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

Consensus

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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.

Additional materials

Public Briefing Slides
Cost Drivers Workbook
Webinar Slides: Forecasting Data Costs for Researchers
Webinar Slides: Forecasting Data Costs for Funders
Webinar Slides: Forecasting Data Costs for Storage Providers
Webinar Video: Forecasting Data Costs for Researchers
Webinar Video: Forecasting Data Costs for Funders
Webinar Video: Forecasting Data Costs for Storage Providers
User Guide: Forecasting Data Costs for Biomedical Researchers
User Guide: Forecasting Data Costs for Funding Organizations
User Guide: Forecasting Data Costs for Storage Providers
Checklist for Administrators at Research Institutions

Publication information

184 pages · 8.5 x 11 · paperback
ISBN Paperback: 0-309-67003-9
ISBN Ebook: 0-309-67004-7
DOI: https://doi.org/10.17226/25639

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.

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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

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

Chapter: Appendix C: Identifying Salary Ranges for Jobs Relevant to the Data Life Cycle

Additional materials

Publication information

Suggested citation

My Academies

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

Chapter: Appendix C: Identifying Salary Ranges for Jobs Relevant to the Data Life Cycle