Data management plans are free-form text documents describing the data used and produced in scientific experiments.The complexity of data-driven experiments requires precise descriptions of tools and datasets used in computations to enable their reproducibility and reuse.Data management plans fall short of these requirements.
In this paper, we propose machine-actionable data management plans that Design and Performance Analysis of Axial Flux Permanent Magnet Machines with Double-Stator Dislocation Using a Combined Wye-Delta Connection cover the same themes as standard data management plans, but particular sections are filled with information obtained from existing tools.We present mapping of tools from the domains of digital preservation, reproducible research, open science, and data repositories to data management plan sections.Thus, we identify the requirements for a good solution and identify its limitations.
We also propose a machine-actionable data model that enables information integration.The model uses ontologies and Competition, Drought, Season Length? Disentangling Key Factors for Local Adaptation in Two Mediterranean Annuals across Combined Macroclimatic and Microclimatic Aridity Gradients is based on existing standards.