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Revealing matrices

Schich, Maximilian

In: Steele, Julie ; Iliinsky, Noah (Hrsgg.): Beautiful visualization : looking at data through the eyes of experts. Sebastopol, CA 2010, pp. 227-254

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This chapter illustrates the usefulness of enriched and refined data model matrices for database project evaluation, exposing many nonintuitive data properties that are hard to uncover by simply using a database or looking at the commonly used indicators of quality. As data becomes more accessible in the form of Linked Data, RDF graphs, or open dumps of relational tables, the presented methods can be applied by funders or the projects themselves, within a very short time frame in a mostly automated process. The visualizations in this chapter present the first comprehensive big picture of an entire example database – the Census of Antique Works of Art and Architecture Known in the Renaissance – where we can see the initial data model definition as well as the emerging complex structure in the collected data. I chose to visualize a state of the database at a point just before it was transferred from a graph-based database system (CENSUS 2005) to a more traditional relational database format (CENSUS BBAW) in 2006, allowing for comparison of the historic state with current and future achievements. By looking at the visualizations, we find out that many of the numbers given in project descriptions are incomplete or even misleading. Some of the new numbers may be smaller than the initially presented ones, but as we learn from our analysis, sometimes a little less is more—and more is different (Anderson 972).

Document type: Book Section
Version: Secondary publication
Date Deposited: 01 Jun 2010 06:42
Faculties / Institutes: University, Fakulty, Institute > Boston/MA , Northeastern University, Center for Complex Network Research
DDC-classification: Arts
Controlled Keywords: Kunstgeschichte, Archäologie, Geisteswissenschaften, Daten, Netzwerk
Uncontrolled Keywords: revealing matrices, beautiful visualization, complex networks, database, data model, node, link, node-link diagram, adjacency matrix, CENSUS
Subject (classification): Aesthetics, Art History