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      FAIR Data and Services in Biodiversity Science and Geoscience

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      Data Intelligence

      MIT Press - Journals

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          Abstract

          We examine the intersection of the FAIR principles (Findable, Accessible, Interoperable and Reusable), the challenges and opportunities presented by the aggregation of widely distributed and heterogeneous data about biological and geological specimens, and the use of the Digital Object Architecture (DOA) data model and components as an approach to solving those challenges that offers adherence to the FAIR principles as an integral characteristic. This approach will be prototyped in the Distributed System of Scientific Collections (DiSSCo) project, the pan-European Research Infrastructure which aims to unify over 110 natural science collections across 21 countries. We take each of the FAIR principles, discuss them as requirements in the creation of a seamless virtual collection of bio/geo specimen data, and map those requirements to Digital Object components and facilities such as persistent identification, extended data typing, and the use of an additional level of abstraction to normalize existing heterogeneous data structures. The FAIR principles inform and motivate the work and the DO Architecture provides the technical vision to create the seamless virtual collection vitally needed to address scientific questions of societal importance.

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          Most cited references 8

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          The next generation of natural history collections

          The last 50 years have witnessed rapid changes in the ways that natural history specimens are collected, preserved, analyzed, and documented. Those changes have produced unprecedented access to specimens, images, and data as well as impressive research results in organismal biology. The stage is now set for a new generation of collecting, preserving, analyzing, and integrating biological samples—a generation devoted to interdisciplinary research into complex biological interactions and processes. Next-generation collections may be essential for breakthrough research on the spread of infectious diseases, feeding Earth's growing population, adapting to climate change, and other grand research challenges. A decade-long investment in research collection infrastructure will be needed.
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            A framework for distributed digital object services

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              Different roles and mutual dependencies of data, information, and knowledge — An AI perspective on their integration

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                Author and article information

                Journal
                Data Intelligence
                Data Intelligence
                MIT Press - Journals
                2641-435X
                January 2020
                January 2020
                : 2
                : 1-2
                : 122-130
                Affiliations
                [1 ]Corporation for National Research Initiatives (CNRI), Reston, Virginia 20191, USA
                [2 ]Naturalis Biodiversity Center, 2333 CR Leiden, The Netherlands
                [3 ]School of Computer Science and Informatics, Cardiff University, Cardiff CF24 3AA, Cardiff, UK
                Article
                10.1162/dint_a_00034
                © 2020

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