AI Data Readiness Assessment This is intended as a self-assessment tool to evaluate your data across five dimensions: Data Silos and Accessibility Metadata and Documentation System Interoperability Governance and Stewardship Reusability and Compliance There are 15 assessment questions that should take approximately 3 minutes to complete.Answer each question for how it applies to your laboratory/organization as best as you can. At the end, you will receive your score and what to do with it. Data Silos and Accessibility Question Title * 1. Can researchers locate specific datasets from 6 months ago in under 30 seconds without asking a colleague? (Required.) Yes No Question Title * 2. Is data stored in a centralized repository (LIMS/ELN/Data Lakehouse) rather than on local instrument PCs or USB drives? (Required.) Yes No Question Title * 3. Does the system allow for automated data retrieval via APIs, or is manual export/import still required? (Required.) Yes No Metadata and Documentation Question Title * 4. Are globally unique persistent identifiers (PIDs) assigned to every new dataset automatically? (Required.) Yes No Question Title * 5. Do naming conventions follow a standardized lab-wide policy, or are they left to individual scientists' discretion? (Required.) Yes No Question Title * 6. Does every file include rich metadata (e.g., instrument model, method version, ambient temperature, and sample ID)? (Required.) Yes No System Interoperability Question Title * 7. Are instruments speaking the same language (e.g., converted from proprietary vendor formats to open standards like JSON, CSV, or ODT)? (Required.) Yes No Question Title * 8. Is there a business glossary/ontology in place to ensure terms like HCl and hydrochloric acid are recognized as the same entity across all systems? (Required.) Yes No Question Title * 9. Can your AI models pull data directly from your LIMS/ELN without 80% of the project time being spent on manual formatting? (Required.) Yes No Governance and Stewardship Question Title * 10. Has a Data Steward been formally assigned to oversee the quality and lifecycle of your scientific data domains? (Required.) Yes No Question Title * 11. Are there automated policies that mandate metadata creation at the point of data origination rather than retrospective cleanup? (Required.) Yes No Question Title * 12. Is there a clear authorization protocol defining who can access, edit, and share sensitive research data? (Required.) Yes No Reusability and Compliance Question Title * 13. Is every dataset accompanied by a standardized README detailing the provenance (origin and history) of the data? (Required.) Yes No Question Title * 14. Does your data remediation process maintain a GxP-validated audit trail for 21 CFR Part 11 or ISO 17025 integrity? (Required.) Yes No Question Title * 15. Can a collaborator or auditor verify your findings by accessing the raw data and the exact processing steps used? (Required.) Yes No Question Title * 16. Where should we send your results? (Required.) Question Title * 17. Please enter your information so we can personalize your results. (Required.) Get My Results