The Embassy of Good Science - User contributions [en]

Theme:0bd48e3b-3590-44ae-a21b-7cf2b425d6cb

2021-03-26T15:33:08Z

Giulia.Inguaggiato:

{{Theme
|Theme Type=Good Practices
|Has Parent Theme=Theme:6f515a18-ce5f-42b0-8741-27248f6435a0
|Title=FAIR principles: sharing data for maximisation of results
|Is About=The FAIR principles describe the ideal way data should be stored and shared to maximise its usefulness and allow the whole research community to benefit from it. FAIR stands for “Findable, Accessible, Interoperable and Re-usable”. The main goal of the FAIR principles is to enable the "‘long term care' of valuable digital assets"<ref>Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3:160018 doi: 10.1038/sdata.2016.18 (2016).</ref>, in order to allow them to be reused for future research. The scope of these principles goes beyond the data in the conventional sense but includes all the components of the research process, including the algorithms and workflows that lead to the resulting data. This means that FAIR data management supports both human-driven and machine-driven data discovery and exploitation activities.
<references />
|Important Because=While conducting our research we (as researchers) produce different kind of data: we write research designs and workflows, we collect raw data, we analyse them, we write about them. However, most of the time the only part of our research which is publicly shared is represented by the articles which we produce as a result of the entire research cycle. In fact, all phases of research could be of potential interest for other researchers, who could reuse the data we produce in a different way.

By maximizing access to and re-use of research data we can optimize the impact of the data that we produce. In line with the principles of Open Science, good data management becomes a fundamental instrument to promote and facilitate the reusability, accessibility and exploitation of research data, thereby allowing for the generation of new knowledge.<ref>Vicente-Saez R., C. Martinez-Fuentes. Open Science now: A systematic literature review for an integrated definition. Journal of Business Research (2018) 88: 428-236.</ref>

In 2014, a workshop named [https://www.lorentzcenter.nl/lc/web/2014/602/info.php3?wsid=602 ‘Jointly Designing a data FAIRPORT’] was organized in Leiden by a group of academic and private sector stakeholders. The aim of the workshop was to improve the infrastructure supporting humans and machines in the discovery and analysis of scientific data and their associated algorithms and workflows. A set of guidelines was developed by the participants to support data producers, scientists and data publishers to take full advantage of the generation of data.<ref>Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3:160018 doi: 10.1038/sdata.2016.18 (2016).</ref> Four foundational principles were agreed by the community to allow stakeholders to discover, integrate, re-use and adequately cite the massive quantities of information being generated by contemporary data intensive science.

These foundational principles were subsequently improved, detailed and elaborated on by the [https://www.force11.org/group/fairgroup/fairprinciples FORCE 11] working group, which is still engaged in fostering the implementation and continued update of the FAIR principles. These foundational principles are known as FAIR principles, see below for specification of the principles. <ref>Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3:160018 doi: 10.1038/sdata.2016.18 (2016).</ref>

==='''FAIR principles'''===
'''Findable:'''

#(Meta)data are assigned a globally unique and eternally persistent identifier.
#Data are described with rich metadata.
#(meta)data are registered or indexed in a searchable resource.
#Metadata specify the data identifier.

'''Accessible'''

#(meta)data are retrievable by their identifier using a standardized communications protocol.
#the protocol is open, free, and universally implementable.
#the protocol allows for an authentication and authorization procedure, where necessary.
#metadata are accessible, even when the data are no longer available.

'''Interoperable'''

#(meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
#(meta)data use vocabularies that follow FAIR principles.
#(meta)data include qualified references to other (meta)data.

'''Re-usable'''

#meta(data) have a plurality of accurate and relevant attributes.
#(meta)data are released with a clear and accessible data usage license.
#(meta)data are associated with their provenance.
#(meta)data meet domain-relevant community standards.

