Rester, Markus

2007-11-01T14:58:09Z

Markus:

File:DI Dr. Rester Markus.jpg

2007-11-01T14:57:11Z

Markus: New page: == Summary == == Copyright status == == Source ==

== Summary ==

== Copyright status ==

== Source ==

Tasks Taxonomy for Graphs

2007-08-16T07:48:43Z

Markus: Reverted edit of Nx3Ppr, changed back to last version by Iwolf

== Low-Level Tasks ==

From [Amar et al. 2005] and [Lee et al 2006].

* General Tasks
{|border="1"
|-
|'''Task'''||'''Description'''
|-
|Retrieve Value ||Given a set of cases, find attributes of those cases.
|-
|Filter||Given some conditions on attributes values, find data cases satisfying those conditions.
|-
|Compute Derived Value||Given a set of data cases, compute an aggregate numeric representation of those data cases.(e.g. average, median, and count)
|-
|Find Extremum||Find data cases possessing an extreme value of an attribute over its range within the data set.
|-
|Sort||Given a set of data cases, rank them according to some ordinal metric.
Determine Range Given a set of data cases and an attribute of interest, find the span of values within the set.
|-
|Characterize Distribution||Given a set of data cases and a quantitative attribute of interest, characterize the distribution of that attribute’s values over the set.
|-
|Find Anomalies||Identify any anomalies within a given set of data cases with respect to a given relationship or expectation, e.g. statistical outliers.
|-
|Cluster||Given a set of data cases, find clusters of similar attribute values.
|-
|Correlate||Given a set of data cases and two attributes, determine useful relationships between the values of those attributes.
|-
|Scan|| Quickly review a set of items.
|-
|Set Operation|| Given multiple sets of items, perform set operations on them. For example, find the intersection of the set of nodes.
|}

* Graph Specific Tasks
{|border="1"
|-
|'''Task'''||'''Description'''
|-
|Find Adjacent Nodes ||Given a node, find its adjacent nodes.
|}

== Graph Task Taxonomy ==

Examples are illustrated using 4 types of graphs:
*(FOAF): friend-of-a-friend
*(FW): food web
*(GO): gene ontology
*(ARM): airport routing map

=== Topology-based Tasks ===

{| border="1"
|-
|'''Task'''||'''Description''' || '''Examples'''
|-
| Adjacency (direct connection)
|
* Find the set of nodes adjacent to a node?
* How many nodes are adjacent to a node?
* Which node has a maximum number of adjacent nodes?
||
*(FOAF) Find the names of the direct friends of Eric.
*(FW) How many kinds of organisms do golden eagles eat?
*(FOAF) Who is the most popular person?
|-
| Accessibility (direct or indirect connection)
|
* Find the set of nodes accessible from a node.
* How many nodes are accessible from a node?
* Find the set of nodes accessible from a node where the distance is less than or equal to n.
* How many nodes are accessible from a node where the distance is less than or equal to n?
||
*(FOAF) Who are your friends, your friends’ friends, and so on?
*(FOAF) How many friends are you connected to in this way?
*(ARM) To what cities can we go from Seoul, Korea by changing planes only once?
|-
| Commmon Connection
|
* Given nodes, find a set of nodes that are connected to all of them.
||
*(FOAF)Find all the people who know both John and Jack.
|-
| Connectivty
|
*Find the shortest path between two nodes.
*Identify clusters.
*Identify connected components.
*Find bridges.
*Find articulation points.
||
*(ARM) What is the shortest path from Seoul, Korea to Athens, Greece?
*(FOAF) Count the number of clusters.
*(FW) There may be subgraphs independent of each other. Count the number of connected components in the graph.
*(FOAF) Who is the person whose removal from the graph results in an unconnected graph?
*(FW) Which is the eating link whose removal from the graph results in an unconnected graph?
|}

=== Attribute-based Tasks ===

{| border="1"
|-
|'''Task'''||'''Description''' || '''Examples'''
|-
| On the Nodes
|
* Find the nodes having a specific attribute value.
* Review the set of nodes.
||
*(FOAF) Who do you know from the people currently shown on screen?
*(FOAF) How many people do you know from the ones currently shown on screen?
*(FOAF) Are there any foreign-sounding names?
|-
| On the Links
|
* Given a node, find the nodes connected only by certain types of links.
* Which node is connected by a link having the largest/smallest value?
||
*(GO) Find the nodes connected by “is-a” relationships from the “Biological Process” node.
*(FW) If a link has an attribute representing the percentage of the diet, what is main food of American crow?
|}

=== Browsing Tasks ===
{| border="1"
|-
|'''Task'''||'''Description''' || '''Examples'''
|-
| Follow Path
|
* Follow a given path
||
* (FOAF) A user looks into A’s friend B, B’s friend C, and C’s friend D.
* (FW) Follow the flow of energy from grasses, to a rabbit that eats grass, to a carnivore that eats the rabbit, and to a carnivore that eats that carnivore.
|-
| Revisit
|
* Return to a previously visited node.
||
*(FOAF) After they follow a path in the above task, they may want to see A’s other friends.
*(FW) Find another carnivore that eats the same rabbit.
|}

=== Overview Tasks ===
This is a compound exploratory task to get estimated values quickly. For example, we might ask users to estimate the size of the social network. Note that sometimes it is more important to be able to estimate the answer than to get an accurate one. Some of the topology tasks can be done easily using an overview of the graph as well. For example, using particular layout algorithms, it is easy to see whether or not there are clusters and connected components. Other algorithms help to find shortest paths between nodes. Overview also helps to find patterns.

