Life-Cycle Decisions for Biomedical Data: The Challenge of Forecasting Costs

National Academies of Sciences, Engineering, and Medicine

doi:10.17226/25639

Life-Cycle Decisions for Biomedical Data:The Challenge of Forecasting Costs (2020)

Consensus Study Report

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Life-Cycle Decisions for Biomedical Data

The Challenge of Forecasting Costs(2020)

Consensus Study Report

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Overview

Contributors

National Academies of Sciences, Engineering, and Medicine; Division on Engineering and Physical Sciences; Division on Earth and Life Studies; Policy and Global Affairs; Board on Mathematical Sciences and Analytics; Committee on Applied and Theoretical Statistics; Computer Science and Telecommunications Board; Board on Life Sciences; Board on Research Data and Information; Committee on Forecasting Costs for Preserving and Promoting Access to Biomedical Data

Description

Biomedical research results in the collection and storage of increasingly large and complex data sets. Preserving those data so that they are discoverable, accessible, and interpretable accelerates scientific discovery and improves health outcomes, but requires that researchers, data curators, and data archivists consider the long-term disposition of data and the costs of preserving, archiving, and promoting access to them.

Life Cycle Decisions for Biomedical Data examines and assesses approaches and considerations for forecasting costs for preserving, archiving, and promoting access to biomedical research data. This report provides a comprehensive conceptual framework for cost-effective decision making that encourages data accessibility and reuse for researchers, data managers, data archivists, data scientists, and institutions that support platforms that enable biomedical research data preservation, discoverability, and use.

Topics

Suggested Citation

National Academies of Sciences, Engineering, and Medicine. 2020. Life-Cycle Decisions for Biomedical Data: The Challenge of Forecasting Costs. Washington, DC: The National Academies Press.https://doi.org/10.17226/25639.

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Publication Info

184 pages |8.5 x 11
ISBNs:

Paperback: 978-0-309-67003-6
Ebook: 978-0-309-67006-7

DOI: https://doi.org/10.17226/25639

RESOURCES AT A GLANCE

Video(s):
Public Briefing Video
How-To Guide: Cost Driver Template for Biomedical Data

More Info

Contents

Table of Contents	skim chapter
Front Matter	i-xiv
Summary	1-9
1 Introduction	10-23
2 Framework Foundation: Data States and Associated Activities	24-32
3 Cost and the Value of Data	33-43
4 The Cost-Forecasting Framework: Identifying Cost Drivers in the Biomedical Data Life Cycle	44-77
5 Applying the Framework to a New State 2 Data Resource	78-96
6 Applying the Framework to a New Data Set	97-108
7 Potential Disruptors to Forecasting Costs	109-118
8 Fostering the Data Management Environment	119-126
Appendixes	127-128
Appendix A: Meetings and Presentations	129-136
Appendix B: Active Data Management Plans as a Planning Tool	137-139
Appendix C: Identifying Salary Ranges for Jobs Relevant to the Data Life Cycle	140-147
Appendix D: Soft Costs for Digital Preservation	148-150
Appendix E: Template to Map Cost Drivers to Data Resource Properties	151-155
Appendix F: Comparison of the Contents Across the Three Data States	156-160
Appendix G: Committee Biographical Information	161-166
Appendix H: Acronyms	167-170

Resources

Links

Public Briefing Slides
Slides from the public briefing, highlighting the key messages from the report.
Cost Drivers Workbook
This workbook aims to help stakeholders identify cost drivers for preserving and promoting access to biomedical data for their specific needs.
Webinar Slides: Forecasting Data Costs for Researchers
Slides from the webinar on Forecasting Data Costs for Researchers, highlighting key takeaways for those in the primary research and data management environment.
Webinar Slides: Forecasting Data Costs for Funders
Slides from the webinar on Forecasting Data Costs for Funders, highlighting key takeaways for those who fund biomedical research.
Webinar Slides: Forecasting Data Costs for Storage Providers
Slides from the webinar on Forecasting Data Costs for Storage Providers, highlighting key takeaways for repositories, repository planners, and program managers.
Webinar Video: Forecasting Data Costs for Researchers
Invited speakers discuss how researchers can plan for the life cycle of their data and how to create an environment conducive to cost forecasting of sustainable data management.
Webinar Video: Forecasting Data Costs for Funders
Invited speakers address how research funders can encourage and foster sustainable data management practices.
Webinar Video: Forecasting Data Costs for Storage Providers
Invited speakers discuss how scientific data repositories and program managers can help make data more discoverable, aid in the development and adoption of data and metadata standardization and best practices, and help users better understand their storage options.
User Guide: Forecasting Data Costs for Biomedical Researchers
This guide will help researchers identify and think through the major decisions in forecasting life cycle costs for preserving, archiving, and promoting access to biomedical data.
User Guide: Forecasting Data Costs for Funding Organizations
This guide will help funding organizations identify and consider the major decisions and recommendations for forecasting life cycle costs for preserving, archiving, and promoting access to biomedical data.
User Guide: Forecasting Data Costs for Storage Providers
This guide will help data storage entities identify and consider the major decisions and recommendations for forecasting life cycle costs for preserving, archiving, and promoting access to biomedical data.
Checklist for Administrators at Research Institutions
This checklist will help administrators of research institutions promote data management practices and implement cost forecasting for data preservation and access.

Videos

Public Briefing Video

Members of the committee discuss the key findings and conceptual framework presented in the report.

How-To Guide: Cost Driver Template for Biomedical Data

Dr. Maryann Martone walks a user through the cost driver template for forecasting the costs associated with a biomedical information resource.

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