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Trusting records: is Blockchain technology the answer?
Abstract
Purpose: The purpose of this paper is to explore the value of Blockchain technology as a solution to creating and preserving trustworthy digital records, presenting some of the limitations, risks and opportunities of the approach. Design/methodology/approach: The methodological approach involves using the requirements embedded in records management and digital preservation standards, specifically ISO 15,489, ARMA’s Generally Accepted Recordkeeping Principles, ISO 14,721 and ISO 16,363, as a general evaluative framework for a risk-based assessment of a specific proposed implementation of Blockchain technology for a land registry system in a developing country. Findings: The results of the analysis suggest that Blockchain technology can be used to address issues associated with information integrity in the present and near term, assuming proper security architecture and infrastructure management controls. It does not, however, guarantee reliability of information in the first place, and would have several limitations as a long-term solution for maintaining trustworthy digital records. Originality/value: This paper contributes an original analysis of the application of Blockchain technology for recordkeeping.
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Metadata
- Authors
- Lemieux, V. L.
- Venue
- Records Management Journal
- Publisher
- Emerald
- Published
- 2016-07-18
- Volume
- 26
- Issue
- 2
- Pages
- 110-139
- ISSN
- 0956-5698 (ISSN-L)
- OpenAlex
- W2531564265
- Cited by
- 497
- References
- 0
- FWCI
- 112.96
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.emerald.com/insight/site-policies (tdm)
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- Lemieux, V. L. (2016). Trusting records: is Blockchain technology the answer? Records Management Journal. https://doi.org/10.1108/rmj-12-2015-0042
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