Examples:
* estimate size of the network
* estimate the number of connected components
* is the network clustered?
* can you identify different patterns of connection?
* (FOAF) has the network a small-world structure?

== High-Level Tasks ==

High-Level tasks which are not a combination of lower level tasks.

* When we compare two or more food webs, we can ask the following questions: What do they have in common? What are the differences among those food webs? Is there any missing or conflicting information?
* Due to errors in the data, several nodes may represent the same entity. For example, the co-authorship graphs often have duplicate author nodes. One important task is to identify whether two or more nodes represent the same person.
* How has the graph changed over time?

== Other tasks ==

There seems to be a set of tasks in the world that match very few of these, but show up often. I welcome others' ideas of how to categorize them:

"what is the general structure of this graph?"
http://www.networkweaving.com/blog/2006/09/nola-networks.html

"what is the distribution of vertex degree in this graph?" (That is, "how are well-linked nodes different from under-linked nodes?")
http://research.microsoft.com/research/pubs/view.aspx?type=Publication&id=1601

"how many As are linked to Bs? How many As link to other As?"
http://www.crookedtimber.org/2005/05/25/cross-ideological-conversations-among-bloggers/

I see things like this so often that they seem to dominate my understanding of how people think of graphing today. (Wattenberg obviously saw the same; his paper from CHI ’06 would do poorly on almost all of the tasks you discuss, but is incredibly effective for questions like “is Sales talking to Engineering?”)

== References ==

* [Amar et al. 2005] Amar, R., Eagan, J., and Stasko, J. Low-Level Components of Analytic Activity in Information Visualization, Proceedings of the Symposium on Information Visualization (InfoVis ’05), pp. 111-117, 2005.

* [Lee et al. 2006] Lee, B., Plaisant, C., Parr, CS., Fekete, JD. and Henry, N. Task Taxonomy for Graph Visualization, In BEyond time and errors: novel evaLuation methods for Information Visualization (BELIV'06), Venice, Italy, May 2006, to be published.

Social Network Generation

2007-08-16T07:48:04Z

Markus: Reverted edit of WjcNqk, changed back to last version by Markus

This wiki page is under construction...

Research work and images have been realised by Nathalie Henry and Jean-Daniel Fekete, using MatrixExplorer, built with the Infovis Toolkit.

== Social Network Characterization ==

Social networks involve persons or groups called actors and relationship between them, with a lot of variety in the kind of actors and relationships. As described in Wasserman and Faust, actors can be people, subgroups, organizations or collectivities; relations may be friendship (relationships), interactions, communications, transactions, movement or kinship. However, the nature of actors and relations does not really matter: we focus on their structure. We can classify the social networks studied in the literature in three categories:
* Tree-like are trees with additional links forming cycles with a specified probability. This category includes genealogy data and very sparse graphs such as Sexually-Transmitted Disease (STD) transmission patterns. We call them “almost trees” because they have are mostly acyclic and nodes have very few parents.
* Almost complete graphs are complete graphs with missing relations. For example, data about trade between countries, cities or companies are almost complete graphs. They are interesting to study as valued graphs; since they usually carry values on their edges.
* Small-world networks (also scale-free or power-law degree-distribution networks) have been studied intensely since they were first described in Watts and Strogatz. They defined them as graphs with three properties: power-law degree distribution, high clustering coefficient and small average shortest path. They are locally dense (sparse with dense sub-graphs).

Three methods exist to select datasets for assessing the quality of analysis systems in the context of social networks: selecting one or two real datasets hoping they are representative, selecting several datasets or generating random datasets with well-known characteristics shared by social networks. With this last method, one should generate datasets with a controlled set of properties and evaluate the systems knowing the properties in advance. It should then eliminate biases linked to a particular dataset and eases the replication of experiments. Unfortunately, while generating tree-like and almost-complete graphs is relatively straightforward, generating graphs with a small-world network structure is still a research topic for computer scientists and physicists. This page shows the results of popular and available network generators. In light of the real social networks we present in the [[#Real Social Networks]], we consider them unsuitable for evaluations since users can easily notice their artifical nature.

== Issues on Social Network Generation for Evaluating Visualizations ==

Watts and Strogatz first described in (Watts, D. J. and S. H. Strogatz (1998). "Collective dynamics of 'small-world' networks." Nature 393: 440 - 442) the concept of small-world networks. They formalized these networks as graphs with three properties: power-law degree distribution, high clustering coefficient and small average shortest path. In the same paper they propose a basic model fitting these properties consisting in a grid (fixed local neighborhood) with additional links simulating some unexpected relations support to the six degrees of separation discovered by Milgram (Milgram, S. (1967). "The small world problem." Psychology Today: 60-67). Barabási and Albert proposed an incremental model to improve it (Barabási, A.-L. and R. Albert (1999). "Emergence of Scaling in Random Networks." Science 286(5439): 509 - 512.
). Since Watts and Strogatz’ model, several have been proposed each generating networks with one or two of the described properties (power-law) but none combine the three of them.

Here are some results of available generators present in the JUNG package. Let's note that for each network generated we only keep the biggest component. Generators present in Pajek[http://vlado.fmf.uni-lj.si/pub/networks/pajek/] and Geomi[http://www.cs.usyd.edu.au/~visual/valacon/geomi/] are incremental scale-free networks generators such as the Barabasi and Albert model.

