policies and make their repositories compliant with larger research infrastructures. Within the institution, the initiatives of Open Science are implemented as a result of joint effort of the library, the departments of research, studies, and doctoral school. The current tasks involve revising the institutional Open Access guidelines and facilitating the implementation of data management plans in doctoral studies. In this chapter, the aim is to provide an overview of the efforts highlighting the successes and failures on the way to best practice in research data management support both institutionally and on the national level.

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 Using Active Learning Classrooms in Building an Infrastructure for Access to Research Data

2018 ◽  
Author(s):  
Stefan Ekman ◽  
Helena Francke
Keyword(s):  
Active Learning ◽  
Data Management ◽  
Collaborative Work ◽  
Data Access ◽  
Open Science ◽  
Management Plan ◽  
Research Data ◽  
Management Skills ◽  
National Network ◽  
Institutional Conditions

Watch the VIDEO.As a central part of its work towards Open Science, Sweden is building an infrastructure for managing, storing, and providing access to research data. A vital component of this infrastructure will be functions at Swedish universities for supporting researchers with data access and management. To support these local functions, here referred to as Data Access Units (DAUs), a national network of DAUs from 28 universities is under formation.To assist in establishing DAUs and strengthening the network, the Swedish National Data Service and the University of Borås offer a joint professional development course to DAU staff. This course ran for the first time in spring 2018, with 21 participants from 12 universities. The course has three main objectives: to develop data management skills; to increase understanding of the institutional conditions for providing access to research data; and to strengthen the national network through interpersonal connections and collegial ties.The methodology chosen for the course is intended to promote collaboration between participants and to take into consideration their various types and levels of expertise and experience. This has resulted in a distance-learning course with four physical meetings, during which an Active Learning Classroom (ALC) methodology is used: participants work actively in groups with instructor-facilitated tasks. The ALC work is combined with significant use of collaborative work between meetings.Our presentation will show how ALC methodology can be used to support the establishment of DAUs and a DAU network. We will discuss some examples of course elements which contribute to the objectives. The discussion will be based on the facilitators’ analyses and on the participants’ answers to an evaluation questionnaire.Participants found that they developed data management skills by working with cases as ALC exercises, and thought these skills would be directly applicable to their work in the DAU. Such ALC exercises were designed around for instance anonymising datasets and writing a data management plan for a potential study.In addressing institutional conditions necessary for data access, we observed how task design and perceived relevance of a topic are important for how participants engage with various aspects of a task. For example, the ALC exercise on legal frameworks was easier to align with perceived DAU needs than the less focused and more abstract exercise on models and principles such as OAIS and FAIR.A clear outcome of the course was a strengthening of the DAU network. Participants gained a sense of collegiality by working in different constellations during various ALC tasks. The social activities – breaks and meals – intentionally included in the course also allowed classroom discussions to flow into more informal spaces.The DAUs and their national network is a vital part of the Swedish infrastructure for Open Science concerning access to research data. The presentation will end with reflections on how ALC methodology can also be employed to strengthen data management and accessibility skills in other parts of the infrastructure, for instance with researchers.

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 The Open Data Challenge: An Analysis of 124,000 Data Availability Statements and an Ironic Lesson about Data Management Plans

2020 ◽  
Vol 2 (4) ◽  
pp. 554-568
Author(s):  
Chris Graf ◽  
Dave Flanagan ◽  
Lisa Wylie ◽  
Deirdre Silver
Keyword(s):  
Machine Learning ◽  
Data Management ◽  
Open Data ◽  
Research Data ◽  
Data Availability ◽  
Policy Changes ◽  
Management Plans ◽  
Trends Over Time ◽  
New Research ◽  
Over Time

Data availability statements can provide useful information about how researchers actually share research data. We used unsupervised machine learning to analyze 124,000 data availability statements submitted by research authors to 176 Wiley journals between 2013 and 2019. We categorized the data availability statements, and looked at trends over time. We found expected increases in the number of data availability statements submitted over time, and marked increases that correlate with policy changes made by journals. Our open data challenge becomes to use what we have learned to present researchers with relevant and easy options that help them to share and make an impact with new research data.

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