Implementation of the FAIR Data Principles for Exploratory Biomarker Data from Clinical Trials | Zendy

Alexander Arefolov | Zendy; Laura Adam | Zendy; Shoshana Brown | Zendy; Yelena Budovskaya | Zendy; Cong Chen | Zendy; Diya Das | Zendy; Chen Farhy | Zendy; Rebecca Ferguson | Zendy; Huang Hongmei | Zendy; Kimberly Kanigel Winner | Zendy; Christina Lu | Zendy; Oksana Polesskaya | Zendy; Tracy Staton | Zendy; Rajeev B. Tajhya | Zendy; Maryann Z. Whitley | Zendy; Jee-Yeon Wong | Zendy; Xiangpei Zeng | Zendy; Mark McCreary | Zendy

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Implementation of the FAIR Data Principles for Exploratory Biomarker Data from Clinical Trials

Author(s) -

Alexander Arefolov,

Laura Adam,

Shoshana Brown,

Yelena Budovskaya,

Cong Chen,

Diya Das,

Chen Farhy,

Rebecca Ferguson,

Huang Hongmei,

Kimberly Kanigel Winner,

Christina Lu,

Oksana Polesskaya,

Tracy Staton,

Rajeev B. Tajhya,

Maryann Z. Whitley,

Jee-Yeon Wong,

Xiangpei Zeng,

Mark McCreary

Publication year - 2021

Publication title -

data intelligence

Language(s) - English

Resource type - Journals

eISSN - 2096-7004

pISSN - 2641-435X

DOI - 10.1162/dint_a_00106

Subject(s) - data curation , interoperability , computer science , data science , data management , reuse , digital data , data quality , risk analysis (engineering) , data mining , world wide web , business , marketing , data transmission , engineering , computer network , metric (unit) , waste management

The FAIR data guiding principles have been recently developed and widely adopted to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets in the face of an exponential increase of data volume and complexity. The FAIR data principles have been formulated on a general level and the technological implementation of these principles remains up to the industries and organizations working on maximizing the value of their data. Here, we describe the data management and curation methodologies and best practices developed for FAIRification of clinical exploratory biomarker data collected from over 250 clinical studies. We discuss the data curation effort involved, the resulting output, and the business and scientific impact of our work. Finally, we propose prospective planning for FAIR data to optimize data management efforts and maximize data value.

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