=== About datasets and representations ===

* All datasets are downloadable in GraphMl format.
* Node-Link diagrams are ordered with the linLog algorithm of Andreas Noack [Graph Drawing 2005] (with edge-repulsion coefficient of 2.5f).
* Matrices are shown both with the initial order (middle image) and reordered with the TSP-Based algorithm (right image) described by Henry and Fekete [Infovis 2006].

=== Small-World Generators ===

WattsBetaSmallWorldGenerator

Parameters:
'''numVertices''' (the number of nodes in the ring lattice), '''beta''' (the probability of an edge being rewired randomly; the proportion of randomly rewired edges in a graph) and '''degree'''( the number of edges connected to each vertex; the local neighborhood size). Degree must be even.

{| border="1"
| Parameters and Resulting Graph characteristics
|-
| graphs || W1 ||W2|| W3 || W4 ||W5 ||W6||W7||W8||W9||W10||W11||W12
|- style="background:lightgrey;"
|'''numVertices'''||47||47||47||47||47||47||47||47||47||47||47||'''94'''
|- style="background:lightgrey;"
|'''beta'''||'''0.1'''||'''0.3'''||'''0.5'''||'''0.7'''||'''0.9'''||0.3||0.3||0.3||0.3||'''0.7'''||'''0.1'''||0.1
|- style="background:lightgrey;"
|'''degree'''||6||6||6||6||6||'''2'''||'''4'''||'''8'''||'''10'''||'''4'''||'''8'''||8
|-
|numVertices||47||47||47||47||47||47||47||47||47||47||47||94
|-
|numEdges||282||282||282||282||282||94||188||376||470||188||376||752
|-
|components||1||1||1||1||1||2||1||1||1||1||1||1
|- style="background:#FFFFCC"
|density||0.36||0.36||0.36||0.36||0.36||0.21||0.29||0.41||0.46||0.29||0.41||'''0.29'''
|-style="background:#FFFFCC"
|clusteringCoefficient||0.51||0.25||0.15||0.09||0.12||0.23||0.25||0.32||0.38||0.07||0.53||'''0.52'''
|-
|diameter||6||4||4||4||4||-||6||4||3||5||5||6
|-
|averageShortestDistance||2.97||2.4||2.32||2.3||2.29||-||3.24||2.15||1.98||2.83||2.56||3.15
|-
|minDegree||5||4||4||3||4||1||2||5||8||2||7||6
|-
|maxDegree||8||9||9||9||9||4||6||10||13||8||10||10
|}

W1 [http://insitu.lri.fr/~nhenry/socnets/wsmallworld/wSmallWorld_47_0.1_6.xml SmallWorld_47_0.1_6.xml]

[[image:wSmallWorld_47_0.1_6.JPG|150px]]
[[image:wSmallWorldMInit_47_0.1_6.PNG|165px]]
[[image:wSmallWorldM_47_0.1_6.JPG|165px]]

W2 [http://insitu.lri.fr/~nhenry/socnets/wsmallworld/wSmallWorld_47_0.3_6.xml SmallWorld_47_0.3_6.xml]

[[image:wSmallWorld_47_0.3_6.JPG|150px]]
[[image:wSmallWorldMInit_47_0.3_6.PNG|165px]]
[[image:wSmallWorldM_47_0.3_6.PNG|165px]]

W3 [http://insitu.lri.fr/~nhenry/socnets/wsmallworld/wSmallWorld_47_0.5_6.xml SmallWorld_47_0.5_6.xml]

[[image:wSmallWorld_47_0.5_6.JPG|150px]]
[[image:wSmallWorldMInit_47_0.5_6.PNG|165px]]
[[image:wSmallWorldM_47_0.5_6.PNG|165px]]

W4 [http://insitu.lri.fr/~nhenry/socnets/wsmallworld/wSmallWorld_47_0.7_6.xml SmallWorld_47_0.7_6.xml]

[[image:wSmallWorld_47_0.7_6.JPG|150px]]
[[image:wSmallWorldMInit_47_0.7_6.PNG|165px]]
[[image:wSmallWorldM_47_0.7_6.PNG|165px]]

W5 [http://insitu.lri.fr/~nhenry/socnets/wsmallworld/wSmallWorld_47_0.9_6.xml SmallWorld_47_0.9_6.xml]

[[image:wSmallWorld_47_0.9_6.JPG|150px]]
[[image:WSmallWorldMInit_47_0.9_6.PNG|165px]]
[[image:WSmallWorldM_47_0.9_6.PNG|165px]]

W6 [http://insitu.lri.fr/~nhenry/socnets/wsmallworld/wSmallWorld_47_0.3_2.xml SmallWorld_47_0.3_2.xml]

[[image:wSmallWorld_47_0.3_2.JPG|150px]]
[[image:WSmallWorldMInit_47_0.3_2.PNG|165px]]
[[image:WSmallWorldM_47_0.3_2.PNG|165px]]

W7 [http://insitu.lri.fr/~nhenry/socnets/wsmallworld/wSmallWorld_47_0.3_4.xml SmallWorld_47_0.3_4.xml]

[[image:wSmallWorld_47_0.3_4.JPG|150px]]
[[image:WSmallWorldMInit_47_0.3_4.PNG|165px]]
[[image:WSmallWorldM_47_0.3_4.PNG|165px]]

W8 [http://insitu.lri.fr/~nhenry/socnets/wsmallworld/wSmallWorld_47_0.3_8.xml SmallWorld_47_0.3_8.xml]

[[image:wSmallWorld_47_0.3_8.JPG|150px]]
[[image:WSmallWorldMInit_47_0.3_8.PNG|165px]]
[[image:WSmallWorldM_47_0.3_8.PNG|165px]]

