ELIXIR Software Management Plan for Life Sciences

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.

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Plano de gestão de dados fair: uma proposta para a Fiocruz | Fair data management plan: a proposal for Fiocruz

Liinc em Revista ◽

10.18617/liinc.v15i2.5030 ◽

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.

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Information Integration for Machine Actionable Data Management Plans

International Journal of Digital Curation ◽

10.2218/ijdc.v12i1.529 ◽

2017 ◽

Vol 12 (1) ◽

pp. 22-35 ◽

Cited By ~ 2

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.

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

Septentrio Conference Series ◽

10.7557/5.5576 ◽

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.

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The Open-Specimen Movement

BioScience ◽

10.1093/biosci/biaa146 ◽

2020 ◽

Author(s):

Jocelyn P Colella ◽

Ryan B Stephens ◽

Mariel L Campbell ◽

Brooks A Kohli ◽

Danielle J Parsons ◽

...

Keyword(s):

Data Management ◽

Open Data ◽

Open Science ◽

Management Plan ◽

Scientific Data ◽

Primary Data ◽

Explicit Integration ◽

Cultural Shift ◽

Major Barrier ◽

Annual Reporting

Abstract The open-science movement seeks to increase transparency, reproducibility, and access to scientific data. As primary data, preserved biological specimens represent records of global biodiversity critical to research, conservation, national security, and public health. However, a recent decrease in specimen preservation in public biorepositories is a major barrier to open biological science. As such, there is an urgent need for a cultural shift in the life sciences that normalizes specimen deposition in museum collections. Museums embody an open-science ethos and provide long-term research infrastructure through curation, data management and security, and community-wide access to samples and data, thereby ensuring scientific reproducibility and extension. We propose that a paradigm shift from specimen ownership to specimen stewardship can be achieved through increased open-data requirements among scientific journals and institutional requirements for specimen deposition by funding and permitting agencies, and through explicit integration of specimens into existing data management plan guidelines and annual reporting.

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Strategies for biomedical software management, sharing, and citation

10.7287/peerj.preprints.2640 ◽

2016 ◽

Author(s):

Daniel S Katz ◽

Kyle E Niemeyer ◽

Arfon M Smith

Keyword(s):

Data Management ◽

Working Group ◽

Software Management ◽

Research Software ◽

Open Issues

This document is an open response to the NIH Request for Information (RFI): Strategies for NIH Data Management, Sharing, and Citation, Notice Number: NOT-OD-17-015, written by the leaders of the FORCE11 Software Citation Working Group from its inception in mid-2015 through today. This group produced a set of Software Citation Principles and related discussion, which are the basis for this document. Here, we describe research software, summarize the software citation principles, discuss open issues related to software citation, and make recommendations to the NIH.

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Strategies for biomedical software management, sharing, and citation

10.7287/peerj.preprints.2640v1 ◽

2016 ◽

Author(s):

Daniel S Katz ◽

Kyle E Niemeyer ◽

Arfon M Smith

Keyword(s):

Data Management ◽

Working Group ◽

Software Management ◽

Research Software ◽

Open Issues

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The establishment of a Norwegian node in RDA

Septentrio Conference Series ◽

10.7557/5.4976 ◽

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.

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Understanding the Data Management Plan as a Boundary Object through a Multi-stakeholder perspective

International Journal of Digital Curation ◽

10.2218/ijdc.v16i1.746 ◽

2021 ◽

Vol 16 (1) ◽

pp. 16

Author(s):

Live Kvale ◽

Nils Pharo

Keyword(s):

Data Management ◽

Delphi Study ◽

Management Plan ◽

Boundary Object ◽

Research Data Management ◽

Three Phase ◽

Management Plans ◽

Stakeholder Perspective ◽

Common Goals ◽

Multi Stakeholder

A three-phase Delphi study was used to investigate an emerging community for research data management in Norway and their understanding and application of data management plans (DMPs). The findings reveal visions of what the DMP should be as well as different practice approaches, yet the stakeholders present common goals. This paper discusses the different perspectives on the DMP by applying Star and Griesemer’s theory of boundary objects (Star & Griesemer, 1989). The debate on what the DMP is and the findings presented are relevant to all research communities currently implementing DMP procedures and requirements. The current discussions about DMPs tend to be distant from the active researchers and limited to the needs of funders and institutions rather than to the usefulness for researchers. By analysing the DMP as a boundary object, plastic and adaptable yet with a robust identity (Star & Griesemer, 1989), and by translating between worlds where collaboration on data sharing can take place we expand the perspectives and include all stakeholders. An understanding of the DMP as a boundary object can shift the focus from shaping a DMP which fulfils funders’ requirements to enabling collaboration on data management and sharing across domains using standardised forms.

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From FAIR research data toward FAIR and open research software

it - Information Technology ◽

10.1515/itit-2019-0040 ◽

2020 ◽

Vol 62 (1) ◽

pp. 39-47 ◽

Cited By ~ 2

Author(s):

Wilhelm Hasselbring ◽

Leslie Carr ◽

Simon Hettrick ◽

Heather Packer ◽

Thanassis Tiropanis

Keyword(s):

Open Source ◽

Open Source Software ◽

Scientific Practice ◽

Open Science ◽

Research Data ◽

Scientific Publications ◽

Research Software ◽

Current State ◽

Software Licenses ◽

Fair Principles

AbstractThe Open Science agenda holds that science advances faster when we can build on existing results. Therefore, research data must be FAIR (Findable, Accessible, Interoperable, and Reusable) in order to advance the findability, reproducibility and reuse of research results. Besides the research data, all the processing steps on these data – as basis of scientific publications – have to be available, too.For good scientific practice, the resulting research software should be both open and adhere to the FAIR principles to allow full repeatability, reproducibility, and reuse. As compared to research data, research software should be both archived for reproducibility and actively maintained for reusability.The FAIR data principles do not require openness, but research software should be open source software. Established open source software licenses provide sufficient licensing options, such that it should be the rare exception to keep research software closed.We review and analyze the current state in this area in order to give recommendations for making research software FAIR and open.

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DMPonline Version 4.0: User-Led Innovation

International Journal of Digital Curation ◽

10.2218/ijdc.v9i1.312 ◽

2014 ◽

Vol 9 (1) ◽

pp. 193-219 ◽

Cited By ~ 2

Author(s):

Magdalena Getler ◽

Diana Sisu ◽

Sarah Jones ◽

Kerry Miller

Keyword(s):

Data Management ◽

Data Model ◽

Usability Testing ◽

Management Plan ◽

Research Support ◽

Web Based ◽

Iterative Development ◽

Development Approach ◽

Community Input ◽

Future Plans

DMPonline is a web-based tool to help researchers and research support staff produce data management and sharing plans. Between October and December 2012, we examined DMPonline in unprecedented detail. The results of this evaluation led to some major changes. We have shortened the DCC Checklist for a Data Management Plan and revised how this is used in the tool. We have also amended the data model for DMPonline, improved workflows and redesigned the user interface. This paper reports on the evaluation, outlining the methods used, the results gathered and how they have been acted upon. We conducted usability testing on v.3 of DMPonline and the v.4 beta prior to release. The results from these two rounds of usability testing are compared to validate the changes made. We also put forward future plans for a more iterative development approach and greater community input.

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