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The Transparent Research Object Vocabulary (TROV) is a key element of the Transparency Certified (TRACE) approach to ensuring research trustworthiness. In contrast with methods that entail repeating computations in part or in full to verify that the descriptions of methods included in a publication are sufficient to reproduce reported results, the TRACE approach depends on a controlled computing environment termed a Transparent Research System (TRS) to guarantee that accurate, sufficiently complete, and otherwise trustworthy records are captured when results are obtained in the first place. Records identifying (1) the digital artifacts and computations that yielded a research result, (2) the TRS that witnessed the artifacts and supervised the computations, and (3) the specific conditions enforced by the TRS that warrant trust in these records, together constitute a Transparent Research Object (TRO). Digital signatures provided by the TRS and by a trusted third-party timestamp authority (TSA) guarantee the integrity and authenticity of the TRO. The controlled vocabulary TROV provides means to declare and query the properties of a TRO, to enumerate the dimensions of trustworthiness the TRS asserts for a TRO, and to verify that each such assertion is warranted by the documented capabilities of the TRS. Our approach for describing, publishing, and working with TROs imposes no restrictions on how computational artifacts are packaged or otherwise shared, and aims to be interoperable with, rather than to replace, current and future Research Object standards, archival formats, and repository layouts.
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Annotation for transparent inquiry: Transparent data and analysis for qualitative research
How can authors using many individual pieces of qualitative data throughout a publication make their research transparent? In this paper we introduce Annotation for Transparent Inquiry (ATI), an approach to enhance transparency in qualitative research. ATI allows authors to connect specific passages in their publication with an annotation. These annotations provide additional information relevant to the passage and, when possible, include a link to one or more data sources underlying a claim; data sources are housed in a repository. After describing ATI’s conceptual and technological implementation, we report on its evaluation through a series of workshops conducted by the Qualitative Data Repository (QDR) and present initial results of the evaluation. The article ends with an outlook on next steps for the project.
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- Award ID(s):
- 1823950
- PAR ID:
- 10140037
- Date Published:
- Journal Name:
- IASSIST Quarterly
- Volume:
- 43
- Issue:
- 2
- ISSN:
- 0739-1137
- Page Range / eLocation ID:
- 1 to 9
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.29173/iq959
