3D modelling is becoming increasingly common in archaeology, and certainly has a range of benefits – fast, accurate digitalisation of spaces and surfaces. However, building the models is only part of the story. Sharing and interacting with these digital representations of archaeology is just as important. Such representations can remain in internal circulation, accessible only to researchers, or data can be shared in accessible formats online, on institution and project websites or, as is increasingly the case, on online platforms. There are a range of platforms for sharing 3D data – SketchFab is one of the most popular. For example the ULAS team chose to release the model of Richard III’s grave on the service last week. It provides a freely accessible web interface for sharing and viewing models.
Since February I’ve been building a SketchFab collection of 3D models relevant to bioarchaeology and funerary archaeology shared on the site by users from across the globe. One aim in building the collection was to better understand if individuals are sharing 3D models of human remains, and how.
I also aimed to build a resource for those interested – it is not always easy to find examples for teaching or research among the thousands of models, but good models can be highly engaging, especially when viewed with simple technology such as Google Cardboard – providing a particular interface to the archaeology.
Searching here, web scraping there: Building a Virtual Collection and Dataset
I decided to go ‘meta’ and web scrape data to analyse one example of a public platform used to display 3D funerary archaeology and human remains. Find out how those are being shared online, and present some thoughts on best practice based on the data, contributing a little to current discussions regarding the practice of digital archaeology and ethics of the digital display of human remains online.
Although I selected Sketchfab for this analysis, a range of other private and public platforms do host models, such as 123D Catch, data repositories such as MorphoSource, and institutional websites like X 3D from the Smithsonian or Digitised Diseases, and there are mobile applications such as Dactyl.
Finding models involves searches of keywords, tags and following winding link trails. I often searched for the same word in different languages: as a Portuguese speaker I’m aware that much of the web is not in English! Through this process I’ve added 170 models so far – all of funerary contexts which appear to include human remains or models of human remains from archaeological, anthropological and medical reference collections.
I extracted metadata and categorised the models using criteria to analyse current use of the platform and its implications for our research. I looked at what types of model were being posted, who was posting them, if they were contextualised with further information, annotation and tags, and what models were being viewed, discussed and downloaded.
To get the data I made use of the great importXML feature in Google Sheets to scrape directly from the site source code. It involved a bit of tweaking, but now I can automatically update and add data in one table. I’m sure that importXML will be the subject of a later blog post!
=TRIM(ArrayFormula(CONCATENATE(IFERROR(importxml(A2,”//a[@class=’item tag-item’]”),””)& CHAR(10))))
Google Sheets formula of the day. Extracting SketchFab tags for metadata analysis!
The anatomy of a digital collection
Of the 170 models in the collection, five were discounted as it was unclear where the human remains were present in the models. That left 165 for analysis. These fell into two groups:
- Elements – 99 models showing skeletal elements out of context, including medical and archaeological reference material
- In Situ – 66 models of remains recorded in situ in excavations or funerary spaces
Elements are more numerous than in situ models, although an outlier user contributes significantly to their total, having uploaded 38 models of individual elements: mostly humeri. In addition, approximately 19 elements are from medical and anthropological reference collections rather than archaeological contexts, which might skew the comparison.
The elements are split between parts of the appendicular (50) and axial skeleton (49) – but two elements are most highly shared: 35 humeri, and 30 almost complete crania. The in situ models are mostly single articulated or semi-articulated inhumations (54 of 66 in situ models), sometimes in full cemeteries. The remainder are collective and multiple inhumations (see Knüsel 2014) including mass graves, or unidentified disarticulated, commingled remains. One secondary cremated deposit is shown (a model loaded by me).
53 user accounts contributed models in the collection. 36 appear to be accounts of individuals, and 17 may represent organisations. Individuals contributed 65% of the models. Users tend to either post in-situ models or elements, not both: only four of the 53 users loaded both categories. Notably, bioarchaeology is used only once as a tag which may indicate that the users are not bioarchaeologists – indeed, only four users appear to be focused on the study of human remains. This could also indicate that bioarchaeologists are not heavily involved in the sharing of human remains on the platform.
The models are presented in a variety of formats with a range of contextual information. Over half featured some form of description, and some of them are very insightful. 56% were described in the 256 character text field provided, of these, 19 models included a link to an external site for more information.
But, 44% didn’t feature any description, which makes it much harder for the viewer to contextualise what they are looking at, especially considering that this is a public platform with many viewers who might not have specific osteological or archaeological knowledge.
Annotations can be added to models (limited to five for free accounts). 141 models didn’t make use of this, but several others had high numbers of annotations. One example used 38 to mark multiple cranio-facial features.
A surprising aspect was the lack of scales included within models. Just 15 of the in situ models, and one of the elements included scales.
