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.

Contents

• The National Academies of SCIENCES • ENGINEERING • MEDICINE
• COMMITTEE ON FORECASTING COSTS FOR PRESERVING AND PROMOTING ACCESS TO BIOMEDICAL DATA
• 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
• Acknowledgment of Reviewers
• Summary
  • THE STUDY CHARGE
  • THE COST-FORECASTING FRAMEWORK
  • CREATING AN ENVIRONMENT CONDUCIVE TO COST FORECASTING OF SUSTAINABLE DATA MANAGEMENT
  • POTENTIAL DISRUPTORS
  • ENSURING LONG-TERM STEWARDSHIP
  • REFERENCE
• 1. Introduction
  • THE CHARGE TO THE NATIONAL ACADEMIES AND THE STUDY COMMITTEE
  • COMMITTEE INFORMATION GATHERING AND APPROACH TO ITS TASK
  • FEDERAL CONTEXT
  • BIOMEDICAL DATA LANDSCAPE
  • FAIR DATA
  • REPORT ORGANIZATION
  • BENEFICIARIES OF THIS REPORT
  • REFERENCES
• 2. Framework Foundation: Data States and Associated Activities
  • STATE 1: THE PRIMARY RESEARCH AND DATA MANAGEMENT ENVIRONMENT
  • STATE 2: THE ACTIVE REPOSITORY AND PLATFORM
  • STATE 3: THE LONG-TERM PRESERVATION PLATFORM
  • PERSONNEL AND THEIR RELATIVE SALARY LEVELS
  • REFERENCES
• 3. Cost and the Value of Data
  • ECONOMIC ISSUES IN FORECASTING COSTS
  • ASSESSING THE VALUE OF DATA
  • APPROACHES TO DATA VALUATION
  • REFERENCES
• 4. The Cost-Forecasting Framework: Identifying Cost Drivers in the Biomedical Data Life Cycle
  • CONSULTING WIDELY TO CONDUCT A COST FORECAST
  • MAPPING COST DRIVERS TO ACTIVITIES IN EACH DATA STATE
  • INDIVIDUAL COST DRIVERS IN THE DEVELOPMENT AND OPERATION OF A BIOMEDICAL INFORMATION RESOURCE
  • ATTACHING DOLLARS TO THE COST FORECAST
  • INFRASTRUCTURAL ELEMENTS NOT CONSIDERED IN THE COST MODEL
  • REFERENCES
• 5. Applying the Framework to a New State 2 Data Resource
  • USE CASE 1: ESTIMATING COSTS ASSOCIATED WITH SETTING UP A NEW DATA REPOSITORY FOR THE U.S. BRAIN INITIATIVE
  • REFERENCES
• 6. Applying the Framework to a New Data Set
  • USE CASE 2: ESTIMATING COSTS ASSOCIATED WITH A PRIMARY RESEARCH DATA SET
  • REFERENCE
• 7. Potential Disruptors to Forecasting Costs
  • BIOMEDICAL DATA VOLUME AND VARIETY
  • ADVANCES IN MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE
  • DEVELOPMENTS WITH POTENTIAL COST SAVINGS
  • WORKFORCE-DEVELOPMENT CHALLENGES
  • LEGAL AND POLICY DISRUPTORS
  • CHANGING UNDERSTANDING OF HUMAN-SUBJECTS POLICY
  • OTHER POTENTIAL DISRUPTORS
  • REFERENCES
• 8. Fostering the Data Management Environment
  • STRATEGIES
  • ACTIONS
  • ADVANCES FOR PRACTICE
  • FACTORS FOR SUCCESSFUL ADOPTION OF DATA-FORECASTING APPROACHES
  • REFERENCES
• Appendixes
  • A. Meetings and Presentations
  • B. Active Data Management Plans as a Planning Tool
  • C. Identifying Salary Ranges for Jobs Relevant to the Data Life Cycle
  • D. Soft Costs for Digital Preservation
  • E. Template to Map Cost Drivers to Data Resource Properties
  • F. Comparison of the Contents Across the Three Data States
  • G. Committee Biographical Information
  • H. Acronyms

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.

Digital Object Identifier: https://doi.org/10.17226/25639

Additional copies of this publication are available from the National Academies Press, 500 Fifth Street, NW, Keck 360, Washington, DC 20001; (800) 624-6242 or (202) 334-3313; http://www.nap.edu.

Printed in the United States of America