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This version is not peer-reviewed.

Plan for Constructing DataDiscoveryLab

Submitted:

20 April 2023

Posted:

27 April 2023

Read the latest preprint version here

Abstract
DataDiscoveryLab is a software tool that enables users to recommend possible pathways to their research with references by extracting valuable insights from academic articles by parsing them into text and figures and processing the image data using computer vision algorithms. The software creates two databases for text-based purposes, one for titles, figure captions, and references, and another for abstracts, introductions, methods, and results using NLP techniques. The software then compares these databases to users' research questions, finds similarities, and presents the findings. Additionally, the software takes data from researchers' scientific software and devices to compare with the current figure-based databases, creating a loop until the best answer and pathways to research and articles to recommend can be found. This tool provides valuable insights and context for researchers, helping them make informed decisions about their research.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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