W9 [http://insitu.lri.fr/~nhenry/socnets/wsmallworld/wSmallWorld_47_0.3_10.xml SmallWorld_47_0.3_10.xml]

[[image:wSmallWorld_47_0.3_10.JPG|150px]]
[[image:WSmallWorldMInit_47_0.3_10.PNG|165px]]
[[image:WSmallWorldM_47_0.3_10.PNG|165px]]

W10 [http://insitu.lri.fr/~nhenry/socnets/wsmallworld/wSmallWorld_47_0.7_4.xml SmallWorld_47_0.7_4.xml]

[[image:wSmallWorld_47_0.7_4.JPG|150px]]
[[image:wSmallWorldMInit_47_0.7_4.PNG|165px]]
[[image:wSmallWorldM_47_0.7_4.PNG|165px]]

W11 [http://insitu.lri.fr/~nhenry/socnets/wsmallworld/wSmallWorld_47_0.1_8.xml SmallWorld_47_0.1_8.xml]

[[image:wSmallWorld_47_0.1_8.JPG|150px]]
[[image:wSmallWorldMInit_47_0.1_8.PNG|165px]]
[[image:wSmallWorldM_47_0.1_8.PNG|165px]]

W12 [http://insitu.lri.fr/~nhenry/socnets/wsmallworld/wSmallWorld_94_0.1_8.xml SmallWorld_94_0.1_8.xml]

[[image:wSmallWorld_94_0.1_8.JPG|150px]]
[[image:wSmallWorldMInit_94_0.1_8.PNG|165px]]
[[image:wSmallWorldM_94_0.1_8.PNG|165px]]

KleinbergSmallWorldGenerator

Parameters:'''latticeSize''' (the lattice size (length of row or column dimension)) and '''clusteringExponent''' (the clustering exponent parameter).

{| border="1"
| Parameters and Resulting Graph characteristics
|-
| graphs || W1 ||W2|| W3 || W4 ||W5 ||W6||W7||W8||W9||W10||W11
|- style="background:lightgrey;"
|'''latticeSize''' || 7 || 7 || 7 || 7 || 7 || 7 || 7 || '''10''' || '''10''' || '''10''' || '''10'''
|- style="background:lightgrey;"
|'''clusteringExponent''' ||'''0.1''' || '''0.5''' || '''1'''|| '''2''' || '''2.5''' || '''4''' || '''8''' || '''2''' || '''4''' || '''8''' || '''12'''
|-
|numVertices || 49 || 49 || 49 || 49 || 49 || 49 || 49 || 100 || 100 || 100 || 100
|-
|numEdges || 490 || 490 || 490 || 490 || 490 || 490 || 490 || 1000 || 1000 || 1000 || 1000
|-
|components || 1 || 1 || 1 || 1 || 1 || 1 || 1 || 1 || 1 || 1 || 1
|- style="background:#FFFFCC"
|density || 0.45 || 0.45 || 0.45 || 0.45 || 0.45 || 0.45 || 0.45 || 0.32 || 0.32 || 0.32 || 0.32
|-style="background:#FFFFCC"
|clusteringCoefficient || 0.08 || 0.09 || 0.14 || 0.19 || 0.19 || 0.26 || 0.32 || 0.18 || 0.23 || 0.32 || 0.33
|-
|diameter || 4 || 4 || 4 || 4 || 4 || 5 || 5 || 5 || 6 || 7 || 7
|-
|averageShortestDistance || 2.38 || 2.36 || 2.37 || 2.44 || 2.48 || 2.54 || 2.73 || 3.1 || 3.57 || 3.65 || 3.68
|-
|minDegree || 9 || 9 || 9 || 9 || 9 || 9 || 9 || 9 || 9 || 9 || 9
|-
|maxDegree || 14 || 12 || 13 || 12 || 12 || 13 || 12 || 13 || 13 || 14 || 12
|}

W1 [http://insitu.lri.fr/~nhenry/socnets/ksmallworld/kSmallWorld_49_0.1.xml SmallWorld_49_0.1.xml]

[[image:kSmallWorld_49_0.1.PNG|150px]]
[[image:kSmallWorldMInit_49_0.1.PNG|165px]]
[[image:kSmallWorldM_49_0.1.PNG|165px]]

W2 [http://insitu.lri.fr/~nhenry/socnets/ksmallworld/kSmallWorld_49_0.5.xml SmallWorld_49_0.5.xml]

[[image:kSmallWorld_49_0.5.PNG|150px]]
[[image:kSmallWorldMInit_49_0.5.PNG|165px]]
[[image:kSmallWorldM_49_0.5.PNG|165px]]

W3 [http://insitu.lri.fr/~nhenry/socnets/ksmallworld/kSmallWorld_49_1.0.xml SmallWorld_49_1.0.xml]

[[image:kSmallWorld_49_1.0.PNG|150px]]
[[image:kSmallWorldMInit_49_1.0.PNG|165px]]
[[image:kSmallWorldM_49_1.0.PNG|165px]]

W4 [http://insitu.lri.fr/~nhenry/socnets/ksmallworld/kSmallWorld_49_2.0.xml SmallWorld_49_2.0.xml]

[[image:kSmallWorld_49_2.0.PNG|150px]]
[[image:kSmallWorldMInit_49_2.0.PNG|165px]]
[[image:kSmallWorldM_49_2.0.PNG|165px]]

W5 [http://insitu.lri.fr/~nhenry/socnets/ksmallworld/kSmallWorld_49_2.5.xml SmallWorld_49_2.5.xml]

