From Research Data and Datasets to Artificial Intelligence and Discovery: Online Data Research Repositories and Digital Scholarly Ecosystems

Date

2022-07-23

Authors

Uzwyshyn, Raymond

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Publisher

International Federation of Library Associations

Abstract

Online networked data research repositories allow sharing and archiving of research data for open science and global research. This sharing opens data to modern interoperability and metadata for search, retrieval, and larger possibilities of open scholarly research ecosystems. Data research repositories are currently being leveraged to accelerate global research, promote international collaboration, and innovate on levels previously thought impossible. Research data repositories may also link data to further content from online publications and other digital communication and aggregation tools. This article pragmatically overviews such a data and content-centered ecosystem at Texas State University Libraries in the United States. The research then discusses the ecosystem's next level of planning and construction involving both bigger data possibilities for AI infrastructures\enabling researchers and their data towards Deep Learning (Neural Net) possibilities. The research uses examples of recent digitized medical image datasets for Cancer/melanoma detection through Deep Learning/Neural Net for global open science possibilities. These methodologies show large promise in making good use of online open data repositories, digital library ecosystems and online datasets. Recent AI research highlights the utility of several easily available online open-source digital library data repository and ecosystem components. An online data-centered research ecosystem accelerates open science, research and discovery on global levels. This open-source ecosystem and software infrastructure may be easily replicated by research institutions. Creating open online data infrastructures for research communities enables future global data and research, collaboration and the advancement of science, the academic research cycle on networked global levels.

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Keywords

artificial intelligence, neural nets, deep learning, big data, research data repositories, online data research ecosystems, online data research repositories, Dataverse, Texas Data Repository

Citation

Uzwyshyn, R. (2022). From research data and datasets to Artificial Intelligence and discovery: Online data research repositories and digital scholarly ecosystems. Proceedings for International Federation of Library Associations World Library Information Congress (WLIC 2022).

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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