Embracing Complex Interfaces Linking Deep Maps and Virtual Interiors to Big Data of the Dutch Golden Age.

Although semantic web technologies are gradually introduced in the digital humanities and cultural heritage institutions the representation of linked data is still very abstract and hardly allows for interactions by researchers or other users. SPARQL, for instance, is not a user-friendly language to query the Semantic Web and representations of Big Data, of historical networks or of Geographical Information Systems (GIS) are still just too “flat” to exploit them in depth for historical research in the humanities or for the disclosure of cultural heritage. (Bodenhamer 2010; Presner 2014). Humanities scholars have challenged the use of digital analytical methods of patterns in Big Data (Drucker 2011; 2013). Valuable as these studies are for close readings of small data, they do not provide solutions yet for handling Big Data and visualizations hereof. How can we embrace complexity, ambiguity, and uncertainty in the analysis and visualization of big data? This question is central in the project
Virtual Interiors as Interfaces for Big Historical Data Research (start September 2018.) It builds upon the current NWO-large infrastructure project
Golden Agents: Creative Industries and the Making of the Dutch Golden Age (2017-2022) that aims at analyzing interactions between various branches of the creative industries and between producers and consumers using a combination of semantic-web and multi-agent technologies and circa 2 million scans of notary acts, such as probate inventories of the City Archives of Amsterdam. Here we present the first experiments with the creation of complex 2D/3D/4D interfaces on top of the Semantic Web, that express uncertainties in/allow users to interact critically in multiple ways with data.

The 2D interface aims to preserve and present the complexities rooted in historical sources through deep mapping. Deep mapping creative industries in Amsterdam embraces the uncertainties to see, experience, and understand space in all its complexity, and enable the visualization and analysis of migration pattern of the creative individuals within the city. Methodologically, this project proposes a mechanism of translating the descriptions of location-related information in historical sources, which are often incomplete or imprecise, into concrete-georeferenced locations. The physical, geo-coded locations, as vectorized in the first cadastral map of Amsterdam by the HisGIS project, serves as a basis in this geo-translation process and as an anchor for the alignment of pre-cadastral maps, archival materials, and modern databases like biographical database such as
ECARTICO and visual collections like
RKDimages, creating a multi-layered deep map of the early modern Amsterdam.

This research develops a framework to analyze the fabrics of painting and other creative industries in an urban space and to understand their choices of location within the framework of location theories from economic geography (Williams, 2018; Isard, 1956). Data concerning the features of urban space, such as the accessibility to public service, market, and customers and the housing price, are collected and analyzed to contextualize the complex living environment of artists. The first experiment focuses on Rembrandt’s neighborhood. The deep maps of Rembrandt’s neighborhood represent the spatial and social connections among Rembrandt’s neighbors and the rental value of housing in the areas Rembrandt lived before and after his bankruptcy. Reconstructing the historical road system of Amsterdam during Rembrandt’s lifetime, the accessibility of Rembrandt’s neighborhood is evaluated to revitalize the physical surroundings of the artist.
The 3D/4D interfaces, which will be anchored at the GIS map layer, will act as a hub to connect the heterogeneous data that are available on 17th century creative industries in a spatially coherent context. Specifically, this part of the project focuses on the creation of virtual reconstructions of domestic interiors on the basis of the information provided by probate inventories and other notary acts, surviving material culture, and structural information from the houses’ building history. Documents with the richest descriptions are compared to archival sources, building floor plans and elevations, surviving objects, archeological finds and contemporary images to find suitable matches. Since this match is certainly not always possible, we need the big data of the Golden Agents project and other collections to select feasible case studies for the creation of some demonstrators. These demonstrators offer us a lens to zoom in into how individuals created, used, displayed and experienced cultural goods in their homes over time, and serve as spatially enhanced interfaces to existing and
ad-hoc developed databases on the creative industries of the Dutch Golden Age. The real-world measurements in which the virtual environments are created allow us moreover to engage with the physicality of the reconstructed domestic space and to use them as exploratory tools to test and show alternative hypotheses about the use of space and the positioning of paintings and other objects within each room.
Although the possibility of cross-referencing information from the abovementioned interdisciplinary data sources enhances our ability to create a reliable reconstruction, a varying degree of ambiguity will still remain. Uncertainty regarding e.g. the house layout and the appearance or position of furniture and objects belonging to the household calls for a structural solution. One of the aims of this project, which makes it relevant to any application in the field of digital humanities beyond this specific temporal and geographical context, is indeed to develop a consistent way to express uncertainty, to describe the source selection criteria and to explain the reasoning behind the 3D reconstruction process in a transparent way. Concerns about the reliability and the powerful agency of virtual reconstructions have been raised since their inception in the historical and archaeological domains (see e.g. Ryan 1996). Despite the fact that this discussion has resulted in recent years in issuing guidelines for best practices (Denard 2012), a reliable and widely applicable practical workflow for 3d/4d interfaces in which these issues of complexity and uncertainty are systematically taken into account is still missing. The case studies that will be presented here will show the work in progress towards an implementation that aims to fill this gap.

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