What Is the Digital Lab Notebook?

Excerpt from a Leonardo da Vinci 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…

DLN Tool Suite

Download the Digital Lab Notebook Tools

CHI has released Beta versions of the first two tools in the Digital Lab Notebook software suite to simplify the collection and management of scientifically reliable metadata. Learn more and download the tools.

Related Project: The Democratization of Scientific Imaging through Metadata Management and Archival Submission Support

This CHI project is funded by a Preservation and Access Research and Development grant from the National Endowment for the Humanities, beginning January 2018. The project supports the development and enhancement of internationalized open source software tools for the collection, management, archiving, and sharing of cultural heritage imaging data and associated metadata. More…

Related Paper: “A Context Metadata Collection and Management Tool for Computational Photography Projects”

Top level interface for the DLN:CaptureContext tool, version 1

This paper, presented by CHI at the Archiving 2017 conference in Riga, Latvia, describes the first module of an advanced set of metadata and knowledge management tools to record a Digital Lab Notebook (DLN), the equivalent of the traditional scientist’s lab notebook. Learn more and download the PDF paper.

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

Cover of the Data Sustainability white paper

At the conclusion of an NEH Start-up grant awarded to CHI in 2014, the team 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. Download the PDF paper.

Other Related Publications

See these other CHI publications for more information pertaining to the Digital Lab Notebook.

NCPTT logo

NCPTT Preservation Technology and Training (PTT) Grant

Applying Scientific Rigor to Photogrammetric 3D Documentation for Cultural Heritage and Natural Science Materials

Contents:  Description  Impact and Deliverables  Background  Consultants and Advisors  

This one-year grant project began July 2016 and was completed on December 31, 2017.

Cultural Heritage Imaging (CHI), in collaboration with several partner consultants and technical advisors, was awarded a Preservation Technology and Training (PTT) Grant from the National Center for Preservation Technology and Training (NCPTT). The grant for $40,000 will produce advanced metadata and knowledge management tools to record a “Digital Lab Notebook” (DLN), the equivalent of the traditional scientist’s lab notebook, describing the means and context of 3D photogrammetric data capture.

Conceptual illustration of the Digital Lab Notebook

Conceptual illustration of the Digital Lab Notebook where user input information about imaging projects produces Linked Open Data


This project provides practical tools and guidance to cultural heritage and natural science practitioners applying close-range 3D photogrammetry during documentation and materials conservation activities in collections and historic sites. These tools will provide them the means to collect and manage scientific, quantitatively measurable, 3D digital representations.

This project’s collection and organization of process-oriented, contextual metadata is highly automated, occurring during the time the image data is captured and processed, rather than afterward. Previous efforts in the manual management of this provenance knowledge have mainly focused on the core data of the imaging subject. This project adds ISO-standard compliant metadata, which establishes the provenance and reliability of the subject’s quantitative digital representation. 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, enabling evaluation of reliability; and prepare digital 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 Deliverables

The project led to the adaptation of two open source software tools. They are now freely downloadable from our Downloads area on this website, where we currently offer RTI and other software. Users can download this project’s software tools and user guides, as well as other resources such as instructional videos. Both of the software tools are based on similar existing tools for use with RTI (see Background below) and have been reworked to meet the specific needs of photogrammetric image capture. This leverage allows the creation of impactful deliverables within a relatively small budget. The software tools have associated user guides and are subject to ongoing testing by members of the project team.

1. DLN:Capture Context for Photogrammetry

Top level interface for the DLN:CaptureContext tool, version 1 Beta

Top level interface for the DLN:CaptureContext tool, version 1 Beta. The initial version is designed to support RTI data.

