Contents: Background | Introduction | Challenges | Journey | Why LabKey | Results | Conclusion
Background
The Alaska Department of Fish and Game’s Wildlife Health and Veterinary Services unit supports statewide monitoring of zoonotic and epizootic pathogens in wild animal populations. Their work spans disease surveillance, necropsy diagnostics, forensic analysis, and public health outreach. With more than 400,000 archived biological samples dating back to 1968, the team operates in a uniquely challenging context—remote field conditions, multi-decade sample tracking, and constantly shifting disease surveillance priorities.
Introduction
For years, the department managed its complex sample collection and testing data using fragmented tools: Excel spreadsheets, Access databases, and ad hoc processes that varied by disease, project, or sample type. The system was prone to errors, difficult to maintain, and poorly suited to evolving research and regulatory demands. Sample duplication, inconsistent metadata, and loss of traceability created major obstacles to efficient and reliable data use.
Challenges
The Wildlife Health and Veterinary Services team experienced these challenges with sample data management:
Disjointed data systems: Each disease or project had its own database, making long-term tracking, comparison, and retrieval cumbersome.
Complex sample lineage: Individual animals often have multiple IDs over their lifetime, and samples must be connected across repeated captures and various identifiers.
Inconsistent metadata: Sparse or missing metadata, especially for older samples, made it difficult to populate required fields or ensure data quality.
Limited internal testing: Most diagnostics are outsourced to external labs, requiring robust tracking of sample shipments, testing status, and returned data.
High sample diversity: Sample types range from blood and tissues to hair and environmental samples—each requiring different metadata fields and storage conditions.
User error and inconsistency: Data entry across time and staff introduced variability in labels, abbreviations, and interpretations that needed harmonization.
The Journey
Recognizing these challenges, the Wildlife Health and Veterinary Services Unit initiated a structured transition to Sample Manager:
Platform Selection and Planning: After identifying the limitations of their legacy systems and a previously attempted LIMS, the department selected LabKey Sample Manager for its flexibility and alignment with their use case.
Core Configuration and Data Entry: Initial efforts focused on structuring two core source types (animal and sampling event) and entering new samples from 2022 onward. This created a foundation for reliable sample tracking over time.
Workflow Development: They expanded usage to include picklists for shipments and job templates to manage sample movement and external testing. Custom data structures were designed to support sample lineage, maternal/fetal relationships, and environmental context.
Archive Integration and Scaling: Efforts are now underway to import and clean historical data using batch import and editing tools. Assay organization is also being refined to support multi-lab result comparisons and long-term data integration.
Why LabKey
LabKey Sample Manager stood out for its:
Flexibility: Adaptable source/sample model allowed the team to map real-world complexity (e.g., maternal-fetal relationships, environmental samples linked to multiple animals).
Customizability: Ability to define fields, sample types, and metadata capture around their actual workflows.
Powerful data model: Supports tracking sample lineage, related animals, repeated sampling events, and assay results over time.
Workflow tools: Features like picklists and jobs helped structure sample handling, especially for external testing.
Scalability: Ability to scale from current samples to historical archives with bulk import, validation, and batch editing tools.
Responsive support: Ongoing collaboration with LabKey staff to enhance functionality and troubleshoot as new needs emerge.
Results
Though still early in implementation, the department has already:
- Entered all samples from 2022 onward into Sample Manager.
- Developed a consistent metadata structure for animals and sampling events.
- Created workflows to manage outbound sample shipments and track returned results.
- Begun consolidating and de-duplicating legacy Excel and Access records.
- Reduced redundant testing through better visibility into sample and result history.
- Enhanced sample traceability, including detailed lineage tracking for serial and split samples.
Conclusion
The Alaska Department of Fish and Game has successfully tailored LabKey Sample Manager to a uniquely complex wildlife health use case. By mapping their nuanced biological data model into a flexible, centralized platform, they’ve gained improved traceability, reduced errors, and created a foundation for long-term data integration and analysis. As they continue onboarding historical data and assays, Sample Manager is poised to become the single source of truth for decades of wildlife health research in Alaska.
Hear first hand from the team at Alaska Department of Fish and Game how they’ve implemented Sample Manager for complex sample tracking.