SMHS SciVisualization - Revision history

Imoubara at 13:26, 23 May 2016

2016-05-23T13:26:04Z

Dinov at 13:23, 23 May 2016

2016-05-23T13:23:15Z

Dinov at 13:20, 23 May 2016

2016-05-23T13:20:51Z

Imoubara at 13:01, 23 May 2016

2016-05-23T13:01:44Z

Imoubara at 12:58, 23 May 2016

2016-05-23T12:58:50Z

Imoubara: /* Complex Network Visualization */

2016-05-19T13:52:57Z

‎Complex Network Visualization

Imoubara: /* SOCR, Excel and R Charts */

2016-05-19T13:52:50Z

‎SOCR, Excel and R Charts

Imoubara at 15:58, 18 May 2016

2016-05-18T15:58:41Z

Imoubara at 15:31, 16 May 2016

2016-05-16T15:31:37Z

Dinov at 15:36, 11 April 2016

2016-04-11T15:36:30Z

Show changes

← Older revision		Revision as of 13:26, 23 May 2016
Line 26:		Line 26:
	** Unsupervised exploratory data mining		** Unsupervised exploratory data mining

−
−	~~:* test (indented bullets)~~

@@ Line 25: / Line 25: @@
 ** Contrasting or comparing several data elements, relations, association
 ** Unsupervised exploratory data mining
 http://www.socr.umich.edu/CSCD/html/Cores/Macore2/SciViz.html

@@ Line 21: / Line 21: @@
 *Investigative Need: the specific scientific question or exploratory interest may also determine the type of visualization:
 ** Examining the composition of the data
-**Examining the composition of the data
+** Exploring the distribution of the data
 ** Contrasting or comparing several data elements, relations, association
-**Exploring the distribution of the data
+** Unsupervised exploratory data mining
 http://www.socr.umich.edu/CSCD/html/Cores/Macore2/SciViz.html

@@ Line 22: / Line 22: @@
 *Investigative Need: the specific scientific question or exploratory interest may also determine the type of visualization:
-**Examining the composition of the data</blockquote>
+**Examining the composition of the data
-**Exploring the distribution of the data</blockquote>
+**Exploring the distribution of the data
-**Contrasting or comparing several data elements, relations, association</blockquote>
+**Contrasting or comparing several data elements, relations, association
-**Unsupervised exploratory data mining</blockquote>
+**Unsupervised exploratory data mining
 http://www.socr.umich.edu/CSCD/html/Cores/Macore2/SciViz.html

@@ Line 3: / Line 3: @@
 ===Questions===
-<li>How and why should we “look” at data?</li>
+*How and why should we “look” at data?
-<li>What data characteristics are important for exploratory data analytics (EDAs)?</li>
+*What data characteristics are important for exploratory data analytics (EDAs)?
 Scientific Data-driven or Simulation-driven visualization methods may be classified in many alternative ways. Visualization techniques can be classified according to many criteria:
@@ Line 10: / Line 10: @@
 <center>[[Image:SMHS_SciVisualization1.png|500px]] </center>
-•	Data Type: structured/unstructured, small/large, complete/incomplete, time/space, ascii/binary, Euclidean/non-Euclidean, etc.
+*Data Type: structured/unstructured, small/large, complete/incomplete, time/space, ascii/binary, Euclidean/non-Euclidean, etc.
-•	Task type: Task  type  is  one  of  the  aspects  considered  in classification  of  visualization  techniques,  which provides means of interaction between the researcher, the data and the display software/platform
+*Task type: Task  type  is  one  of  the  aspects  considered  in classification  of  visualization  techniques,  which provides means of interaction between the researcher, the data and the display software/platform
-•	Scalability:  Visualization   techniques   are   subject   to   some limitations, such as the amount of data that a particular technique can exhibit
+*Scalability:  Visualization   techniques   are   subject   to   some limitations, such as the amount of data that a particular technique can exhibit
-•	Dimensionality: Visualization   techniques   can   also   be   classified according to the number of attributes
+*Dimensionality: Visualization   techniques   can   also   be   classified according to the number of attributes
-•	Positioning and Attributes: the distribution   of   attributes   on   the   chart may affect the interpretation    of    the display representation, e.g., correlation analysis, where the relative distance among the plotted attributes is relevant for observation
+*Positioning and Attributes: the distribution   of   attributes   on   the   chart may affect the interpretation    of    the display representation, e.g., correlation analysis, where the relative distance among the plotted attributes is relevant for observation
-•	Investigative Need: the specific scientific question or exploratory interest may also determine the type of visualization:
+*Investigative Need: the specific scientific question or exploratory interest may also determine the type of visualization:
-<blockquote>o	Examining the composition of the data</blockquote>
+**Examining the composition of the data</blockquote>
-<blockquote>o	Exploring the distribution of the data</blockquote>
+**Exploring the distribution of the data</blockquote>
-<blockquote>o	Contrasting or comparing several data elements, relations, association</blockquote>
+**Contrasting or comparing several data elements, relations, association</blockquote>
-<blockquote>o	Unsupervised exploratory data mining</blockquote>
+**Unsupervised exploratory data mining</blockquote>
 http://www.socr.umich.edu/CSCD/html/Cores/Macore2/SciViz.html

← Older revision		Revision as of 13:52, 19 May 2016
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	==[[SMHS_SciVisualization_SOCR_Excel_R_Charts\|SOCR, Excel and R Charts]]==		==[[SMHS_SciVisualization_SOCR_Excel_R_Charts\|SOCR, Excel and R Charts]]==

−	===[[SMHS_SciVisualization_NetworkViz\|Complex Network Visualization]]===	+	==[[SMHS_SciVisualization_NetworkViz\|Complex Network Visualization]]==

@@ Line 32: / Line 32: @@
 http://www.socr.umich.edu/CSCD/html/Cores/Macore2/SciViz.html
-===[[SMHS_SciVisualization_SOCR_Excel_R_Charts|SOCR, Excel and R Charts]]===
+==[[SMHS_SciVisualization_SOCR_Excel_R_Charts|SOCR, Excel and R Charts]]==
 ===[[SMHS_SciVisualization_NetworkViz|Complex Network Visualization]]===