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      Ten rules to increase the societal value of earth observations

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          Abstract

          Earth Observation (EO) data play an important role in our society today, but there is still tremendous opportunity to improve how these data are used to affect change. In this paper, we provide guidance to help data providers and intermediaries within the EO value chain (from data to applications) increase the societal value of the EO data, information, and data products that they work with. We first describe the EO value chain as a conceptual framework for how data are translated and applied for societal benefit. We then introduce three approaches that are often used to assess and improve the EO value chain. Finally, we present “10 rules” that can be implemented to increase the societal benefits of Earth science information. The 10 rules emphasize meeting user needs, problem-solving within interdisciplinary teams, and long-term sustainable solutions. Some rules focus on a specific segment of the value chain or phase in the problem-solving process, while others are relevant to the value chain or process as a whole. Each rule includes at least one case study example to illustrate the key points. The rules are loosely organized according to project management principles with the initial rules focusing on defining problems, planning for data use, creating effective teams, and examining a diverse selection of solutions. The next set of rules are best applied throughout a project, and include such concepts as evaluation, interoperability, trust, adoption, and documentation. Finally, the last rule addresses the challenge of determining when to close a project.

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          Self-efficacy: Toward a unifying theory of behavioral change.

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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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              Are there social limits to adaptation to climate change?

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Earth Science Informatics
                Earth Sci Inform
                Springer Science and Business Media LLC
                1865-0473
                1865-0481
                June 2020
                March 03 2020
                June 2020
                : 13
                : 2
                : 233-247
                Article
                10.1007/s12145-020-00453-w
                ff39d107-711f-4b8b-accb-f605fde17e1a
                © 2020

                https://creativecommons.org/licenses/by/4.0

                https://creativecommons.org/licenses/by/4.0

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