[[image:kSmallWorld_49_2.5.PNG|150px]]
[[image:kSmallWorldMInit_49_2.5.PNG|165px]]
[[image:kSmallWorldM_49_2.5.PNG|165px]]

W6 [http://insitu.lri.fr/~nhenry/socnets/ksmallworld/kSmallWorld_49_4.0.xml SmallWorld_49_4.0.xml]

[[image:kSmallWorld_49_4.0.PNG|150px]]
[[image:kSmallWorldMInit_49_4.0.PNG|165px]]
[[image:kSmallWorldM_49_4.0.PNG|165px]]

W7 [http://insitu.lri.fr/~nhenry/socnets/ksmallworld/kSmallWorld_49_8.0.xml SmallWorld_49_8.0.xml]

[[image:kSmallWorld_49_8.0.PNG|150px]]
[[image:kSmallWorldMInit_49_8.0.PNG|165px]]
[[image:kSmallWorldM_49_8.0.PNG|165px]]

W8 [http://insitu.lri.fr/~nhenry/socnets/ksmallworld/kSmallWorld_100_2.0.xml SmallWorld_100_2.0.xml]

[[image:kSmallWorld_100_2.0.PNG|150px]]
[[image:kSmallWorldMInit_100_2.0.PNG|165px]]
[[image:kSmallWorldM_100_2.0.PNG|165px]]

W9 [http://insitu.lri.fr/~nhenry/socnets/ksmallworld/kSmallWorld_100_4.0.xml SmallWorld_100_4.0.xml]

[[image:kSmallWorld_100_4.0.PNG|150px]]
[[image:kSmallWorldMInit_100_4.0.PNG|165px]]
[[image:kSmallWorldM_100_4.0.PNG|165px]]

W10 [http://insitu.lri.fr/~nhenry/socnets/ksmallworld/kSmallWorld_100_8.0.xml SmallWorld_100_8.0.xml]

[[image:kSmallWorld_100_8.0.PNG|150px]]
[[image:kSmallWorldMInit_100_8.0.PNG|165px]]
[[image:kSmallWorldM_100_8.0.PNG|165px]]

W11 [http://insitu.lri.fr/~nhenry/socnets/ksmallworld/kSmallWorld_100_12.0.xml SmallWorld_100_12.0.xml]

[[image:kSmallWorld_100_12.0.PNG|150px]]
[[image:kSmallWorldMInit_100_12.0.PNG|165px]]
[[image:kSmallWorldM_100_12.0.PNG|165px]]

=== Scale-Free Networks Generator ===

BarabasiAlbertGenerator

Parameters: '''init_vertices''' (number of vertices that the graph should start with), '''numEdgesToAttach''' (the number of edges that should be attached from the new vertex to pre-existing vertices at each time step) and '''numSteps''' (number of time steps). init_vertices must be superior or equal to numEdgesToAttach.

{| border="1"
| Parameters and Resulting Graph characteristics
|-
| graphs || W1 ||W2|| W3 || W4 ||W5 ||W6||W7||W8
|- style="background:lightgrey;"
|'''init_vertices'''||4||4||4||4||2||2||2||4
|- style="background:lightgrey;"
|'''numEdgesToAttach'''||2||2||2||1||1||1||2||4
|- style="background:lightgrey;"
|'''numSteps'''||10||50||100|| 100||100||50||50||50
|-
|numVertices||14||53||104|| 80||76||51||52||54
|-
|numEdges||40||200||400||158||150||100||200||400
|-
|components||1||1||1||1||1||1||1||1
|- style="background:#FFFFCC"
|density||0.45||0.27||0.19||0.16||0.16||0.2||0.27||0.37
|-style="background:#FFFFCC"
|clusteringCoefficient||0.15||0.2||0.07||0.51||0.51||0.66||0.16||0.23
|-
|diameter||4||6||6||11||14||8||5||4
|-
|averageShortestDistance||2.24||2.81||3.18||5.26||5.7||3.74||2.8||2.15
|-
|minDegree||2||1||2||1||1||1||2||4
|-
|maxDegree||5||16||19||8||12||16||17||26
|}

W1 [http://insitu.lri.fr/~nhenry/socnets/bascalefree/baScaleFree_4_2_10.xml ScaleFree_4_2_10.xml]

[[image:baScaleFree_4_2_10.PNG|150px]]
[[image:baScaleFreeMInit_4_2_10.PNG|165px]]
[[image:baScaleFreeM_4_2_10.PNG|165px]]

W2 [http://insitu.lri.fr/~nhenry/socnets/bascalefree/baScaleFree_4_2_50.xml ScaleFree_4_2_50.xml]

[[image:baScaleFree_4_2_50.PNG|150px]]
[[image:baScaleFreeMInit_4_2_50.PNG|165px]]
[[image:baScaleFreeM_4_2_50.PNG|165px]]

W3 [http://insitu.lri.fr/~nhenry/socnets/bascalefree/baScaleFree_4_2_100.xml ScaleFree_4_2_100.xml]

[[image:baScaleFree_4_2_100.PNG|150px]]
[[image:baScaleFreeMInit_4_2_100.PNG|165px]]
[[image:baScaleFreeM_4_2_100.PNG|165px]]

W4 [http://insitu.lri.fr/~nhenry/socnets/bascalefree/baScaleFree_4_1_100.xml ScaleFree_4_1_100.xml]