All researchers at all levels but also society as a whole can benefit from the implementation of FAIR data management. Granting access to data produced throughout the entire research cycle is also important on a global scale since it allows researchers who operate in countries with less developed research infrastructures to benefit from others scientists’ work.<ref>The FAIR Data Principles (FORCE 11 discussion forum) [consulted on 02/01/2018]. Available at: https://www.force11.org/group/fairgroup/fairprinciples</ref>
<references />
|Important For=All stakeholders in research
|Has Best Practice=The European Commission decided to run a pilot under Horizon 2020 the [http://ec.europa.eu/research/participants/data/ref/h2020/other/hi/oa-pilot/h2020-hi-erc-oa-guide_en.pdf Open Research Data Pilot] (ORD pilot). Which aims to improve and maximise access to and re-use of research data generated by Horizon 2020 projects. This initiative supports and requires the application of FAIR principles within the H2020 research projects, and therefore it strives to maximise the output and outreach of publicly funded research.
|Has Reference=a
}}
{{Related To
|Related To Resource=Resource:B47afc7d-44d6-4713-a209-953d58e81778;Resource:9c917ab2-c01d-446b-89c1-a9cd415afb00;Resource:695b5c9b-f3ac-4fc8-8e20-1dfd5f7347ff;Resource:E1dd8012-da5a-494c-8e15-3e3c17e4a587
|Related To Theme=Theme:06925397-5843-495d-a22d-3e983bdcb99e;Theme:Ecc7ac02-6e53-4634-b053-91045c50390c
}}
{{Tags
|Has Virtue And Value=Honesty; Transparency
|Has Good Practice And Misconduct=Data Management; Data sharing
}}

Theme:E30b6f25-2071-4f6c-80ed-7c22f9d0e4ab

2021-03-25T15:01:57Z

Giulia.Inguaggiato:

{{Theme
|Theme Type=Good Practices
|Has Parent Theme=Theme:639528ea-d2c2-4565-8b44-15bb9646f74b
|Title=Research integrity in practice: dealing with everyday dilemmas
|Is About=For some, an important aspect of research integrity (RI) training is to make clear links between educational material and the “real life” practices of researchers. Discussing dilemmas in practice can be a valuable method to reflect broadly on how to be ‘good’ researchers.
|Important Because=As researchers, we often face RI dilemmas. For example, a dilemma about the inclusion of an extra author in a publication. Most of the time, dilemmas are implicitly or explicitly related to relational aspects (e.g. collaboration with a supervisor or boss). Although guidelines and codes of conduct provide us with guidance on how to act, often we face difficult situations in which contrasting values are at stake. While developing RI training, it is important to reflect on researchers’ day-to-day dilemmas in addition to theoretical knowledge of RI issues (e.g. codes of conduct, best practices, and regulations). This, however, can be challenging. It entails building a bridge between theory and practice, and reflecting on how to act in situations of ethical uncertainty.
|Important For=phd students; Supervisors; Postdocs; Senior researchers; Junior researchers; Research integrity trainers
|Has Best Practice=The European Commission funded VIRT2UE project has designed a set of practical tools for recognizing and dealing with RI dilemmas in practice. One of these tools is the so called ‘Virtues, Values and Norms in Perspective’ exercise. In this exercise, inspired by a [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5236068/ virtue ethics approach to RI education], <ref>Pennock T. R., O'Rourke M. Developing a Scientific Virtue-Based Approach to Science Ethics Training. Sci Eng Ethics. 2017; 23(1): 243–262.</ref> participants are asked to reflect on a concrete dilemma experienced by one of the participants. By engaging in a dialogue, trainees are asked to put themselves in the shoes of the people involved in the case at stake and reflect on which values would be important for each of them. Then they are asked to reflect on which virtues are required to deal with the dilemma at stake: are they in conflict with each other? How are they related to salient norms? Which virtue is the most important in this situation? What is needed (concretely) to act in accordance with that virtue?

This exercise aims at fostering reflection in oneself by means of understanding the concepts of virtues/values and norms and their relationship with practice.

Another initiative is the [https://www.eur.nl/sites/corporate/files/24708_integriteitsspel_interactief_2016.pdf Rotterdam Dilemma Game], <ref>Dilemma game. Available at: [https://www.eur.nl/sites/corporate/files/24708_integriteitsspel_interactief_2016.pdf https://www.eur.nl/sites/corpo...]</ref> which focuses less on virtue ethics but nonetheless provides structure to discuss RI dilemmas.
<references />
|Has Reference=a
}}
{{Related To
|Related To Resource=Resource:5bbdd729-8f96-432a-a0ee-56510e343d01
}}
{{Tags}}

User:Giulia.Inguaggiato

2021-03-25T15:00:32Z

Giulia.Inguaggiato: create user page