11.3 NFOVIS VS SCIVIS 11.3.2 DATA DOMAIN The domain of a scivis dataset typically describes a compact region of sampled at several locations Infovis no spatial information(sample points Dont contain cells having the function of interpolation
11.3 INFOVIS VS SCIVIS 11.3.2 DATA DOMAIN • The domain of a scivis dataset typically describes a compact region of sampled at several locations • Infovis: • no spatial information (sample points) • Don’t contain cells having the function of interpolation n R
11.3 NFOVIS VS SCIVIS 11.3.3 DATA ATTRIBUTES infovis vs scivis Infovis data values are of more types than numerical values · Sci vis classification The kind of scale: nominal, ordinal, binary, discrete, and continuous Qualitative, quantitative and categorical Linear, planar, volumetric, temporal, multidimensional, tree, network, and workspace Values and relations
11.3 INFOVIS VS SCIVIS 11.3.3 DATA ATTRIBUTES • infovis VS Scivis • Infovis data values are of more types than numerical values • SciVis classification: • The kind of scale: nominal,ordinal, binary, discrete, and continuous • Qualitative, quantitative and categorical • Linear, planar, volumetric, temporal, multidimensional, tree, network, and workspace. • Values and Relations
11.3 NFOVIS VS SCIVIS 11.3.3 DATA ATTRIBUTES Data type Attribute domain Operations Examples nominal unordered set comparison text, references syntax elements ordered set ordering ratings (e.g, bad average, good) discrete integers(7, N) integer arithmetic lines of code continuous reals(R) real arithmetic code metrics Table 11.1. attribute data types in infovis
11.3 INFOVIS VS SCIVIS 11.3.3 DATA ATTRIBUTES Table 11.1. Attribute data types in infovis
11.3 NFOVIS VS SCIVIS 11.3.4 INTERPOLATION Infovis: inherently discrete SciVis: originally continuous Scivis Infovis Data domain spatial C Rn abstract, non-spatial Attribute types numeric C Rm any data types Data points samples of attributes tuples of attributes over domain without spatial location Cells support interpolation describe relations Interpolation piecewise continuous can be inexistent Table 11.2. Comparison of dataset notions in scivis and infovis
11.3 INFOVIS VS SCIVIS 11.3.4 INTERPOLATION Table 11.2. Comparison of dataset notions in scivis and infovis. ◼ Infovis: inherently discrete ◼ SciVis: originally continuous
11.4 TABLE VISUALIZATION 7950000795000 200411301200 000079500 079500007950007950000,795000 SI 0.795000079500095000705000 0000.795000 20050071500 0010790000790000 200001400795000700079500079500 Figure 11.2. Textual visualization of a database table containing stock exchange data
11.4 TABLE VISUALIZATION Figure 11.2. Textual visualization of a database table containing stock exchange data