Accountable Bench-to-Bedside Data-Sharing Mechanism for Researchers

Author:

Seneviratne Oshani1ORCID,Adams Kacy1ORCID,McGuinness Deborah L.1ORCID

Affiliation:

1. Rensselaer Polytechnic Institute, USA

Abstract

We present a trustworthy mechanism for sharing, reusing, and repurposing data to address the challenge of the costly and time-consuming effort needed to bring an innovative idea from the bench (basic research) to the bedside (clinical level). Even though researchers may generate a solution on their own, other aspects of research, including peer review and dissemination of data/results, have an inherent social component. Compared with the centralized mechanisms of data-sharing (and the subsequent reuse and repurposing), many, if not all, aspects of these processes can be decentralized by using blockchain (for full decentralized and autonomous control), coupled with provenance (to ascertain how and where the resources have been leveraged) and incentive semantics (for characterizing how researchers would be rewarded for their contributions). By capturing metadata details at each step of the workflow, data will be easier to audit, verify, and merge with related datasets. It is common in settings where data is either sensitive or valuable (or both) to have formal data use agreements or sometimes less formal rules for reuse, which we have captured in smart contracts. A key innovative aspect of this work is the departure from the traditional natural language–based data use agreements to make these agreements more computable, resulting in enhanced usability and interoperability by a broader community. We have developed the Data Sharing Ontology, a structured vocabulary to guide various incentive mechanisms and criteria used in the decentralized protocol we introduced with smart contracts. Our solution can track data reuse, provide peer reviews on accountable data reuse, and report any violations, thus providing metrics for measuring data producers’ impact on reward structures and research measures. We introduce the SCIENCE-index designed to incentivize data-sharing in scientific research, which builds upon prior indices used in academic research, such as the h-index and the data-index. The SCIENCE-index is publicly available and automatically calculated by a smart contract based on an individual’s data sharing, reuse, and responsible stewardship activities. By incentivizing fair and honest data-related activities, the SCIENCE-index can help improve the speed, cost, and quality of scientific research. As an example application of this decentralized data-sharing framework, we demonstrate how this approach could radically improve the quality and the efficiency of scientific output in the setting of COVID-19 research data-sharing from the National COVID Cohort Collaborative (N3C).

Funder

Algorand Centres of Excellence program managed by the Algorand Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

General Medicine

Reference81 articles.

1. Alice Meadows. 2014. To Share or not to Share? That is the (Research Data) Question... Retrieved Jan 31, 2021 from https://scholarlykitchen.sspnet.org/2014/11/11/to-share-or-not-to-share-that-is-the-research-data-question

2. Charles Arthur. 2010. Businesses unwilling to share data but keen on government doing it. https://www.theguardian.com/technology/2010/jun/29/business-data-sharing-unwilling

3. Effective Choice in the Prisoner's Dilemma

4. Cryptocurrency Scams: Analysis and Perspectives

5. Publication bias: A problem in interpreting medical data;Begg Colin B.;Journal of the Royal Statistical Society: Series A (Statistics in Society),1988

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3