Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Developing a standardized but extendable framework to increase the findability of infectious disease datasets
by
Yeaman, Michael R.
, Su, Andrew I.
, Tsueng, Ginger
, Cano, Marco A. Alvarado
, Shabman, Reed S.
, Kang, Mengjia
, Starren, Justin
, Wu, Qinglong
, Zhou, Xinghua
, Brown, Liliana
, Wu, Chunlei
, Xin, Jiwen
, Czech, Candice
, Pache, Lars
, Rasmussen, Luke V.
, Savidge, Tor C.
, Bento, José
, Hughes, Laura D.
in
631/114/2402
/ 631/114/2416
/ Communicable Diseases
/ Computer applications
/ Consortia
/ Datasets
/ Datasets as Topic - standards
/ Humanities and Social Sciences
/ Humans
/ Infectious diseases
/ Metadata
/ multidisciplinary
/ Reproducibility of Results
/ Science
/ Science (multidisciplinary)
2023
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Developing a standardized but extendable framework to increase the findability of infectious disease datasets
by
Yeaman, Michael R.
, Su, Andrew I.
, Tsueng, Ginger
, Cano, Marco A. Alvarado
, Shabman, Reed S.
, Kang, Mengjia
, Starren, Justin
, Wu, Qinglong
, Zhou, Xinghua
, Brown, Liliana
, Wu, Chunlei
, Xin, Jiwen
, Czech, Candice
, Pache, Lars
, Rasmussen, Luke V.
, Savidge, Tor C.
, Bento, José
, Hughes, Laura D.
in
631/114/2402
/ 631/114/2416
/ Communicable Diseases
/ Computer applications
/ Consortia
/ Datasets
/ Datasets as Topic - standards
/ Humanities and Social Sciences
/ Humans
/ Infectious diseases
/ Metadata
/ multidisciplinary
/ Reproducibility of Results
/ Science
/ Science (multidisciplinary)
2023
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Developing a standardized but extendable framework to increase the findability of infectious disease datasets
by
Yeaman, Michael R.
, Su, Andrew I.
, Tsueng, Ginger
, Cano, Marco A. Alvarado
, Shabman, Reed S.
, Kang, Mengjia
, Starren, Justin
, Wu, Qinglong
, Zhou, Xinghua
, Brown, Liliana
, Wu, Chunlei
, Xin, Jiwen
, Czech, Candice
, Pache, Lars
, Rasmussen, Luke V.
, Savidge, Tor C.
, Bento, José
, Hughes, Laura D.
in
631/114/2402
/ 631/114/2416
/ Communicable Diseases
/ Computer applications
/ Consortia
/ Datasets
/ Datasets as Topic - standards
/ Humanities and Social Sciences
/ Humans
/ Infectious diseases
/ Metadata
/ multidisciplinary
/ Reproducibility of Results
/ Science
/ Science (multidisciplinary)
2023
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Developing a standardized but extendable framework to increase the findability of infectious disease datasets
Journal Article
Developing a standardized but extendable framework to increase the findability of infectious disease datasets
2023
Request Book From Autostore
and Choose the Collection Method
Overview
Biomedical datasets are increasing in size, stored in many repositories, and face challenges in FAIRness (findability, accessibility, interoperability, reusability). As a Consortium of infectious disease researchers from 15 Centers, we aim to adopt open science practices to promote transparency, encourage reproducibility, and accelerate research advances through data reuse. To improve FAIRness of our datasets and computational tools, we evaluated metadata standards across established biomedical data repositories. The vast majority do not adhere to a single standard, such as Schema.org, which is widely-adopted by generalist repositories. Consequently, datasets in these repositories are not findable in aggregation projects like Google Dataset Search. We alleviated this gap by creating a reusable metadata schema based on Schema.org and catalogued nearly 400 datasets and computational tools we collected. The approach is easily reusable to create schemas interoperable with community standards, but customized to a particular context. Our approach enabled data discovery, increased the reusability of datasets from a large research consortium, and accelerated research. Lastly, we discuss ongoing challenges with FAIRness beyond discoverability.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
This website uses cookies to ensure you get the best experience on our website.