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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Pateiro, T., Marques de Matos, D. & Cardoso, E. (2018). Visual analytics of Hebrew manuscripts codicological metadata. The 1st KDD Workshop on Data Science for Digital Art History: tackling big data Challenges, Algorithms, and Systems.
Exportar Referência (IEEE)
T. Pateiro et al.,  "Visual analytics of Hebrew manuscripts codicological metadata", in The 1st KDD Workshop on Data Science for Digital Art History: tackling big data Challenges, Algorithms, and Systems, London, 2018
Exportar BibTeX
@misc{pateiro2018_1732227821516,
	author = "Pateiro, T. and Marques de Matos, D. and Cardoso, E.",
	title = "Visual analytics of Hebrew manuscripts codicological metadata",
	year = "2018",
	howpublished = "Digital",
	url = "http://dsdah2018.blogs.dsv.su.se "
}
Exportar RIS
TY  - CPAPER
TI  - Visual analytics of Hebrew manuscripts codicological metadata
T2  - The 1st KDD Workshop on Data Science for Digital Art History: tackling big data Challenges, Algorithms, and Systems
AU  - Pateiro, T.
AU  - Marques de Matos, D.
AU  - Cardoso, E.
PY  - 2018
CY  - London
UR  - http://dsdah2018.blogs.dsv.su.se 
AB  - This paper presents the CodicoDaViz research project, developed with the goal of applying data visualisation techniques to the field of codicology. Adding to the multidisciplinary nature of digital humanities (DH), this project brings together a group of experts of DH, business intelligence and computer science. Using Hebrew manuscript data as a starting point, CodicoDaViz proposes an environment for exploratory analysis to be used by Humanities experts to deepen their understanding of codicological data, and to formulate new research hypotheses. In this paper we demonstrate how data visualisation was instrumental in understanding and structuring the dataset. Examples of the dashboards that have been designed (in Tableau) to enable an interactive and ad-hoc exploration of data are also discussed.
ER  -