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A five-tile tomographic micro-CT dataset of the oak sculpture "Holy woman with lantern" - part 2 of 2

<p><strong>Summary</strong><br> This submission contains a five-tile tomographic datasets of an oak sculpture <em>Holy woman with lantern,&nbsp;</em>belonging to the Rijksmuseum collection. The first part consists of the first three tiles, the second part of the last two tiles. The data is made available as part of [Bossema et al., 2020] and [Dom&iacute;nguez-Delm&aacute;s et al., 2020]. &nbsp;</p> <p><strong>Apparatus</strong><br> The dataset is acquired using the custom-built and highly flexible CT scanner, FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1944-by-1536&nbsp;pixels, 14-bit, flat detector panel. Full details can be found in [Coban 2020].</p> <p><strong>Sample Information</strong><br> The sample is an oak sculpture of a <em>Holy woman with lantern</em>, 35.8 cm high, c. 1500-1525 [Rijksmuseum inventory number BK-NM-9253, &nbsp;https://www.rijksmuseum.nl/en/collection/BK-NM-9253]. It was mounted on a wooden block on the rotation stage.</p> <p>See Figure 7 in [Bossema et al., 2020] for a picture of the object and the mount and [Dom&iacute;nguez-Delm&aacute;s, 2020] for analysis of the reconstructed images. <em>&nbsp;</em><br> &nbsp;</p> <p><strong>Experimental Plan</strong><br> The data in this submission was collected to facilitate measurements of the tree rings (dendrochronological research) at different heights, and to illustrate the use of detector tiling for the investigation cultural heritage objects. To image the entire object, five vertical tiles were scanned at image resolution 67.8 micron. For each scan, the sample was rotated 360&deg; in circular and continuous motion, with a dark-field (closed-shutter), and 2 flat-field (open-shutter) images taken before and after the acquisition. The datasets of Tile 1-4 consist of 2914 projections, the dataset of Tile 5 of 1500 projections.<br> All raw data (i.e. no corrections) is made available in .tif format.</p> <p><strong>List of Contents</strong><br> The content of the submission is given below.</p> <p>part 1:</p> <ul> <li><strong>t1: </strong>first vertical tile, bottom of sculpture</li> <li><strong>t2:</strong> second vertical tile</li> <li><strong>t3:</strong> third vertical tile</li> </ul> <p>part 2:</p> <ul> <li><strong>t4:</strong> fourth vertical tile</li> <li><strong>t5:</strong> fifth vertical tile, top of the sculpture</li> </ul> <p>Each data folder contains:</p> <ul> <li>dark-field (or closed-shutter) image,&nbsp;<em>di000000.tif</em>,</li> <li>flat-field (or open-shutter) image before acquisition,&nbsp;<em>io000000.tif</em>, and after acquisition, <em>io000001.tif</em>,</li> <li>raw (unprocessed or uncorrected) projections,&nbsp;<em>scan_*.tif</em>,</li> <li><em>data settings XRE.txt</em>, a text file with scanner metadata,</li> <li><em>scan settings.txt</em>, a text file with scanner metadata in more human readable format, and</li> <li><em>data settings XRE.ini</em>, a snapshot text file of basic geometry information at the start of a scan.</li> <li><em>script_executed.txt</em>, the text file containing the list of commands the apparatus has executed.</li> </ul> <p><strong>Additional Links</strong><br> These&nbsp;datasets are&nbsp;produced by the&nbsp;<a href="https://www.cwi.nl/research/groups/computational-imaging">Computational Imaging group</a>&nbsp;at Centrum Wiskunde &amp; Informatica (CI-CWI). For any relevant Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group&#39;s&nbsp;<a href="http://github.com/cicwi">GitHub page</a>.</p> <p><strong>Contact Details</strong><br> For more information or guidance in using these datasets, please get in touch with&nbsp;</p> <ul> <li>bossema [at] cwi.nl</li> </ul> <p><strong>Acknowledgments</strong><br> We thank Paul van Duin and Marta Dom&iacute;nguez Delm&aacute;s for providing us with the opportunity to scan this interesting object.</p>

ShareScore

28/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
8
Access
16
Reuse readiness
0
Engagement
0

Dataset details

Repository
zenodo
Published
April 9, 2020
License
cc-by-4.0
DOI
10.5281/zenodo.3747326

Scored with release 0.9.0

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