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DATASET
Estimated_Personnel_in_the_PRC_Armed_Forces_2016_and_2020 .csv (1.11 kB)
DOCUMENT
Report - Military Modernization in the Indo-Pacific.pdf (1.16 MB)
DATASET
Selected_PLA_Weaponry_2020.csv (1.51 kB)
.MP4
Seminar_Recording_1920x1080_GMT20220915-020051.mp4 (376.18 MB)
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Datasets related to Key Trends and Drivers in Military Modernization in the Indo-Pacific: Implications for Australia and Responses

dataset
posted on 2022-09-16, 02:55 authored by Andrew Tan, Bates GillBates Gill, Yves-Heng LimYves-Heng Lim, Antoine Levesques, Adam LockyerAdam Lockyer, Fred SmithFred Smith, Rahul Roy-Chaudhury, Viraj Solanki

This dataset underlies the report generated entitled "Key Trends and Drivers in Military Modernization in the Indo-Pacific: Implications for Australia and Responses" by Bates Gill, Yves-Heng Lim, Antoine Levesques, Adam Lockyer, Fred Smith, Rahul Roy-Chaudhury, Viraj Solanki and Andrew T. H. Tan. 

This project addresses the priority Defence policy topic of Accelerating Regional Military Modernization (and Asymmetric Advantages). It assesses the trends, attributes and drivers of accelerating military modernization in the Indo-Pacific, in order to understand and clearly delineate the challenges facing Australia. The report then proceeds to examine the roles of the key actors in this phenomenon, namely, China, the United States and India. Finally, the project puts forward and assesses potential Australian responses in the face of the region’s accelerating military modernization dynamic.


The dataset is made up of the following:

1. Estimated_Personnel_in_the_PRC_Armed_Forces_2016_and_2020.csv

2. Selected_PLA_Weaponry_2020.csv 

3. Report - Military Modernization in the Indo-Pacific.pdf 

4. Seminar_Recording_1920x1080_GMT20220915-020051.mp4

Funding

This project was funded by the Department of Defence (Australia) under its Strategic Policy Grants Program 202021-0235 Macquarie University, from 1 July 2021 until 30 September 2022.

History

Q/A Log

  • Institutional review completed

FAIR Self Assessment Summary

This text has been generated from a tool that has been adapted from the ARDC FAIR Assessment Tool Findable -------- Does the dataset have any identifiers assigned? Global Is the dataset identifier included in all metadata records/files describing the data? Yes How is the data described with metadata? Comprehensively (see suggestion) using a recognised formal machine-readable metadata schema What type of repository or registry is the metadata record in? Data is in one place but discoverable through several registries Accessible ---------- How accessible is the data? Publicly accessible Is the data available online without requiring specialised protocols or tools once access has been approved? File download from online location Will the metadata record be available even if the data is no longer available? Yes Interoperable ------------- What (file) format(s) is the data available in? In a structured, open standard, machine-readable format What best describes the types of vocabularies/ontologies/tagging schemas used to define the data elements? Standardised vocabularies/ontologies/schema without global identifiers How is the metadata linked to other data and metadata (to enhance context and clearly indicate relationships)? There are no links to other metadata Reusable -------- Which of the following best describes the license/usage rights attached to the data? Standard machine-readable license (e.g. Creative Commons) How much provenance information has been captured to facilitate data reuse? Partially recorded

FAIR Self Assessment Rating

  • 4 Stars

Data Sensitivity

  • General

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