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Showing 1–7 of 7 results
Advanced filters: Author: Shelley Stall Clear advanced filters
  • All disciplines should follow the geosciences and demand best practice for publishing and sharing data, argue Shelley Stall and colleagues.

    • Shelley Stall
    • Lynn Yarmey
    • Lesley Wyborn
    Comments & Opinion
    Nature
    Volume: 570, P: 27-29
  • An analysis of more than 50 collaborations shows the secrets of success, write Joel Cutcher-Gershenfeld and colleagues from the Stakeholder Alignment Collaborative.

    • Joel Cutcher-Gershenfeld
    • Karen S. Baker
    • Ilya Zaslavsky
    Comments & Opinion
    Nature
    Volume: 543, P: 615-617
  • Software and data citation are emerging best practices in scholarly communication. This article provides structured guidance to the academic publishing community on how to implement software and data citation in publishing workflows. These best practices support the verifiability and reproducibility of academic and scientific results, sharing and reuse of valuable data and software tools, and attribution to the creators of the software and data. While data citation is increasingly well-established, software citation is rapidly maturing. Software is now recognized as a key research result and resource, requiring the same level of transparency, accessibility, and disclosure as data. Software and data that support academic or scientific results should be preserved and shared in scientific repositories that support these digital object types for discovery, transparency, and use by other researchers. These goals can be supported by citing these products in the Reference Section of articles and effectively associating them to the software and data preserved in scientific repositories. Publishers need to markup these references in a specific way to enable downstream processes.

    • Shelley Stall
    • Geoffrey Bilder
    • Timothy Clark
    Comments & OpinionOpen Access
    Scientific Data
    Volume: 10, P: 1-11
  • As big data, open data, and open science advance to increase access to complex and large datasets for innovation, discovery, and decision-making, Indigenous Peoples’ rights to control and access their data within these data environments remain limited. Operationalizing the FAIR Principles for scientific data with the CARE Principles for Indigenous Data Governance enhances machine actionability and brings people and purpose to the fore to resolve Indigenous Peoples’ rights to and interests in their data across the data lifecycle.

    • Stephanie Russo Carroll
    • Edit Herczog
    • Shelley Stall
    Comments & OpinionOpen Access
    Scientific Data
    Volume: 8, P: 1-6