Computer Graphics（PPT讲稿）INFORMATION VISUALIZATION

CHAPTER 11 INFORMATION VISUALIZATION

CHAPTER 11 INFORMATION VISUALIZATION

OUTLINE Scientific Visualization(scivis) Engineering, computational fluid mechanics, mathematics to medical and earth scIences Data coming from numerical simulations and measurements of physical quantities Information Visualization(infovis) More abstract of data Generic graph, trees to database tables, text and computer software Present a succinct overview of inforvis methods and techniques

OUTLINE • Scientific Visualization (scivis) • Engineering, computational fluid mechanics, mathematics to medical and earth sciences • Data coming from numerical simulations and measurements of physical quantities • Information Visualization (infovis) • More abstract of data • Generic graph, trees to database tables, text and computer software • Present a succinct overview of inforvis methods and techniques

OUTLINE 11.2 goal of infovis 11.3 similarities and differences between the scivis and infovis fields 11.4 visualization of the database table 11.5 visualization of relational data 11.6 visualization of multivariate data 11.7 visualization of text document

OUTLINE 11.2 goal of infovis 11.3 similarities and differences between the scivis and infovis fields 11.4 visualization of the database table 11.5 visualization of relational data 11.6 visualization of multivariate data 11.7 visualization of text document

11.2 WHAT'S INFOVIS? To visualize is to form a mental model or mental image of something" [Spence 071 Broad definition visualization applies to abstract quantities and relations in order to get insight in the data [chi 02 1 Inforvis application a wider spectrum of data types than scivis applications: data that has no physical placement > Abstract data: computer file systems, databases documents from archives, and stock exchange courses

11.2 WHAT’S INFOVIS? ◼ To visualize is to “form a mental model or mental image of something” [Spence 07] ◼ Broad definition: visualization applies to abstract quantities and relations in order to get insight in the data [Chi 02 ] ◼ Inforvis application ➢a wider spectrum of data types than scivis applications: data that has no physical placement ➢Abstract data: computer file systems, databases, documents from archives, and stock exchange courses

11.3 NFOVIS VS SCIVIS 11.3.1 DATASET B Java 500 p3 pa 100 Figure 11.1. EXamples of (a) scivis and(b) infovis datasets

11.3 INFOVIS VS SCIVIS 11.3.1 DATASET Figure 11.1. Examples of (a) scivis and (b) infovis datasets

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