The Genesy Model for a Blockchain-based Fair Ecosystem of Genomic Data

Carlini, Federico; Carlini, Roberto; Palma, Stefano Dalla; Pareschi, Remo; Zappone, Federico; Albanese, Daniele

doi:10.1109/sds49854.2020.9143897

Cited by 4 publications

(5 citation statements)

References 7 publications

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“…There are several other examples of data analysis supported by DLT in literature. 26 , 27 , 42 , 55 , 61 …”

Section: Resultsmentioning

confidence: 99%

“…Genetic data markets based on DLT and monetization of genetic data are hot topics. 13 , 15 , 24 , 26 , 34 , 38 , 41–44 , 49 , 55 In our review, we identified mostly technical and conceptual papers with varying degrees of maturity—but generally, a lot of hope is put into this novel technology. Several biotech startups are already building and operating genetic data markets based on DLT.…”

Section: Discussionmentioning

confidence: 99%

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A scoping review of distributed ledger technology in genomics: thematic analysis and directions for future research

Beyene

Toussaint

Thiebes

et al. 2022

Journal of the American Medical Informatics Association

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Objective Rising interests in distributed ledger technology (DLT) and genomics have sparked various interdisciplinary research streams with a proliferating number of scattered publications investigating the application of DLT in genomics. This review aims to uncover the current state of research on DLT in genomics, in terms of focal research themes and directions for future research. Materials and Methods We conducted a scoping review and thematic analysis. To identify the 60 relevant papers, we queried Scopus, Web of Science, PubMed, ACM Digital Library, IEEE Xplore, arXiv, and BiorXiv. Results Our analysis resulted in 7 focal themes on DLT in genomics discussed in literature, namely: (1) Data economy and sharing; (2) Data management; (3) Data protection; (4) Data storage; (5) Decentralized data analysis; (6) Proof of useful work; and (7) Ethical, legal, and social implications. Discussion Based on the identified themes, we present 7 future research directions: (1) Investigate opportunities for the application of DLT concepts other than Blockchain; (2) Explore people’s attitudes and behaviors regarding the commodification of genetic data through DLT-based genetic data markets; (3) Examine opportunities for joint consent management via DLT; (4) Investigate and evaluate data storage models appropriate for DLT; (5) Research the regulation-compliant use of DLT in healthcare information systems; (6) Investigate alternative consensus mechanisms based on Proof of Useful Work; and (7) Explore DLT-enabled approaches for the protection of genetic data ensuring user privacy. Conclusion While research on DLT in genomics is currently growing, there are many unresolved problems. This literature review outlines extant research and provides future directions for researchers and practitioners.

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“…There are several other examples of data analysis supported by DLT in literature. 26 , 27 , 42 , 55 , 61 …”

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A scoping review of distributed ledger technology in genomics: thematic analysis and directions for future research

Beyene

Toussaint

Thiebes

et al. 2022

Journal of the American Medical Informatics Association

View full text Add to dashboard Cite

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“…COBRA 60 (Section 6.3) represents an early stage project (still under design) and illustrates how the framework can help on selecting the right blockchain at design time. Genesy 8 (Section 6.4), represents a case in which the prior choice was a nonblockchain distributed ledger; so the framework helps to envision whether the particular requirements of the application call for an innovative solution other than the “traditional” blockchains. Photofied (Section 6.5) is a project already in production, which illustrates how to successfully migrate the underlying blockchain platform thanks to the insights gained from the framework application.…”

Section: Framework Evaluationmentioning

confidence: 99%

“…Genesy is an innovative blockchain platform which acts as an intermediary between the owner of the genomic data and its potential users (i.e., university research centers, private laboratories, hospitals, geneticists, etc.) 8 . It envisions the use of blockchain, cloud computing, and artificial intelligence as means to structure a new ecosystem that ensures the user's exclusive property and access to their genomic data, but also the possibility of participating in the benefits of the genomic research.…”

Section: Framework Evaluationmentioning

confidence: 99%

“…Even though the most popular blockchain implementation is Bitcoin, a myriad others are currently running or in advanced development. A number of important nonfinancial applications are emerging for different use cases that vary from logistic and supply chain management, 4,5 to those concerning the development of scalable, efficient and high‐impact decentralized solutions to social, economic and environmental innovation challenges, including energy, life science and health care 6‐9 …”

Section: Introductionmentioning

confidence: 99%

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Blockchain and cryptocurrencies: A classification and comparison of architecture drivers

Garriga

Palma

Arias³

et al. 2020

Concurrency and Computation

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Blockchain is a decentralized transaction and data management solution, the technological leap behind the success of Bitcoin and other cryptocurrencies. As the variety of existing blockchains and distributed ledgers continues to increase, adopters should focus on selecting the solution that best fits their needs and the requirements of their decentralized applications, rather than developing yet another blockchain from scratch. In this article we present a conceptual framework to aid software architects, developers, and decision makers to adopt the right blockchain technology. The framework exposes the interrelation between technological decisions and architectural features, capturing the knowledge from existing academic literature, industrial products, technical forums/blogs, and experts' feedback. We empirically show the applicability of our framework by dissecting the platforms behind Bitcoin and other top 10 cryptocurrencies, aided by a focus group with researchers and industry practitioners. Then, we leverage the framework together with key notions of the architectural tradeoff analysis method to analyze four real‐world blockchain case studies from industry and academia. Results shown that applying our framework leads to a deeper understanding of the architectural tradeoffs, allowing to assess technologies more objectively and select the one that best fit developers' needs, ultimately cutting costs, reducing time‐to‐market and accelerating return on investment.

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