Digitization Workshop ASIH 2016
Statement of Purpose
These links and documents contain information about digitizing natural history collections and their associated data.
Introduction to Digitization
In the context of the SPNHC wiki ‘digitize’ means converting ALL analog data to digital data according to standard vocabularies such as DarwinCore and AudubonCore. That is, we start with the concept of a specimen that has been accessioned in a collection. We envision these digital data eventually to include the entirety of analog data that are associated with a particular specimen. This may include but is not limited to: textual data from labels and ledgers associated with specimens, images of specimens, DNA and other ‘omics, field notes, tomographic imaging data, specimen history (including preservation), and specimen-associated literature. Digitizing might be accomplished by collections managers, technicians, contractors, and other entities, the results of which are included within the institution’s collection management system. In many instances these data may be generated off site by investigators.
Content generated during The American Society of Ichthyologists and Herpetologists (ASIH) Annual Joint Meeting - 2016, during an iDigBio sponsored workshop by the following individuals participating in the "Digitization" working group of the aforementioned workshop: : Gil Nelson (Florida State University, Courtesy Faculty), Larry Page (The Florida Museum of Natural History, Ichthyology Curator), Cristina Cox-Fernandes (UMass Amherst Biology, Adjunct Research Associate Professor), Mark Sabaj (ANSP, Ichthyology Collection Manager), Adam Summers (University of Washington, Professor - Friday Harbor Labs), Kevin Love (iDigBio, IT Expert), Ken Thompson (Lock Haven University, Professor; Retired), Randy Singer (Florida Museum of Natural History), and Gregory Watkins-Colwell (Yale Peabody Museum, Herps and Fishes, Collection Manager).
- Databasing Overview from Digitization Workshop ASIH 2016
- Data Aggregation Overview from Digitization Workshop ASIH 2016
iDigBio’s workflows for digitization
iDigBio, the U.S. National Science Foundation’s national resource for facilitating and enabling collections digitization throughout the United States has developed several sets of digitization workflows (including transcription and imaging) for various disciplines and preparation types, including fluid-preserved specimens. These workflows are the product of several working groups and workshops and are publically available at: https://www.idigbio.org/content/workflow-modules-and-task-lists#spirits
Drafts of revisions of workflows for making digital photographs of specimens:
Six task clusters of digitization
Foundation for above workflows
1. Predigitization Curation
- locating specimens
- checking determinations (nomenclature) and other information in database
- Insert institutionally and/or globally unique identifiers for specimens.
- transferring specimens to work station
2. Data Entry
- Transcribing label data into an electronic database.
3. Imaging and other media
- Recording digital representations
- 2D photographs
- 3D tomographic images such as CT, MRI and PET scanning
- audio recordings
- video recordings
4. Image processing
- Specialized Georeferencing Tools: https://www.idigbio.org/wiki/index.php/Georeferencing#Specialized_Georeferencing_Tools
- iDigBio Georeferencing Working Group-Georeferencing Community Protocols and Workflows: https://www.idigbio.org/wiki/index.php/Georeferencing#Georeferencing_Community_Protocols_and_Workflows
- Georeferencing Quick Reference Guide: http://manisnet.org/GeoreferencingQuickReferenceGuide.pdf
- A guide to the best practices for georeferencing biological species written by the BioGeomancer Consortium: http://www.gbif.org/resource/80536
6. Data mobilization
By data mobilization we mean contributing your data and media to a designated aggregator (e.g. iDigBio, GBIF, VertNet) via a protocol similar to GBIF’s Integrated Publishing Toolkit. These data are then integrated with data from many institutions to ensure research and other access to more complete datasets. Examples include:
Adam Summers workflow for CT scanning
Bullet list of how I get many specimens scanned at the same time: https://docs.google.com/document/d/1mMvCIee4uIVqaDEgc6vSsljRdx60wTwNECAIvwWdHFs/edit
Adam’s example of a lot of data associated with specimens: https://osf.io/ecmz4/wiki/Fishes/