Leveraging the global research infrastructure to characterize the impact of National Science Foundation research.
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| Title: | Leveraging the global research infrastructure to characterize the impact of National Science Foundation research. |
|---|---|
| Authors: | Jones, Jamaica1 (AUTHOR) jaj160@pitt.edu, Habermann, Ted2 (AUTHOR) |
| Source: | Information Services & Use. Feb-May2025, Vol. 45 Issue 1/2, p30-47. 18p. |
| Subject Terms: | *Artificial intelligence, *Research personnel, *Metadata, Author-publisher relations, Databases, Government agencies |
| Abstract: | The global research infrastructure (GRI) is made up of the repositories and organizations that provide persistent identifiers (PIDs) and metadata for many kinds of research objects and connect these objects to funders, research institutions, researchers, and one another using PIDs. The INFORMATE Project has combined three data sources to focus on understanding how the global research infrastructure might help the US National Science Foundation (NSF) and other federal agencies identify and characterize the impact of their support. In this paper we present INFORMATE observations of three data systems. The NSF Award database represents NSF funding while the NSF Public Access Repository (PAR) and CHORUS, as a proxy for the GRI, represent two different views of results of that funding. We compare the first at the level of awards and the second two at the level of published research articles. Our findings demonstrate that CHORUS datasets include significantly more NSF awards and more related papers than does PAR. Our findings also suggest that time plays a significant role in the inclusion of award metadata across the sources analyzed. Data in those sources travel very different journeys, each presenting different obstacles to metadata completeness and suggesting necessary actions on the parts of authors and publishers to ensure that publication and funding metadata are captured. We discuss these actions, as well as the implications that our findings have for emergent technologies such as artificial intelligence and natural language processing. [ABSTRACT FROM AUTHOR] |
| Copyright of Information Services & Use is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 185859322 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Leveraging the global research infrastructure to characterize the impact of National Science Foundation research. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jones%2C+Jamaica%22">Jones, Jamaica</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jaj160@pitt.edu</i><br /><searchLink fieldCode="AR" term="%22Habermann%2C+Ted%22">Habermann, Ted</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Information+Services+%26+Use%22">Information Services & Use</searchLink>. Feb-May2025, Vol. 45 Issue 1/2, p30-47. 18p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Research+personnel%22">Research personnel</searchLink><br />*<searchLink fieldCode="DE" term="%22Metadata%22">Metadata</searchLink><br /><searchLink fieldCode="DE" term="%22Author-publisher+relations%22">Author-publisher relations</searchLink><br /><searchLink fieldCode="DE" term="%22Databases%22">Databases</searchLink><br /><searchLink fieldCode="DE" term="%22Government+agencies%22">Government agencies</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The global research infrastructure (GRI) is made up of the repositories and organizations that provide persistent identifiers (PIDs) and metadata for many kinds of research objects and connect these objects to funders, research institutions, researchers, and one another using PIDs. The INFORMATE Project has combined three data sources to focus on understanding how the global research infrastructure might help the US National Science Foundation (NSF) and other federal agencies identify and characterize the impact of their support. In this paper we present INFORMATE observations of three data systems. The NSF Award database represents NSF funding while the NSF Public Access Repository (PAR) and CHORUS, as a proxy for the GRI, represent two different views of results of that funding. We compare the first at the level of awards and the second two at the level of published research articles. Our findings demonstrate that CHORUS datasets include significantly more NSF awards and more related papers than does PAR. Our findings also suggest that time plays a significant role in the inclusion of award metadata across the sources analyzed. Data in those sources travel very different journeys, each presenting different obstacles to metadata completeness and suggesting necessary actions on the parts of authors and publishers to ensure that publication and funding metadata are captured. We discuss these actions, as well as the implications that our findings have for emergent technologies such as artificial intelligence and natural language processing. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Information Services & Use is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=185859322 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1177/18758789251336079 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 30 Subjects: – SubjectFull: Artificial intelligence Type: general – SubjectFull: Research personnel Type: general – SubjectFull: Metadata Type: general – SubjectFull: Author-publisher relations Type: general – SubjectFull: Databases Type: general – SubjectFull: Government agencies Type: general Titles: – TitleFull: Leveraging the global research infrastructure to characterize the impact of National Science Foundation research. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jones, Jamaica – PersonEntity: Name: NameFull: Habermann, Ted IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb-May2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 01675265 Numbering: – Type: volume Value: 45 – Type: issue Value: 1/2 Titles: – TitleFull: Information Services & Use Type: main |
| ResultId | 1 |