[[image:baScaleFree_4_1_100.PNG|150px]]
[[image:baScaleFreeMInit_4_1_100.PNG|165px]]
[[image:baScaleFreeM_4_1_100.PNG|165px]]

W5 [http://insitu.lri.fr/~nhenry/socnets/bascalefree/baScaleFree_2_1_100.xml ScaleFree_2_1_100.xml]

[[image:baScaleFree_2_1_100.PNG|150px]]
[[image:baScaleFreeMInit_2_1_100.PNG|165px]]
[[image:baScaleFreeM_2_1_100.PNG|165px]]

W6 [http://insitu.lri.fr/~nhenry/socnets/bascalefree/baScaleFree_2_1_50.xml ScaleFree_2_1_50.xml]

[[image:baScaleFree_2_1_50.PNG|150px]]
[[image:baScaleFreeMInit_2_1_50.PNG|165px]]
[[image:baScaleFreeM_2_1_50.PNG|165px]]

W7 [http://insitu.lri.fr/~nhenry/socnets/bascalefree/baScaleFree_2_2_50.xml ScaleFree_2_2_50.xml]

[[image:baScaleFree_2_2_50.PNG|150px]]
[[image:baScaleFreeMInit_2_2_50.PNG|165px]]
[[image:baScaleFreeM_2_2_50.PNG|165px]]

W8 [http://insitu.lri.fr/~nhenry/socnets/bascalefree/baScaleFree_4_4_50.xml ScaleFree_4_4_50.xml]

[[image:baScaleFree_4_4_50.PNG|150px]]
[[image:baScaleFreeMInit_4_4_50.PNG|165px]]
[[image:baScaleFreeM_4_4_50.PNG|165px]]

EppsteinPowerLawGenerator

Parameters: '''numVertices''' (the number of vertices for the generated graph), '''numEdges''' (the number of edges the generated graph will have, should be Theta(numVertices)) and '''r''' (the model parameter).

== Real Social Networks ==

Here is a panel of undirected networks issued from scientific articles, benchmarks or contests. Social network visualization or analysis tools provide also some real datasets: Pajek [http://vlado.fmf.uni-lj.si/pub/networks/data/] and UCINet [http://vlado.fmf.uni-lj.si/pub/networks/data/UciNet/UciData.htm].

=== Small-World ===

{| border="1"
| Parameters and Resulting Graph characteristics for Co-Authoring Networks
|Name ||Team Collaboration (with external collaborators)||Infovis component 1 ||Infovis component 2 || Infovis component 3||Infovis component 4
|-style="background:lightgrey"
|'''Source'''||Collected ||Contest||Contest||Contest||Contest
|-
|numNodes||146||135||48||47||32
|-
|numEdges||540||321||91||114||109
|-
|components||1||1||1||1||1
|-style="background:#FFFFCC"
|density||0.16||0.13||0.2||0.23||0.33
|-style="background:#FFFFCC"
|clusteringCoefficient||0.91||0.82||0.79||0.83||0.81
|-
|diameter||4||11||7||10||6
|-
|averageShortestDistance||2.65||4.4||3.71||3.84||2.6
|-
|minDegree||1||1||1||1||1
|-
|maxDegree||57||22||11||15||15
|}

TeamCollaborationExternal [http://insitu.lri.fr/~nhenry/socnets/realsmallworld/teamCollaborationExternalAnonym.xml TeamCollaborationExternal.xml]

[[image: teamCollaborationExternal.PNG|150px]]
[[image: teamCollaborationExternalMInit.PNG|165px]]
[[image: teamCollaborationExternalM.PNG|165px]]

Infovis Component 1 [http://insitu.lri.fr/~nhenry/socnets/realsmallworld/ivComp1.xml ivComp1.xml]

[[image: ivComp1.PNG|150px]]
[[image: ivComp1MInit.PNG|165px]]
[[image: ivComp1M.PNG|165px]]

Infovis Component 2 [http://insitu.lri.fr/~nhenry/socnets/realsmallworld/ivComp2.xml ivComp2.xml]

[[image: ivComp2.PNG|150px]]
[[image: ivComp2MInit.PNG|165px]]
[[image: ivComp2M.PNG|165px]]

Infovis Component 3 [http://insitu.lri.fr/~nhenry/socnets/realsmallworld/ivComp3.xml ivComp3.xml]

[[image: ivComp3.PNG|150px]]
[[image: ivComp3MInit.PNG|165px]]
[[image: ivComp3M.PNG|165px]]

Infovis Component 4 [http://insitu.lri.fr/~nhenry/socnets/realsmallworld/ivComp4.xml ivComp4.xml]

[[image: ivComp4.PNG|150px]]
[[image: ivComp4MInit.PNG|165px]]
[[image: ivComp4M.PNG|165px]]

=== Tree-like ===

{| border="1"
| Parameters and Resulting Graph characteristics for Genealogy and Virus Transmission
|Name ||genealogy||MSTTransmission1||MSTTransmission2||HIVTransmission
|-style="background:lightgrey"
|'''Source'''||Pajek||Article [http://sextrans.bmjjournals.com/cgi/content/abstract/80/4/280]||Article[http://sextrans.bmjjournals.com/cgi/content/abstract/80/4/280]||Article [http://sti.bmjjournals.com/cgi/content/abstract/78/suppl_1/i159]
|-
|numVertices||242||38||84||243
|-
|numEdges||510||78||182||514
|-
|components||1||1||1||1
|-style="background:#FFFFCC"
|density||0.09||0.23||0.16||0.09
|-style="background:#FFFFCC"
|clusteringCoefficient||0.66||0.53||0.52||0.65
|-
|diameter||11||10||9||23
|-
|averageShortestDistance||5.78||4.42||4.31||8.27
|-
|minDegree||1||1||1||1
|-
|maxDegree||14||7||17||20
|}

