Use Case: Digitizing Invertebrate Collections at the American Museum of Natural History

Institution: Division of Invertebrate Zoology, American Museum of Natural History

Interviewee: Christine Johnson

Collection Size: ~23 million specimens

Link to the Invertebrate Collections at AMNH

Link to the Webinar by IDIGBIO featuring work at AMNH on October 15, 2025

GIGAmacro Magnify2 setup at AMNH for batch digitizing specimen and label information. Screenshot from IDIGBIO webinar on October 15, 2025. Link to the Webinar by IDIGBIO featuring work at AMNH on October 15, 2025

 

Background

The American Museum of Natural History (AMNH) in New York City houses one of the largest and most diverse invertebrate zoology collections in the world. With an estimated 23 million specimens—ranging from pinned insects to marine invertebrates preserved in ethanol—the Division of Invertebrate Zoology supports global research in biodiversity, ecology, and conservation.

For years, researchers sought efficient ways to digitize these massive collections, making specimen data and imagery accessible to scientists worldwide. Manual photography was slow, inconsistent, and labor-intensive. In 2015, AMNH staff first encountered the GIGAmacro imaging system in an early demonstration and recognized its potential to accelerate high-resolution specimen digitization. After several years and the successful acquisition of funding, Christine Johnson, Curatorial Associate at AMNH, led the initiative to bring the GIGAmacro Magnify² system into the museum’s digitization workflow.

 

Challenge

The division faced several major hurdles:

  • Scale of collection: With millions of specimens, traditional one-by-one imaging approaches were unfeasible.
  • Variety of materials: Collections included both dry and wet (ethanol-preserved) specimens requiring flexible imaging setups.
  • Label documentation: Each pinned specimen often carries multiple small labels containing critical data—difficult to image and read efficiently.
  • Speed and data management: Grant deliverables required imaging tens of thousands of specimens, yet previous processes were too slow to meet targets.
  • Data extraction: Turning specimen labels into structured digital records remained a bottleneck, even once images were captured.

 

Solution

The AMNH team integrated the GIGAmacro Magnify² robotic imaging system into a streamlined, semi-automated digitization workflow designed for both pinned and wet specimens. Johnson and her team developed custom grids and mounting templates to photograph batches of specimens simultaneously—greatly increasing throughput while maintaining quality.

 

GIGAmacro Magnify2 setup at AMNH for batch digitizing wet specimens and label information. Screenshot from IDIGBIO webinar on October 15, 2025. Link to the Webinar by IDIGBIO featuring work at AMNH on October 15, 2025

 

Key Workflow Innovations

  • Grid-Based Batch Imaging:

    Specimens are pinned or placed into a foam or yoga-mat substrate arranged in a grid (32–56 cells). Each cell includes the specimen, barcode, and labels, enabling systematic imaging of dozens at once.

  • Dual Use for Wet and Dry Specimens:

    Custom wells hold ethanol vials in place, allowing imaging of marine invertebrates without removing them from storage containers.

  • Automated Stacking and Stitching:

    The Magnify² captures multiple focus layers per specimen, producing high-resolution, fully in-focus images with both specimen and labels legible.

  • Integrated Post-Processing:

    Once images are captured, they are automatically processed through stacking software and renamed via barcode-based automation. The resulting datasets are uploaded directly to the AMNH collection database.

  • AI-Assisted Label Transcription:

    Using accessible tools such as ChatGPT and Google Gemini, the team implemented optical text extraction from specimen labels, feeding data into the museum’s database for faster catalog creation and geolocation mapping.

    Preparation of specimens in a batch template created by AMNH. Screenshot from IDIGBIO webinar on October 15, 2025. Link to the Webinar by IDIGBIO featuring work at AMNH on October 15, 2025

 

Results and Impact

The implementation of the GIGAmacro Magnify² system has transformed AMNH’s digitization capacity and data accessibility:

  • 5–6× faster throughput compared to manual imaging.
  • Over 27,000 bee specimens digitized, with a target of 40,000 for current grant deliverables.
  • Integrated AI workflows now extract label data automatically, dramatically reducing transcription time.
  • Improved specimen safety — batch imaging reduces physical handling and risk of damage.
  • Data accessibility — all imaged specimens are uploaded to AMNH’s public database, enabling global research access and biodiversity analysis.
  • Cross-disciplinary applications — the images are being used for time-series studies comparing historical and modern distributions, supporting ecological and climate research.

Johnson also notes that the Magnify² enables holistic, information-rich imagery, capturing both specimen and labels in a single high-resolution frame. This comprehensive documentation simplifies cataloging, data verification, and sharing across institutions.

Example image after focal stacking. Screenshot from IDIGBIO webinar on October 15, 2025. Link to the Webinar by IDIGBIO featuring work at AMNH on October 15, 2025

 

Customer Quotes

“We’re at least five times faster than when we did it one by one. It’s also safer for the specimens because we’re not constantly repositioning them under a camera.”

— Christine Johnson, Curatorial Associate, AMNH

“It’s great to have one image that includes everything—the specimen, barcode, and labels—all in focus and high resolution.”

— Christine Johnson, AMNH

“We’re now using AI to read the labels, and it’s working really, really well. What used to take days can now be done in minutes.”

— Christine Johnson, AMNH

 

Looking Ahead

AMNH continues to refine and expand its use of the GIGAmacro Magnify² platform. Future goals include:

  • Integrating automated stacking and file-renaming pipelines directly into GIGAmacro software.
  • Exploring AI-based workflow customization for even faster post-processing.
  • Considering additional systems to support simultaneous imaging setups for different specimen types.
  • Sharing digitization methods with other museums through webinars and publications, such as Johnson’s presentation for iDigBio’s Digitization Series (October 2025). Link to the Webinar by IDIGBIO featuring work at AMNH on October 15, 2025

The result is a compelling example of how advanced imaging robotics and open software tools can modernize natural history digitization—making vast scientific collections more accessible, searchable, and meaningful for researchers worldwide.

 

The Team at GIGAmacro

We’re thrilled that Magnify² plays a part in AMNH’s effort to digitize millions of invertebrates. From grid-based batch imaging to automated stacking and renaming, our focus is making high-quality capture fast, repeatable, and compatible with standard data pipelines—so more scientists can use these collections to answer big questions.