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      Data Shepherding in Nanotechnology. The Exposure Field Campaign Template

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          Abstract

          In this paper, we demonstrate the realization process of a pragmatic approach on developing a template for capturing field monitoring data in nanomanufacturing processes. The template serves the fundamental principles which make data scientifically Findable, Accessible, Interoperable and Reusable (FAIR principles), as well as encouraging individuals to reuse it. In our case, the data shepherds’ (the guider of data) template creation workflow consists of the following steps: (1) Identify relevant stakeholders, (2) Distribute questionnaires to capture a general description of the data to be generated, (3) Understand the needs and requirements of each stakeholder, (4) Interactive simple communication with the stakeholders for variables/descriptors selection, and (5) Design of the template and annotation of descriptors. We provide an annotated template for capturing exposure field campaign monitoring data, and increase their interoperability, while comparing it with existing templates. This paper enables the data creators of exposure field campaign data to store data in a FAIR way and helps the scientific community, such as data shepherds, by avoiding extensive steps for template creation and by utilizing the pragmatic structure and/or the template proposed herein, in the case of a nanotechnology project (Anticipating Safety Issues at the Design of Nano Product Development, ASINA).

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          The FAIR Guiding Principles for scientific data management and stewardship

          There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
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            FAIR Principles: Interpretations and Implementation Considerations

            The FAIR principles have been widely cited, endorsed and adopted by a broad range of stakeholders since their publication in 2016. By intention, the 15 FAIR guiding principles do not dictate specific technological implementations, but provide guidance for improving Findability, Accessibility, Interoperability and Reusability of digital resources. This has likely contributed to the broad adoption of the FAIR principles, because individual stakeholder communities can implement their own FAIR solutions. However, it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations. Thus, while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways, for true interoperability we need to support convergence in implementation choices that are widely accessible and (re)-usable. We introduce the concept of FAIR implementation considerations to assist accelerated global participation and convergence towards accessible, robust, widespread and consistent FAIR implementations. Any self-identified stakeholder community may either choose to reuse solutions from existing implementations, or when they spot a gap, accept the challenge to create the needed solution, which, ideally, can be used again by other communities in the future. Here, we provide interpretations and implementation considerations (choices and challenges) for each FAIR principle.
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              The FAIR guiding principles for data stewardship: fair enough?

              The FAIR guiding principles for research data stewardship (findability, accessibility, interoperability, and reusability) look set to become a cornerstone of research in the life sciences. A critical appraisal of these principles in light of ongoing discussions and developments about data sharing is in order. The FAIR principles point the way forward for facilitating data sharing more systematically—provided that a number of ethical, methodological, and organisational challenges are addressed as well.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Nanomaterials (Basel)
                Nanomaterials (Basel)
                nanomaterials
                Nanomaterials
                MDPI
                2079-4991
                13 July 2021
                July 2021
                : 11
                : 7
                : 1818
                Affiliations
                [1 ]Transgero Limited, Cullinagh, Newcastle West, V42V384 Limerick, Ireland; Finbarr.murphy@ 123456transgero.eu
                [2 ]Department of Accounting and Finance, Kemmy Business School, University of Limerick, V94T9PX Limerick, Ireland
                [3 ]Air Pollution Management, Willemoesgade 16, st tv, DK-2100 Copenhagen, Denmark; joonas.apm@ 123456gmail.com
                [4 ]ARCHE Consulting, Liefkensstraat 35D, B-9032 Wondelgem, Belgium
                [5 ]Institute for Atmospheric and Earth System Research (INAR), University of Helsinki, PL 64, FI-00014 Helsinki, Finland
                [6 ]Institute of Atmospheric Sciences and Climate (CNR-ISAC) Via Gobetti 101, 40129 Bologna, Italy; s.trabucco@ 123456isac.cnr.it (S.T.); b.delsecco@ 123456isac.cnr.it (B.D.S.)
                [7 ]Environmental Informatics Research Group, Department of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; tharvanitis@ 123456meng.auth.gr
                Author notes
                Author information
                https://orcid.org/0000-0002-2263-0279
                https://orcid.org/0000-0002-6769-1999
                https://orcid.org/0000-0002-7463-7923
                https://orcid.org/0000-0001-8881-4575
                Article
                nanomaterials-11-01818
                10.3390/nano11071818
                8308211
                34361203
                3bbdc5e5-f407-4598-82a7-669619fd6285
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 15 June 2021
                : 09 July 2021
                Categories
                Article

                nanotechnology,exposure assessment,field campaigns,fair data,data management plan

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