Imprint: The content of this blog entry is based on VR experiments in the context of projects carried out in the scope of the authors masters degree studies at FHNW University of Applied Sciences and Arts Northwestern Switzerland under the supervision of Prof. Dr. Doris Agotai.
Working with museological and cultural heritage data evidently brings some challenges along as this kind of data differs in its nature from data of other fields. Here are some ideas and approaches of how to tackle them.
Data structure and format
In order to allow any kind of automated data processing, structured data is required with unified scales of measurement. However many archives contain a mixture between quantitative and qualitative description of data, since information derived from expert knowledge is mostly qualitative in nature. To make use of textual descriptions, for example, requires to identify keywords and attribute them to an object in form of some kind of tags. Also for other scales of measurement harmonization might be needed.
Coping with the lack of standards
There is no global standard how archival or museological systems should be structured, each collection has its own structure. While in the past collection databases functioned as internal museum tools for the almost exclusive use of collection managers and curators, there was no obvious reason for standardisation and consequently little motivation to alter formats, classifications, and terminologies that characterized collections documentation. However nowadays, as Fiona Cameron points out, the presence of collection records on museum Internet sites has opened up database access for a wide range of potential users. Although this move has been touted in the linchpin solution to facilitating expanded public access to museum resources, the exact process for rendering collection databases truly useful and engaging to public users has remained undefined [1]. In consequence, it is difficult to combine data from multiple archives in one application and the reusability of an app developed for one particular dataset is limited.
Oliver Grau has written much on this subject, in particular in regards to the documentation of new media art [2] [3]. In addition, Hauck and Kuroczynski have made a proposition for a Cultural Heritage Markup Language, although their primary focus is on the creation and preservation of 3D assets of digital reconstructions [4]. Furthermore, the use of a museum collection management software like MuseumPlus or ArtPlus from zetcom for instance helps with the definition of data structure and documentation of collections and collection-related processes and could be an enabler of standards for this industry [5].
Dealing with incompleteness and imprecision
It is in the nature of cultural heritage data that datasets are often not complete or information is imprecise. An example for this is the geographical origin of objects. Instead of having a precise geolocation the given dataset only provides the name of a region, province or even just the country of origin. In such a case, where should the marker of such an object be placed on a world map – in the geometrical center of that province area or the capital city? Both proposition are based on assumptions and might not reflect the truth origin. When visualizing data it is important to be transparent about gaps in datasets. Careful consideration must be given not to imply a higher level of detail (LoD) in the data transformation process than the original level of information (LoI). In cultural heritage reconstruction the difference between LoD and LoI is referred to as level of hypothesis (LoH) [4]. Learnings from the field of of archaeology can be applied to this issue. Gershon puts emphasis on the importance of an accurate representation of incompleteness and uncertainty and recommends to purposefully choose a lower level of detail to demonstrate this [6].
Dealing with polysemy
In Theorizing Digital Cultural Heritage Cameron writes that “collection objects can be seen as inherently polysemic. That is, they possess the potential to be interpreted in a variety of way, depending on the nature of their incarnation as museum objects, and are subject to perceptual fluctuations in meaning dependent on various factors, whether cultural, theoretical, disciplinary, institutional, or individual.” She gives an example of a silver teaspoon that can be classified as Industrial Art, Decorative Art, Silver, Industry or anything else depending on the context and concludes that “an object’s meaning or its classification, is not self-evident or singular, but is imposed on it depending on the position and aims of the museum.” [1]
A similar issue regarding the categorisation of collection items occurs in the given dataset. As a concrete example, the material attribute contains almost as many different types and variants as there are objects in the collection. For meaningful interaction and usability an aggregation will be needed to a manageable amount of superordinate categories. Careful considerations need to be made as this classification process can be highly subjective.
Sensible choices and tradeoffs regarding visualisation
There are many factors to consider when making choices about the visual representation style starting with obvious factors such as color, shape, style, perspective, size and amount of data on display, medium, context, etc. It is evident that there is no neutral way to visually represent data points, each form of visualisation carries its own underlying message. Bolter writes in this context that “the computer is not a neutral space for conveying information. It shapes the information it conveys and is shaped in turn by the physical and cultural worlds in which it functions” [7]. Yet there are also many more less obvious design decisions that need to be considered. One of them is visualizing temporal evolution as the objects in the collection cover a long period of time over which many geopolitical changes have occured. Some collection items contain descriptions of historical geographical locations such as “Maya lowland” for example. How can the change of political structures over time be represented appropriately? The challenge posed regarding the visualisation of the geographical context is to find the right balance between historical fidelity on one side of the spectrum and orientation, comprehensibility and usability on the other side. An additional aspect that is also related to the map representation is a sensible approach to political issues such as disputed country borders and autonomous or independent regions.
Dealing with a documentation layer
Another challenge lies in the fact that archival databases typically consist of artefacts such as photographs and metadata representing the actual object. Yet this documentation layer is merely an image of the original and it should be taken into account that the reproduction might not be complete nor fully representing its substantiality and it can to some degree be an interpretation of the source object [8]. And an additional constraint is that in most cases there are only 2D images of objects available which limits the forms of representation in the virtual 3D space. While 3D scanning has become more accessible in recent years some of the reasons for not taking advantage thereof are the lack of knowhow and resources to create 3D models as well as a certain school of thought buzzing around that in the context of cultural heritage and art some objects should only be looked at from a particular perspective. For these reasons adequate display modes for 2D artefacts in a 3D environment have to be considered.
We will propose concepts of more in-depth solutions approaches to deal with the given constraints of museological cultural heritage data over the course of this project.
[1] Cameron, Fiona and Robinson, Helena (2007): Chapter “Digital Knowledgescapes: Cultural, Theoretical, Practical and Usage Issues Facing Museum Collection Databases in a Digital Epoch” in “Theorizing Digital Cultural Heritage. A critical Discourse” edited by Cameron, Fiona and Kenderdine, Sarah. MIT Press.
[2] Grau, Oliver (2013): “The Database of Virtual Art: for an expanded concept of documentation”. ICHIM 03 – Art Access & Visual Education. Archives & Museum Informatics Europe. URL: http://www.archimuse.com/publishing/ichim03/016C.pdf
[3] Grau, Oliver and Haller, Sebastian and Hoth, Janina and Rühse, Viola and Schiller, Devon and Seiser, Michaela (2017): “Documenting Media Art: A WEB 2.0-Archive and Bridging Thesaurus for MediaArtHistories”. Leonardo.
[4] Hauck, Oliver and Kuroczynski, Piotr (2015): “Cultural Heritage Markup Language: How to Record and Preserve 3D Assets of Digital Reconstruction”. Proceedings of the 20th International Conference on Cultural Heritage and New Technologies 2015 (CHNT 20).
[5] Zetcom. URL: https://www.zetcom.com
[6] Gershon, Nahum D. (1998): Visualization of an Imperfect World. IEEE Computer Graphics and Applications, p.43-45.
[7] Bolter, Jay David and Gromala, Diane (2003): “Windows and Mirrors: Interaction Design, Digital Art and the Myth of Transparency”. MIT Press, Cambridge, Massachusetts.
[8] K. Koebel, D. Agotai, S. Arisona and M. Oberli (2017): “Biennale 4D — A Journey in time: Virtual reality experience to explore the archives of the Swiss pavilion at the “Biennale di Venezia” art exhibition,” 23rd International Conference on Virtual System & Multimedia (VSMM), Dublin.