Building Museum Conservation Tools
Among many things, one part of the PhD that I am incredibly grateful for is the process of slowing down a bit and having time to really deep dive into a particular set of problems and focusing on an individual case study. While working on the Maori meetinghouse Te Hau Ki Turanga at the Museum of New Zealand Te Papa several pain points became very clear. The first of which was when I began researching the history of how the meetinghouse had been conserved over a period of 150 years and trying to piece together crack growth/restoration improvements from one conservator to the next. The second was during the digitally capture of the meetinghouse for the documentation of contemporary conservation reports and the amount of staff time this took. Finally, in handing over the 3D data-sets, finding software that could continue to track rate of change over time and monitoring (in quantifiable measurements) how the surface geometry of the structure was shifting-especially for the upcoming 3-year restoration project.
Pain Point 1: Researching the Conservation History of Te Hau Ki Turanga
While researching the conservation history of Te Hau Ki Turanga it became incredibly clear that there were huge gaps in knowledge not just between different institutions—the National Museum of New Zealand Te Papa was originally known as the Colonial Museum (dates) and then the Dominion Museum (dates) before its current title as Te Papa (1992-current)—but from year to year between different sets of conservators or registers. It was hard to decipher for example the hand illustrations of a conservator (think doctor’s note). This problem is not unique to the Museum of New Zealand, but I found is something that challenges the museum/heritage field in general.
Paint Point 2: Staff Time and Human Error during the 3D Capture Process
The complete 3D capture, through both photogrammetric and laser scan techniques, took approximated 12 hours per day for 7 days. This does not include the prep work that would add an addition 2-3 days of work. I found that the amount of staff time it takes to 3D capture a museum’s collection can be seen as a major friction point. In addition to the amount of time, human error is also a major factor in minimizing data error. The basic principles of good photogrammetric capture are good geometry. In order to minimize potential error in the data sets one must map out and align perfect geometric ratios from the camera sensor to the object with exact 66% overlap. When this is achieved the software can align the pixels in correct XYZ space from 9 different angles from the camera. Try as I may to have been perfect with my calculations and mapping of the space, the geometry did not end up being as exact as I wanted it to be.
Pain Point 3: Software that Produces 3D Surface Maps of Objects and then Compare Datasets
Finally, for the long term preservation strategy of Te Hau Ki Turanga especially during its 3-year restoration project it would be invaluable to be able to collect similar 3D data sets of the structure of the meetinghouse and compare these for alignment and to track change over time. Unfortunately, it does not look like there is currently software that does this.
Working with an engineering partner and discussing these pain points it has become clear that there needs to be solutions to these issues. The approach that we are taking is one that is modular, meaning can exist separately for each pain point, as well as work together addressing all 3 pain points—in 1 pipeline of productivity. In developing possible solutions, we are incredibly fortunate to work with a group of advisors on this project: Dale Kronkright, Director of Conservation Georgia O’Keeffe Museum; Liz Neely, Community Development American Alliance of Museums; James Davis, Professor Computer Science UCSC; Robert Kastler, Director of Photography at the Museum of Modern Art; and Carla Schroer, Director and Founder of Cultural Heritage Imaging.
Much more to come on this later….