Gondola Genealogy [http://insitu.lri.fr/~nhenry/socnets/realtreelike/GondolaGen.xml GondolaGen.xml]

[[image: gondolaGen.PNG|150px]]
[[image: gondolaGenMInit.PNG|165px]]
[[image: gondolaGenM.PNG|165px]]

MSTTransmission 1 [http://insitu.lri.fr/~nhenry/socnets/realtreelike/Mst1.xml Mst1.xml]

[[image: mst1.PNG|150px]]
[[image: mst1MInit.PNG|165px]]
[[image: mst1M.PNG|165px]]

MSTTransmission 2 [http://insitu.lri.fr/~nhenry/socnets/realtreelike/Mst2.xml Mst2.xml]

[[image: mst2.PNG|150px]]
[[image: mst2MInit.PNG|165px]]
[[image: mst2M.PNG|165px]]

HIV Transmission [http://insitu.lri.fr/~nhenry/socnets/realtreelike/Hiv.xml Hiv.xml]

[[image: hiv.PNG|150px]]
[[image: hivMInit.PNG|165px]]
[[image: hivM.PNG|165px]]

=== Almost Complete Graphs ===

{| border="1"
| Parameters and Resulting Graph characteristics for Email Communication within a research lab.
|-
|Name||emailDay per person||emailWeek per person||emailMonth per person||emailYear per person||emailDay per team||emailWeek per team||emailMonth per team||emailYear per team
|-style="background:lightgrey"
|'''Source'''||Collected||Collected||Collected||Collected||Collected||Collected||Collected||Collected
|-
|numVertices||134||200||242||447||30||33||35||42
|-
|numEdges||442||1676||3514||11462||183||410||564||980
|-
|components||1||1||1||1||1||1||1||1
|-style="background:#FFFFCC"
|density||0.16||0.2||0.24||0.24||0.45||0.61||0.68||0.75
|-style="background:#FFFFCC"
|clusteringCoefficient||0.52||0.55||0.62||0.71||0.62||0.78||0.83||0.84
|-
|diameter||9||7||6||6||5||3||3||3
|-
|averageShortestDistance||4.29||2.92||2.52||2.42||2.17||1.71||1.57||1.45
|-
|minDegree||1||1||1||1||1||1||1||3
|-
|maxDegree||15||51||86||195||16||26||34||40
|}

Email exchange per person during a day [http://insitu.lri.fr/~nhenry/socnets/realalmostcomplete/emailDay.xml emailDay.xml]

[[image: emailDay.PNG|150px]]
[[image: emailDayMInit.PNG|165px]]
[[image: emailDayM.PNG|165px]]

Email exchange per person during a week [http://insitu.lri.fr/~nhenry/socnets/realalmostcomplete/emailWeek.xml emailWeek.xml]

[[image: emailWeek.PNG|150px]]
[[image: emailWeekMInit.PNG|165px]]
[[image: emailWeekM.PNG|165px]]

Email exchange per person during a month [http://insitu.lri.fr/~nhenry/socnets/realalmostcomplete/emailMonth.xml emailMonth.xml]

[[image: emailMonth.PNG|150px]]
[[image: emailMonthMInit.PNG|165px]]
[[image: emailMonthM.PNG|165px]]

Email exchange per person during a year [http://insitu.lri.fr/~nhenry/socnets/realalmostcomplete/emailYear.xml emailYear.xml]

[[image: emailYear.PNG|150px]]
[[image: emailYearMInit.PNG|165px]]
[[image: emailYearM.PNG|165px]]

Email exchange per research group during a day [http://insitu.lri.fr/~nhenry/socnets/realalmostcomplete/emailGDay.xml emailGDay.xml]

[[image: emailGDay.PNG|150px]]
[[image: emailGDayMInit.PNG|165px]]
[[image: emailGDayM.PNG|165px]]

<blockquote>
Number of email coded with link width in the nodelink, edge color in the matrix
</blockquote>

<blockquote>
[[image: emailGDayS.PNG|150px]]
[[image: emailGDayMC.PNG|165px]]
</blockquote>

Email exchange per research group during a week
[http://insitu.lri.fr/~nhenry/socnets/realalmostcomplete/emailGWeek.xml emailGWeek.xml]

[[image: emailGWeek.PNG|150px]]
[[image: emailGWeekMInit.PNG|165px]]
[[image: emailGWeekM.PNG|165px]]

<blockquote>
Number of email coded with link width in the nodelink, edge color in the matrix
</blockquote>

<blockquote>
[[image: emailGWeekS.PNG|150px]]
[[image: emailGWeekMC.PNG|165px]]
</blockquote>

Email exchange per research group during a month
[http://insitu.lri.fr/~nhenry/socnets/realalmostcomplete/emailGMonth.xml emailGMonth.xml]

[[image: emailGMonth.PNG|150px]]
[[image: emailGMonthMInit.PNG|165px]]
[[image: emailGMonthM.PNG|165px]]

<blockquote>
Number of email coded with link width in the nodelink, edge color in the matrix
</blockquote>

<blockquote>
[[image: emailGMonthS.PNG|150px]]
[[image: emailGMonthMC.PNG|150px]]
</blockquote>

Email exchange per research group during a year
[http://insitu.lri.fr/~nhenry/socnets/realalmostcomplete/emailGYear.xml emailGYear.xml]

