Operationalizing and digitizing person-centered daily functioning: a case for functionomics.

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Esther R C Janssen, Ilona M Punt, Johan van Soest, Yvonne F Heerkens, Hillegonda A Stallinga, Huib Ten Napel, Lodewijk W van Rhijn, Barend Mons, Andre Dekker, Paul C Willems, Nico L U van Meeteren
{"title":"Operationalizing and digitizing person-centered daily functioning: a case for functionomics.","authors":"Esther R C Janssen, Ilona M Punt, Johan van Soest, Yvonne F Heerkens, Hillegonda A Stallinga, Huib Ten Napel, Lodewijk W van Rhijn, Barend Mons, Andre Dekker, Paul C Willems, Nico L U van Meeteren","doi":"10.1186/s12911-024-02584-2","DOIUrl":null,"url":null,"abstract":"<p><p>An ever-increasing amount of data on a person's daily functioning is being collected, which holds information to revolutionize person-centered healthcare. However, the full potential of data on daily functioning cannot yet be exploited as it is mostly stored in an unstructured and inaccessible manner. The integration of these data, and thereby expedited knowledge discovery, is possible by the introduction of functionomics as a complementary 'omics' initiative, embracing the advances in data science. Functionomics is the study of high-throughput data on a person's daily functioning, that can be operationalized with the International Classification of Functioning, Disability and Health (ICF).A prerequisite for making functionomics operational are the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This paper illustrates a step by step application of the FAIR principles for making functionomics data machine readable and accessible, under strictly certified conditions, in a practical example. Establishing more FAIR functionomics data repositories, analyzed using a federated data infrastructure, enables new knowledge generation to improve health and person-centered healthcare. Together, as one allied health and healthcare research community, we need to consider to take up the here proposed methods.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11212415/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12911-024-02584-2","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

An ever-increasing amount of data on a person's daily functioning is being collected, which holds information to revolutionize person-centered healthcare. However, the full potential of data on daily functioning cannot yet be exploited as it is mostly stored in an unstructured and inaccessible manner. The integration of these data, and thereby expedited knowledge discovery, is possible by the introduction of functionomics as a complementary 'omics' initiative, embracing the advances in data science. Functionomics is the study of high-throughput data on a person's daily functioning, that can be operationalized with the International Classification of Functioning, Disability and Health (ICF).A prerequisite for making functionomics operational are the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This paper illustrates a step by step application of the FAIR principles for making functionomics data machine readable and accessible, under strictly certified conditions, in a practical example. Establishing more FAIR functionomics data repositories, analyzed using a federated data infrastructure, enables new knowledge generation to improve health and person-centered healthcare. Together, as one allied health and healthcare research community, we need to consider to take up the here proposed methods.

以人为本的日常功能操作化和数字化:功能组学案例。
目前正在收集越来越多有关个人日常功能的数据,其中蕴含的信息将彻底改变以人为本的医疗保健。然而,由于日常功能数据大多以非结构化和不可访问的方式存储,其潜力尚未得到充分挖掘。功能组学作为 "全息 "计划的补充,结合数据科学的进步,可以整合这些数据,从而加快知识的发现。功能组学是对有关个人日常功能的高通量数据的研究,可通过《国际功能、残疾和健康分类》(ICF)进行操作。本文举例说明了在严格认证的条件下,如何逐步应用 FAIR 原则,使功能组学数据具有机器可读性和可访问性。建立更多的 FAIR 功能组学数据存储库,并利用联合数据基础设施进行分析,能够产生新的知识,从而改善健康状况和以人为本的医疗保健。作为一个联合健康和医疗保健研究团体,我们需要共同考虑采用这里提出的方法。
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 求助全文
来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信