VII.7 The Census of Antique Works of Art and Architecture Known in the Renaissance 1947-2005

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Maximilian Schich

Maximilian Schich is an art historian working as DFG Visiting Research Scientist at the BarabásiLab—Center for Complex Network Research at Northeastern University in Boston, where he collaborates with network scientists, studying complex networks in art history and archaeology. This map presents a comprehensive picture of an entire scholarly database—the Census of Antique Works of Art and Architecture Known in the Renaissance. The map goes beyond the theoretic debates of database standards, formats, and software by depicting the actual configuration of existing data. Focusing on the connectivity of database entries, the map improves oversimplified—and, therefore, often wrong—indicators of data quality such as the raw number of records. Annotations in the map highlight a multitude of valuable insights that scholars can use to guide data access, management, and research. Similar maps can be produced for relational databases or linked open data in any domain. This map was created just before the transition from a graph database system (http://www.dyabola.de) to a more traditional relational database format (http://www.census.de), allowing for comparison of the historic state with future achievements.


References:

Schich, Maximilian. 2010. “Revealing Matrices.” In Beautiful Visualization: Looking at Data Through the Eyes of Experts, edited by Julie Steele and Noah Lilinsky, 227-254. Sebastopol, CA: O‘Reilly.

Schich, Maximilian. 2011. The Census of Antique Works of Art and Architecture Known in the Renaissance, 1947-2005. Courtesy of Maximilian Schich. In “7th Iteration (2011): Science Maps as Visual Interfaces to Digital Libraries,” Places & Spaces: Mapping Science, edited by Katy Börner and Michael J. Stamper. http://scimaps.org.

Acknowledgements: This exhibit is supported by the National Science Foundation under Grant No. IIS-0238261, CHE-0524661, IIS-0534909 and IIS-0715303, the James S. McDonnell Foundation; Thomson Reuters; the Cyberinfrastructure for Network Science Center, University Information Technology Services, and the School of Library and Information Science, all three at Indiana University. Some of the data used to generate the science maps is from the Web of Science by Thomson Reuters and Scopus by Elsevier. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.