More are tagged than categorised, perhaps due to the fact that the categories are fixed and relatively generic (i.e. ‘Science’ or ‘3D scan’). Because the tags are more flexible I’ve broken them out for analysis.
|Tags & Cats||No Tags or Categories||Only Categorised||Only Tagged||Tagged and Categorised||Grand Total|
The top two most used tags: ‘Agisoft’ and ‘Photoscan’ refer to Agisoft Photoscan software for photogrammetry and are mentioned 59 times, ‘photogrammetry’ is mentioned 15 times. Archaeology is used frequently, as well as anatomy. A further 121 tags are used on under 10 models, including the word archaeology in other languages, and words like anthropology, osteology and human. Bioarchaeology is used only once for a model of a Çatalhöyük burial. The tag frequencies could be the result of the diverse nature of some of the material – you might assume that the modelling technique is the only common element of many models, but they are all of human remains. This may indicate a preoccupation with technology and technique rather than the subjects.
Most models had less than 1000 views, however, five have over 1000 views. The first of the ‘top five’ is Richard III’s grave (in situ), which is already dominating the figures with 77% of the total views for the collection. A cranium from the Battle of Culloden which was previously reported on the BBC is also in the ‘top five’ category. The smaller numbers of in situ models are more viewed and liked than elements. This is influenced by the Richard III model, but even discounting that one, there are more views per in situ model.
|Av. Per Model||–||536.5||2.7||2.6||0.2|
Categories and tags appear to make the models more easily visible – the 82 items with no tags or categories assigned have a mean value of only 48.2 views, compared to 2481.8 for models which have been tagged and categorised. Even without Richard III (which is tagged and categorised), the other tagged and categorised models have a mean view value of 371.5.
|Tags and Cats||No. Models||Views||Views per Model Category||Downloads||Likes||Comments|
|Tagged and Categorised||32||79418||2481.8||299||242||29|
|No Tags or Categories||82||3955||48.2||19||0|
What do the data say?
More elements are being counted than funerary contexts. This may have been influenced by selection, as my search might not have been representative, and a single outlier user contributed 38 models of which all were elements. The outlier user also appears to be a factor in the high frequency of humeri in the sample; but the general occurrence of humeri, crania and femurs may be due to the fact that they are three very recognisable parts of the skeleton.
The sharing of elements and funerary contexts on this platform appears to be more ‘bottom-up’ than ‘top-down’. This is because organisations seem to contribute fewer models of remains than individuals. We can’t be sure why, but it could be related to policy as museums are posting other models. The British Museum currently has 34 models on Sketchfab, but none show human remains:
“the websites of museums seem far more reluctant to display the dead online…It might also relate to the fear of de-contextualising human remains” (Williams and Atkin 2015)
Another possibility is that the organisations prefer to run their own platforms i.e. Digitised Diseases or the Smithsonian’s 3DX, rather than upload remains to third party sites.
There are good examples of contextualised information in the descriptions of several models, but the missing information for almost half the dataset does have an impact on the engagement. The models are being shared on a public platform, but without descriptions their communicative potential is limited. In addition, few models make use of annotations, and only a small number include a scale. Their potential for research and education is diminished when this contextual information is not included. A comment from Sara Perry regarding the physical display of human remains highlights relevant points:
“the more meaningful displays of ethically-loaded objects are those that are well-contextualised, that use both visuals and text to jar viewers out of simplistic interpretations of the subject matter, that weave displays together into a larger critical narrative; and that attempt to trace – or account for the lack of tracing of – consent” (Perry 2011)
This brings us to the ethical discussion about the display of human remains, which can be a sensitive subject. Without contextual information, there is less clarity on rationale and consent for sharing, which are important points of ethical statements and codes of practice relating to human remains in archaeology, the Vermillion Accord (World Archaeological Congress 1989), Tamaki Makau-rau Accord (World Archaeological Congress 2005), BABAO Code of Practice (2010) and BABAO Code of Ethics (2010) and the Dilmun Bioarchaeology Ethics Statement (Morgan and Boutin 2009) among others. But, these do emphasise support for the scientific value of such remains in research, and encourage the communication of results and display of human remains. Therefore, if descriptions are provided in a considered and informative manner, addressing ethical matters, then we are heading in the right direction.
The approach can be related in some ways to the idea of ‘slow data’ (Kansa 2015), which highlights “the value of small and properly contextualized data”, and proposes careful consideration of the management and dissemination of such data. Most models in the collection were not available for download, but all of the 14 models that were available were downloaded at least twice and one was downloaded 234 times. Download availability is another aspect of interaction requiring ethical consideration. On one hand this can promote open data, and new teaching and learning experiences, on the other, the ethical and legal implications of sharing human remains in digital formats are still under debate – the application depends on the project context.
