The pursuit of approaches to federate data to accelerate Alzheimer's disease and related dementia research: GAAIN, DPUK, and ADDI.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-05-25 eCollection Date: 2023-01-01 DOI:10.3389/fninf.2023.1175689
Arthur W Toga, Mukta Phatak, Ioannis Pappas, Simon Thompson, Caitlin P McHugh, Matthew H S Clement, Sarah Bauermeister, Tetsuyuki Maruyama, John Gallacher
{"title":"The pursuit of approaches to federate data to accelerate Alzheimer's disease and related dementia research: GAAIN, DPUK, and ADDI.","authors":"Arthur W Toga, Mukta Phatak, Ioannis Pappas, Simon Thompson, Caitlin P McHugh, Matthew H S Clement, Sarah Bauermeister, Tetsuyuki Maruyama, John Gallacher","doi":"10.3389/fninf.2023.1175689","DOIUrl":null,"url":null,"abstract":"<p><p>There is common consensus that data sharing accelerates science. Data sharing enhances the utility of data and promotes the creation and competition of scientific ideas. Within the Alzheimer's disease and related dementias (ADRD) community, data types and modalities are spread across many organizations, geographies, and governance structures. The ADRD community is not alone in facing these challenges, however, the problem is even more difficult because of the need to share complex biomarker data from centers around the world. Heavy-handed data sharing mandates have, to date, been met with limited success and often outright resistance. Interest in making data Findable, Accessible, Interoperable, and Reusable (FAIR) has often resulted in centralized platforms. However, when data governance and sovereignty structures do not allow the movement of data, other methods, such as federation, must be pursued. Implementation of fully federated data approaches are not without their challenges. The user experience may become more complicated, and federated analysis of unstructured data types remains challenging. Advancement in federated data sharing should be accompanied by improvement in federated learning methodologies so that federated data sharing becomes functionally equivalent to direct access to record level data. In this article, we discuss federated data sharing approaches implemented by three data platforms in the ADRD field: Dementia's Platform UK (DPUK) in 2014, the Global Alzheimer's Association Interactive Network (GAAIN) in 2012, and the Alzheimer's Disease Data Initiative (ADDI) in 2020. We conclude by addressing open questions that the research community needs to solve together.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":"17 ","pages":"1175689"},"PeriodicalIF":4.6000,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248126/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fninf.2023.1175689","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0

Abstract

There is common consensus that data sharing accelerates science. Data sharing enhances the utility of data and promotes the creation and competition of scientific ideas. Within the Alzheimer's disease and related dementias (ADRD) community, data types and modalities are spread across many organizations, geographies, and governance structures. The ADRD community is not alone in facing these challenges, however, the problem is even more difficult because of the need to share complex biomarker data from centers around the world. Heavy-handed data sharing mandates have, to date, been met with limited success and often outright resistance. Interest in making data Findable, Accessible, Interoperable, and Reusable (FAIR) has often resulted in centralized platforms. However, when data governance and sovereignty structures do not allow the movement of data, other methods, such as federation, must be pursued. Implementation of fully federated data approaches are not without their challenges. The user experience may become more complicated, and federated analysis of unstructured data types remains challenging. Advancement in federated data sharing should be accompanied by improvement in federated learning methodologies so that federated data sharing becomes functionally equivalent to direct access to record level data. In this article, we discuss federated data sharing approaches implemented by three data platforms in the ADRD field: Dementia's Platform UK (DPUK) in 2014, the Global Alzheimer's Association Interactive Network (GAAIN) in 2012, and the Alzheimer's Disease Data Initiative (ADDI) in 2020. We conclude by addressing open questions that the research community needs to solve together.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
寻求数据联合的方法,以加速阿尔茨海默病和相关痴呆症的研究:GAAIN、DPUK 和 ADDI。
数据共享加速科学发展已成为共识。数据共享提高了数据的实用性,促进了科学思想的创造和竞争。在阿尔茨海默病及相关痴呆症(ADRD)社区,数据类型和模式分散在许多组织、地域和管理结构中。阿尔茨海默病及相关痴呆症(ADRD)界并非唯一面临这些挑战的群体,然而,由于需要共享来自世界各地中心的复杂生物标记物数据,问题变得更加棘手。迄今为止,强硬的数据共享规定所取得的成效有限,而且经常遭到公然抵制。人们对使数据可查找、可访问、可互操作和可重复使用(FAIR)的兴趣往往导致集中式平台的出现。然而,当数据管理和主权结构不允许数据移动时,就必须采用其他方法,如联盟。实施完全联合的数据方法并非没有挑战。用户体验可能会变得更加复杂,对非结构化数据类型的联合分析仍然具有挑战性。在推进联合数据共享的同时,还应改进联合学习方法,使联合数据共享在功能上等同于直接访问记录级数据。在本文中,我们将讨论由 ADRD 领域的三个数据平台实施的联合数据共享方法:英国痴呆症平台(DPUK)(2014 年)、全球阿尔茨海默氏症协会互动网络(GAAIN)(2012 年)和阿尔茨海默氏症数据倡议(ADDI)(2020 年)。最后,我们探讨了研究界需要共同解决的开放性问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
期刊最新文献
A Systematic Review of Sleep Disturbance in Idiopathic Intracranial Hypertension. Advancing Patient Education in Idiopathic Intracranial Hypertension: The Promise of Large Language Models. Anti-Myelin-Associated Glycoprotein Neuropathy: Recent Developments. Approach to Managing the Initial Presentation of Multiple Sclerosis: A Worldwide Practice Survey. Association Between LACE+ Index Risk Category and 90-Day Mortality After Stroke.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1