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

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dc.audienceAudience::Big Data Special Interest Groupen_US
dc.contributor.authorUzwyshyn, Raymond
dc.coverage.spatialLocation::United States of Americaen_US
dc.date.accessioned2022-07-06T11:18:09Z
dc.date.available2022-07-06
dc.date.available2022-07-06T11:18:09Z
dc.date.issued2022-07-06
dc.description.abstractOnline 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.en_US
dc.identifier.urihttps://2022.ifla.org/
dc.identifier.urihttps://repository.ifla.org/handle/20.500.14598/1975
dc.language.isoenen_US
dc.publisherInternational Federation of Library Associations and Institutions (IFLA)en_US
dc.relation.ispartofseries87th IFLA World Library and Information Congress (WLIC) / 2022 in Dublin, Ireland;
dc.rights.holderRaymond Uzwyshynen_US
dc.rights.licenseCC BY 4.0en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.subjectSubject::Artificial intelligenceen_US
dc.subjectSubject::Net neutralityen_US
dc.subjectSubject::Big dataen_US
dc.subjectSubject::Librariesen_US
dc.subjectSubject::Research data repositoriesen_US
dc.subjectSubject::Researchen_US
dc.titleOnline Data Research Repositories and Digital Scholarly Ecosystems: From Research Data and Datasets to Artificial Intelligence and Discoveryen_US
dc.typeArticlesen_US
dc.typeEvents Materialsen_US
ifla.UnitUnits::Special Interest Group::Big Data Special Interest Groupen_US
ifla.oPubId0en_US

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