Related Grant: “Applying Scientific Rigor to Photogrammetric 3D Documentation for Cultural Heritage and Natural Science Materials”

In collaboration with several partner consultants and technical advisors, CHI was awarded a grant from the National Center for Preservation Technology and Training (NCPTT) that will produce advanced metadata and knowledge management tools to record a “Digital Lab Notebook” (DLN), describing the means and context of 3D photogrammetric data capture. More…

White Paper: “Data Sustainability and Advanced Metadata Management for Scientific Imaging”

At the conclusion of this NEH Start-up grant, CHI produced a white paper describing the outcome of the project: a user-friendly software toolkit that greatly simplifies methods of building a Digital Lab Notebook (DLN), an essential component of digital scientific imaging. Read the paper.

Video Lightning Talk About This Grant

Watch this brief video of a talk about this grant by Carla Schroer, founder and director at CHI, presented at the National Endowment for the Humanities' Office of Digital Humanities in September 2014. You can also view all the talks from this session.

NEH Grants Announcement

On March 27, 2014, the National Endowment for the Humanities announced $18.2 million in grants to 208 humanities projects, including this grant to CHI. See the NEH press release. The specific grant to CHI is described in the NEH list of Digital Humanities Start-up Grants.

What Is the Digital Lab Notebook?

Learn more about the digital lab notebook. Like a scientist's written account before the digital age, it records the means and circumstances of the capture of digital information from a “real world” subject, tracking all the events associated with the processing of this information into a digital representation. More…

Related Publications

See these CHI publications for more information pertaining to the digital lab notebook.


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Digital Humanities Start-up Grant

Data Sustainability and Advanced Metadata Management for Scientific Imaging

Contents:  Impact and Products  Project Partners  Software Details  

Flow of data through the RTI tool chain from capture to results

Process flow chart for RTI showing the flow of data—images and metadata—(in yellow) through the tool chain (in blue) from photographic capture to finished results

This project was completed December 31, 2015.

The National Endowment for the Humanities (NEH) awarded a Digital Humanities Start-up Grant of $60,000 to Cultural Heritage Imaging (CHI) that began on May 1, 2014.

This pilot project was to evaluate the usability and desirability for subsequent adoption of a new metadata and knowledge management methodology. The project envisioned a “digital lab notebook” that takes the form of a user-friendly toolkit to document not only the algorithmic transformation of photographic data, but also the context in which the photographs were created.

This methodology is designed for digital representations that are built with computational photography technologies and intended for use in interdisciplinary science and humanities scholarship. The near-automatic nature of computational photography has advantages for the creation of digital representations for science and scholarship. These advantages, in combination with this project’s new metadata and knowledge management methodology, offer greatly enhanced digital data and knowledge sustainability. Together they encourage reuse of digital representations, allow users of the data to understand how they were made, which enables evaluation of reliability, and prepare digital representation data for long-term archiving. When applied across the field of computational photography, the results of this approach enhance the digital knowledge sustainability of humankind’s legacy.

Impact and Products

This project included software design and development, analysis of the workflow and usage patterns of imaging practitioners, and an opportunity to present the newly developed tools and get feedback from the project partners.

The project introduced greatly simplified methods for building a Digital Lab Notebook (DLN), which is an essential component of digital scientific imaging. The DLN takes the form of a user-friendly toolkit, comprising two software modules, DLN:Capture Context and DLN:Inspector. The software is designed to document not only the algorithmic transformation of photographic data, but also the context in which the photographs were created. The resulting organized data and metadata are necessary to evaluate a digital surrogate’s quality and reliability.

The DLN:Inspector tool was designed and built from the ground up. The DLN:Capture Context tool was refined, and features were added and tested. Overall, the project was a success, and the two new and valuable tools will be made available as open source software later in 2016. (Learn more about the software below).

Project Partners

The project was carried out in two case studies with groups that work with these computational photography technologies: Reflectance Transformation Imaging (RTI) and Structure from Motion photogrammetry. Over the course of the project, the case study leads and consultants produced recommendations, including software revisions for enhanced usability and the improved robustness of the archival submission tool.

