Life-Cycle Decisions for Biomedical Data

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.Table of ContentsFront MatterSummary1 Introduction2 Framework Foundation: Data States and Associated Activities3 Cost and the Value of Data4 The Cost-Forecasting Framework: Identifying Cost Drivers in the Biomedical Data Life Cycle5 Applying the Framework to a New State 2 Data Resource6 Applying the Framework to a New Data Set7 Potential Disruptors to Forecasting Costs8 Fostering the Data Management EnvironmentAppendixesAppendix A: Meetings and PresentationsAppendix B: Active Data Management Plans as a Planning ToolAppendix C: Identifying Salary Ranges for Jobs Relevant to the Data Life CycleAppendix D: Soft Costs for Digital PreservationAppendix E: Template to Map Cost Drivers to Data Resource PropertiesAppendix F: Comparison of the Contents Across the Three Data StatesAppendix G: Committee Biographical InformationAppendix H: Acronyms