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      Mobilizing primary biodiversity records in environmental assessments in Spain

      1 , 2 , 1 , 2 , 1 , 2 , 2 , 1
      Biodiversity Data Journal
      Pensoft Publishers

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          Abstract

          Environmental Assessment is an essential tool for minimising the environmental impact of human development, generating huge amounts of biodiversity data. However, much of this information, also in Spain, remains inaccessible after being partially included in Records of Decision (RODs). As a result, these dark data remain under-utilised, limiting their potential to provide information for conservation efforts and decision-making processes.This dataset compiles 4,630 species records derived from RODs published in the Spanish Official State Gazette between 2013 and 2023, focusing on catalogued species listed in the Spanish Catalogue of Threatened Species and the List of Wild Species under Special Protection Regime. The data were collected using automated text-mining techniques and manually curated to correct errors and classify records as primary biodiversity records (PBRs), absences or literature-based occurrences. A total of 1,290 PBRs, 170 absences and 3,391 literature-based records were identified. PBRs were georeferenced and standardised according to the Darwin Core Standard. This dataset offers valuable insights into the presence and distribution of 31 non-Chiroptera species and 28 Chiroptera species, including 12 endangered (EN), 31 vulnerable (VU) and 16 listed species. The publication of these data in a FAIR (Findable, Accessible, Interoperable and Reusable) format via the Global Biodiversity Information Facility enhances their accessibility for future conservation planning and decision-making processes.

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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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            Shedding Light on the Dark Data in the Long Tail of Science

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              Make scientific data FAIR

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                Author and article information

                Contributors
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                Journal
                Biodiversity Data Journal
                BDJ
                Pensoft Publishers
                1314-2828
                1314-2836
                March 25 2025
                March 25 2025
                : 13
                Affiliations
                [1 ]Universidad de Navarra, Instituto de Biodiversidad y Medioambiente BIOMA, Irunlarrea 1, 31008, Pamplona, Spain
                [2 ]Universidad de Navarra, Facultad de Ciencias, Departamento de Biología Ambiental, Biodiversity Data Analytics and Environmental Quality (BEQ), Irunlarrea 1, 31008, Pamplona, Spain
                Article
                10.3897/BDJ.13.e142302
                8aaaf79c-8494-49b2-b996-1a5d4784e68a
                © 2025

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

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