Dale Kronkright, Georgia O'Keeffe Museum: Case Study Lead

Photo of Dale KronkrightDale is Head of Conservation at the Georgia O’Keeffe Museum. He holds numerous advanced certificates in scientific analytical methods and has received a number of national and state preservation awards. Regarding this project, Dale says:

“CHI is at the heart of building the critical mass needed to engage the public with humanities themes using rich, interactive and relevant imaged-based, digital platforms. I find it hard to imagine another digital technology effort that can better help small museums, archives and historic sites advance their 3D-imaged based preservation strategies more reliably than CHI’s proposal for this [project].”


Adam Rabinowitz, Institute of Classical Archaeology at University of Texas, Austin: Case Study Lead

Photo of Adam RabinowitzAdam is Assistant Professor of Classics and Assistant Director of the Institute of Classical Archaeology at the University of Texas at Austin. He has more than 20 years of archaeological field experience at Greek, Roman, and Byzantine sites in Italy, England, Israel, Tunisia, and Ukraine. Adam sums up his support for this project:

“CHI’s work has had a major influence on my thinking about the archival preservation of photographic data, and I am eager to work with them....Computational photography is the one field I have encountered in a 25-year-long career in archaeology in which the primary data captured in the field actually have the potential to become richer and more informative over time…. I know that the project will help us not only to preserve our existing data for future reuse, but to prepare for the increasing role that computational photography will play in our subsequent projects.”

Key Contributors

Martin Doerr, Knowledge Representation Consultant

Since 1990 Martin has been Research Director at the Foundation of Research and Technology – Hellas (FORTH). He is head of the Centre for Cultural Informatics, an activity of the Information Systems Lab of FORTH-ICS. He has been leading the development of systems for knowledge representation and terminology, metadata, and content management.

Erich Leisch, Software Engineer Consultant

Erich is a senior software engineer with FORTH. His professional interests include data modeling and structuring in database design and message specification.

Ronald Bourret, Software Engineer Consultant

Ron is a software consultant, writer, and researcher who has written code in areas as diverse as query engines, scheduling algorithms, XML parsers, and graphics.

Judy Bogart, Senior Technical Writer Consultant

Judy is a senior technical writer and editor who has worked in the software industry for over 30 years, currently with consulting company Expert Support Inc.

Software Details

Digital provenance information, essential for science and scholarship, is a record of the means and circumstances of digital information capture from a “real world” subject and tracks all the events that happen during the processing of this information into a completed digital representation. Such information is absolutely crucial for current and future reuse of both the original data and the advanced digital representations derived from them. The absence of such contextual knowledge critically threatens the value of digital representations for scholarly and scientific purposes.

The project’s two software modules, DLN:Capture Context and DLN:Inspector, are based on the latest documentary science and are designed to make the collection of data and metadata in computational photography nearly automatic and easy for users.

DLN:Capture Context simplifies user management of the large volume of metadata through a user-friendly interface. This interface expedites user metadata input with a template process. For example, following a one-time entry of the user’s photo equipment and associated metadata, the user creates templates and saves commonly used equipment configurations. At the time of the capture session, these templates can be selected with a mouse click. The software follows a similar process to help the user record and group metadata regarding the locations, institutions, imaging subjects, and people associated with the photographic data acquisition session. Relevant metadata can be entered to an extent determined by the user, grouped as desired, selected with a mouse click at the time of the capture session, and added to the DLN for a specific set of images. The tool includes a software installer, which installs the open source Postgres database and configures the Capture Context tool for use on both Windows and Mac OS X operating systems.

DLN:Inspector automatically checks the metadata for the image sets collected and preprocessed for RTI against documented rules and recommendations for camera settings, archival workflow, and preparation of images for future processing. The DLN:Inspector tool is intended to work with JPEG and Digital Negative (DNG) files, regardless of which processing tool was used to produce those files.

These tools will be made available in the Downloads area of this web site later in 2016.


Please note: Any views, findings, conclusions, or recommendations expressed in this website do not necessarily reflect those of the National Endowment for the Humanities.