Academic Journal
Standards for Data Space Building Blocks.
| Τίτλος: | Standards for Data Space Building Blocks. |
|---|---|
| Συγγραφείς: | Noardo, Francesca, Atkinson, Rob, Bastin, Lucy, Maso, Joan, Simonis, Ingo, Villar, Alejandro, Voidrot, Marie-Françoise, Zaborowski, Piotr |
| Πηγή: | Remote Sensing; Oct2024, Vol. 16 Issue 20, p3824, 38p |
| Θεματικοί όροι: | Remote sensing, Information sharing |
| Περίληψη: | Data spaces are conceptualised as a trusted and secure distributed data ecosystem through which to exchange resources in the Web. Several efforts define guidance toward data space implementation, such as reference architectures and frameworks. As yet, the proposed data space solutions do not provide common and mature implementation options yet, and this gap between concept and implementation risks confusing users and developers. However, well-recognised organisations have been developing solutions and standards that address interoperability and good data exchange practices for decades, especially in the domain of geospatial information and remote sensing. Therefore, this paper compares the available solutions, providing the mapping and integration of the proposed blueprints to available interoperable standards. This concrete mapping, followed by a discussion with experts, results in a proposal of integrated reference data space building blocks, and an overview of the related standards and solutions. It is designed to support the effective practical implementation of data spaces and to guide future solution developments. This work can form the base for effective collaboration among different organisations, clearly identifying their scopes. A key role is apparent for standards and use cases from the remote sensing and geospatial domains, which have achieved wide adoption and maturity over the past years. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI 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.) | |
| Βάση Δεδομένων: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: Standards for Data Space Building Blocks. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Noardo%2C+Francesca%22">Noardo, Francesca</searchLink><br /><searchLink fieldCode="AR" term="%22Atkinson%2C+Rob%22">Atkinson, Rob</searchLink><br /><searchLink fieldCode="AR" term="%22Bastin%2C+Lucy%22">Bastin, Lucy</searchLink><br /><searchLink fieldCode="AR" term="%22Maso%2C+Joan%22">Maso, Joan</searchLink><br /><searchLink fieldCode="AR" term="%22Simonis%2C+Ingo%22">Simonis, Ingo</searchLink><br /><searchLink fieldCode="AR" term="%22Villar%2C+Alejandro%22">Villar, Alejandro</searchLink><br /><searchLink fieldCode="AR" term="%22Voidrot%2C+Marie-Françoise%22">Voidrot, Marie-Françoise</searchLink><br /><searchLink fieldCode="AR" term="%22Zaborowski%2C+Piotr%22">Zaborowski, Piotr</searchLink> – Name: TitleSource Label: Source Group: Src Data: Remote Sensing; Oct2024, Vol. 16 Issue 20, p3824, 38p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Remote+sensing%22">Remote sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Information+sharing%22">Information sharing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Data spaces are conceptualised as a trusted and secure distributed data ecosystem through which to exchange resources in the Web. Several efforts define guidance toward data space implementation, such as reference architectures and frameworks. As yet, the proposed data space solutions do not provide common and mature implementation options yet, and this gap between concept and implementation risks confusing users and developers. However, well-recognised organisations have been developing solutions and standards that address interoperability and good data exchange practices for decades, especially in the domain of geospatial information and remote sensing. Therefore, this paper compares the available solutions, providing the mapping and integration of the proposed blueprints to available interoperable standards. This concrete mapping, followed by a discussion with experts, results in a proposal of integrated reference data space building blocks, and an overview of the related standards and solutions. It is designed to support the effective practical implementation of data spaces and to guide future solution developments. This work can form the base for effective collaboration among different organisations, clearly identifying their scopes. A key role is apparent for standards and use cases from the remote sensing and geospatial domains, which have achieved wide adoption and maturity over the past years. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI 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.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs16203824 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 38 StartPage: 3824 Subjects: – SubjectFull: Remote sensing Type: general – SubjectFull: Information sharing Type: general Titles: – TitleFull: Standards for Data Space Building Blocks. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Noardo, Francesca – PersonEntity: Name: NameFull: Atkinson, Rob – PersonEntity: Name: NameFull: Bastin, Lucy – PersonEntity: Name: NameFull: Maso, Joan – PersonEntity: Name: NameFull: Simonis, Ingo – PersonEntity: Name: NameFull: Villar, Alejandro – PersonEntity: Name: NameFull: Voidrot, Marie-Françoise – PersonEntity: Name: NameFull: Zaborowski, Piotr IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 10 Text: Oct2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 16 – Type: issue Value: 20 Titles: – TitleFull: Remote Sensing Type: main |
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