New Tools for Digital Lab Notebook Creation for use in Reflection Transformation Imaging

Mark Mudge, Carla Schroer


Scientific digital documentation of cultural heritage and natural science subjects can be a powerful tool for e-science and citizen scholarship. For centuries, the scientific method has required the recording of all empirical data’s collection contexts and processes in a lab notebook, which provides informational transparency and enables informed reuse.

This talk will introduce two metadata and knowledge management software tools called Digital Lab Notebook:Capture Context (DLN:CC) and Digital Lab Notebook: Inspector (DLN:Inspector), These packages take the form of user-friendly toolkits that record the contexts in which the original photographic sets of empirical information were acquired and inspect these photographic datasets for successful processing.

This methodology is designed for digital representations that are built with computational photography technologies. While this software’s first iteration is optimized for the computational photography technique Reflectance Transformation Imaging (RTI), the software is designed for easy adaptation to other computational photography technologies. The near-automatic nature of computational photography has advantages for the creation of scientific digital surrogates. A digital surrogate is a “stand-in” for “real world” subjects. They can be used for subsequent scientific or scholarly research.

Here’s how it works. First, the DLN:CC harvests the capture context and process metadata associated with the empirical data and automatically maps this metadata to the CIDOC/CRMdig ontology. Next the processed photosets are inspected by DLN:Inspector to see if they will or will not successfully generate an RTI digital surrogate. When successful, the metadata is sent to the DLN. The metadata information in the DLN is then published as both XML and Research Description Framework (RDF) Linked Open Data files.

These DLN tools enable future evaluation of surrogate reliability and aids long-term archiving. When applied across the field of computational photography, the results of this strategic approach will be to enhance the digital data and knowledge sustainability of humankind’s legacy.