This tool collects and organizes information that cannot be obtained automatically in software. This includes information about project purposes, the subject of the photographic capture, the people who are part of the project, the institutions or stakeholders involved, and specifics of the camera and lighting configuration. Documents and web links can also be incorporated into the data. While the camera automatically stores information about the camera settings for each image, it does not collect information about other aspects of the equipment, such as what illumination is used, how the camera is mounted (e.g., tripod or handheld), whether filters are used on the lens, whether spectra outside the visible are used, and so on. After a one-time entry of relevant information, this tool allows users to create templates of their equipment configurations and other frequently used information. The user selects and combines the appropriate organized information prior to data capture. The selected information is then automatically mapped to the CIDOC Conceptual Reference Model (CRM) to preserve any relationships present in the metadata. The tool then automatically produces a human-readable XML file and a file written in the machine-readable Resource Description Framework (RDF). The RDF file is prepared for web publication using Linked Open Data. The tools can import additional data at any time or export this information for use with the software on other computers. Data prepared in this way can automatically link to other related web information, widening and deepening the information relationships that underlie knowledge formation.

2. DLN:Inspector for Photogrammetry

Interface for the DLN:Inspector tool, version 1 Beta

Interface for the DLN:Inspector tool, version 1 Beta. This version contains rules specific to RTI data.

This tool automatically ensures that each image set meets the requirements for high-quality photogrammetry. These requirements can be checked algorithmically. For example it can confirm whether autofocus is turned off and check that aperture does not change across a given image calibration set. The tool will check for image-processing errors, such as sharpening, which should not be applied to photogrammetry data. This validation step will ensure users are alerted to potential issues in their image sets. Anyone else who wants to reuse these images can easily find this information.

3. A guide for users on the good practices of high-quality data acquisition for photogrammetry, including an aid to archiving. This guide will augment the photogrammetry Good Practice Guide already being made available by the UK’s Archaeology Data Service, written by Kieron Niven, one of this project’s advisors.

Community: CHI hosts and maintains a discussion forum site, CHIForums, as a public service. No fees are required for membership, and forum users can post questions and receive advice as they deploy the computational photography technologies fostered by CHI.


This proposal is an opportunity to realize extraordinary leverage from previous work by the project team, including their worldwide collaborators (see Consultants and Advisors below). Software for highly automated, scientific metadata acquisition and organization into a Digital Lab Notebook (DLN) already exists for use with the computational photography based Reflectance Transformation Imaging (RTI) technology. The National Science Foundation in 2010 and the National Endowment for the Humanities in 2014 supported this software’s development. This foundational work on the architecture and software for nearly automatic metadata collection and knowledge management is currently just for RTI. However, the tools are explicitly designed for adaptations to other computational photography based empirical data capture tools such as 3D photogrammetry, multi/hyperspectral imaging (M/HSI) and high dynamic range (HDR) imaging. The project will adapt this software for use with 3D photogrammetry, as envisioned by the earlier NSF and NEH funded projects. It will also produce guides for the integrated use of this new software within close range 3D photogrammetry good practice.

Paid Consultants

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.

Technical Advisors

Five experienced professionals will serve as volunteer technical advisors on this project.

Dominic Oldman

Dominic is the Principle Investigator of the Andrew W. Mellon Foundation’s ResearchSpace initiative at the British Museum and the deputy chair of ICOM’s CIDOC Conceptual Reference Model (CRM) Special Interest Group.

Steve Stead

Since 2002 Steve has worked on the development of the CIDOC Conceptual Reference Model (CRM) as part of the team that guided it through to becoming ISO21127:2006 and recently to becoming ISO21127:2014. Steve teaches the use of the CRM to heritage sector professionals..

Neffra Matthews

Neffra is a geographer with the National Operations Center, Bureau of Land Management (BLM). She is a also a photogrammetrist by profession, with 25 years of photogrammetry experience, and has spent much of her career producing maps from aerial photography and 3D models of cultural and paleontological subjects using close-range photogrammetry.

Kieron Niven

Kieron is the Digital Archivist and author/editor of the Guides to Good Practice series in the Archaeology Data Service (ADS) group in the Department of Archaeology at the University of York, UK.

Tom Malzbender

Tom is a research scientist working in computer vision, imaging, and 3D graphics. During his 31-year career at Hewlett-Packard Laboratories, he developed Reflectance Transformation Imaging (RTI) along with Dan Gelb. In collaboration with Mark Mudge, Tom co-invented Highlight RTI. His RTI/PTM methods are used in the fields of criminal forensics, paleontology, collections conservation and archaeology.