There are differing approaches to this. For example, ULAS decided not to make the Richard III model available to download. Other platforms such as Digitised Diseases permit downloads of their reference material, but no 3D prints. In a more ancient case, the recent open access publication of Homo Naledi did include 3D data stored on the MorphoSource repository which could be shared and printed (Berger et al. 2015). On Sketchfab other users are posting reference material online which may be used to print local copies at other institutions, for example VCU Archaeology has posted approximately 273 models, including human remains (Means 2016).
I should point out a caveat regarding this dataset. The reason for posting the models is not always clear. For example, models may not have descriptions due to the fact that they are loaded as ‘tests’ or for use within groups rather than having the purpose of specific public engagement. But we should not forget that Sketchfab is a public platform where anyone can access (and analyse!) the data.
This has been an interesting exercise in understanding how 3D models of human remains and funerary archaeology are shared on one online platform. Clearly, the data is from a subset of models and there are other project sites and platforms, but this dataset can provide one example of current practice. Sketchfab is an online platform for general use and the user interface is fixed, rather than specifically customisable (see Opitz and Johnson 2016). Therefore, to enhance user experience we should better understand the way the available features are used, and propose best practices. Based on this review there are certainly a number of areas that I will look to reinforce in my own work, which may be applicable to any models:
- Consider the purpose of sharing the data, and who the project is for. Build an approach and develop an ethical statement on the creation and sharing of digital imaging and web platform use – for human remains. Make sure this considers relevant local legislation i.e. the Human Tissue Act in the UK
- Go for gold with your descriptions and curate your metadata! It is vital to contextualise the models and provide information on ethical or legal guidelines. Providing links to further information is recommended. Tagging and categorising the models also makes them much more accessible
- For bonus points post the approved data to an open repository such as Figshare or MorphoSource, and reference a data DOI in the model description. Creative Commons provides a range of licencing options. Ensure that the data is preserved in a digital repository or archive
- Quality control: Check the model orientation and that the background is not overpowering. Scales or control points should be included. Ensure the model works well in Virtual Reality (VR). Remove test models from accounts unless needed. Consult or work in collaboration with a bioarchaeologist to make sure the descriptions are relevant and identifications are positive
There are myriad applications of 3D modelling in archaeology, which only increase as the tools and technology are adopted. Every day more and more links to 3D models on project sites and platforms are shared on sites like Twitter – for example see @STORI3D_PAST.
Freemium online platforms address an issue previously noted: “One of the key problems in 3D post-processing is the management and accessibility of data and models” (Forte et al. 2012, 9) – providing an accessible portal with an integrated 3D viewer. They also support open data and sharing. Open access to information can enable a vast array of different initiatives, combined in creative ways, like this ‘diary in the attic’ from @electricarchaeo (Graham 2015).
In bioarchaeology, participation on these types of platforms can allow us to address the “lack of online engagement between bioarchaeologists and the public…champion the tenets of anthropology and counteract popular misconceptions about skeletons and burials” which was noted by Meyers Emery & Killgrove (2015) in a recent article on bioarchaeology blogs.
Increasingly, institutions are also understanding that much of their public engagement will now take place digitally, with platforms acting as a ‘medium through which information is published or exchanged’ (Proctor 2010). The British Museum have a Sketchfab account, hosted an account for 3D models on GitHub, and linked to models online as part of a recent exhibition. Still more can be done: @CosmoWenman recently called for museums to start to share more of their unpublished 3D data more openly. Cosmo highlighted the fact that it can result in increased accessibility, as for example 3D models provide tactile feedback for the blind. Other projects are also sharing. Must Farm is a great example of the use of digital media including Must Farm site diary blogs and social media to engage and communicate. Virtual collections can also be used as reference material for students and specialists, as in the case of VCU, or Digitised Diseases, and for classroom demos. From personal experience I know that VR can enhance learning having provided Google Cardboard to students in classes for immersive activities.
As we move through the adoption curve for these technologies, digital 3D models will become ever more common. This presents a great opportunity but also a significant challenge; an opportunity in that it is possible to use this media in highly engaging ways and directly share detailed information. The challenges include the presentation and association of relevant information for each model, the curation of the data and ensuring long term accessibility, and the approach to the ethics of the creation and sharing of such media. We have great examples of well contextualised data, presented in engaging ways, but there is much that can be done yet. We should advocate for continued conversation on best practice about how and where to create, share and curate this digital media, but most importantly we should ask ourselves why we are creating the models, and who we are sharing them with.
Header Image: 2 Crouched Burial inserted in Bronze Age pit (Source: Powlesland 2015) https://skfb.ly/CMXH (CC BY-NC 4.0).
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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