[[image: emailGYear.PNG|150px]]
[[image: emailGYearMInit.PNG|165px]]
[[image: emailGYearM.PNG|165px]]

<blockquote>
Number of email coded with link width in the nodelink, edge color in the matrix
</blockquote>

<blockquote>
[[image: emailGYearS.PNG|150px]]
[[image: emailGYearMC.PNG|165px]]
</blockquote>
[[Category:Datasets]]

Stardinates

2007-08-16T07:46:55Z

Markus: Reverted edit of Fi4W9p, changed back to last version by Iwolf

[[Image:Stardinates.jpg|250px|thumb|Stardinates]]
{{Quotation|The Stardinates are a novel interactive Information Visualization (InfoVis) technique which aims at visualizing highly structured data. They represent some Gestalt principles very well, especially the principles of Closure and ’Prägnanz’. As a consequence, Stardinates form very distinct and memorable patterns which make abstraction and aggregation much easier.|[Lanzenberger, 2003]}}

== References ==

*[Lanzenberger, 2003]: Lanzenberger, M., "The Stardinates - Visualizing Highly Structured Data", Proceedings of the Seventh International Conference on Information Visualization (IV'03), 2003.

[[Category: Techniques]]

2007-04-16: Historic Information Graphics literature review by Aaron Marcus

2007-07-23T03:04:30Z

Markus: Reverted edit of QvhCxc, changed back to last version by Markus

[[Marcus, Aaron|Aaron Marcus]], well-known for his works on Usability and Information Graphics, presents a very interesting historic literature review on Information Graphics in the Visual Business Intelligence Newsletter of [http://www.perceptualedge.com/ Perceptual Edge]. He also provides some not very well known books and articles which might turn out to be real jewels.

{{Quotation|What follows is an idiosyncratic, eclectic, abbreviated celebration of works published over the past 80 years on the topic of information graphics, or information visualization, comprising documents in my own library collected over the past 40 years.|[Marcus, 2007]}}

http://www.perceptualedge.com/articles/guests/Information%20Graphics.pdf

== References ==
[Marcus, 2007] Aaron Marcus, [http://www.perceptualedge.com/articles/guests/Information Graphics.pdf Information Graphics: A Celebration and Recollection], Visual Business Intelligence Newsletter, Perceptual Edge, Created at: February 14, 2007, Retrived at: April 16, 2007. http://www.perceptualedge.com/articles/guests/Information%20Graphics.pdf

[[Category:News]] [[Category:2007/04]]

Radial Hierarchical Visualization

2007-07-23T03:03:52Z

Markus: Reverted edit of Xm1H76, changed back to last version by Markus

== Authors ==
[[Keim, Daniel]]

[[Mansmann, Florian]]

[[Schneidewind, Jörn]]

Schreck, Tobias

== Short Description ==

{{Quotation|The Radial Traffic Analyzer display is perfectly suitable to show grouped information in the inner circles while presenting related detail information on the outer circles. It is complemented by appropriate interaction techniques like hints on mouse-over, drag & drop to adapt the order of the rings, filtering using clicks and details accessible via a popup menu.| [[Keim, Daniel]] et al., 2006}}

== Suitable Data Types ==
Suitable data types for this information visualization technique are Internet Protocol packets. 

== Figures ==

The Radial Traffic Analyzer visualizes network traffic using a radial hierarchical layout. The radial visualization was chosen to display data with the same level of importance. Users interpreting a left-to-right layout may assign more importance to an item on one side due to the cultural reading direction. In the default configuration, the Radial Traffic Analyzer uses four concentrical rings, each one representing an attribute of the transferred packets.

[[Image:Rta_small.jpg]]

The rings in this example show the following information, from the innermost to the outermost ring: 
1. Source IP adress 
2. Destination IP 
3. Source port number 
4. Destination port number. 
The share in total traffic determines the size of a single circle segment. To improve readability, entries with the same value (e.g., the same IP, or the same port number) always use the same colour. Popular port numbers appear in reserved, unique colours (e.g. green is always used for port 80 - HTTP), which are not used again to display something else. Traffic over secured channels is shown in brighter colours, whereas traffic over unsecured channels appears in darker colour.

Circle segments are sorted on a ring, and grouped by the attributes on the inner rings. The next figure shows the design rationale:

[[Image:Rta_sort.jpg]]

The Radial Traffic Analyzer allows a variety of user interaction. Entries and their associated traffic can be filtered by single-clicking a circle segment. The order of the rings can be adapted to the users' needs, as well as the number of the rings, or their attributes. For example, the Radial Traffic Analyzer can be configured to display security alerts generated by an intrusion detection system:

[[Image:Rta_sec.jpg]]

As seen in the figure above, the innermost circle can be used to limit the source of network traffic to one specified country. For this purpose, the Radial Traffic Analizer uses the [http://www.maxmind.com Maxmind’s GeoIP Database] to evaluate the geo-location information. Geographical information is arranged on a treemap using the HistoMap algorithm; each geographical unit is matched to a rectangle. The amount of traffic determines the rectangle size.

[[Image:Rta_country.jpg]]

== Evaluation ==
As per April 2007, there are no evaluations or reference implementations of the Radial Traffic Analyzer.

== References ==
[Keim, et. al. 2006] Daniel A. Keim, Florian Mansmann, Jörn Schneidewind, and Tobias Schreck: [http://infovis.uni-konstanz.de/members/schreck/tsprojects/papers/vast06.pdf "Monitoring Network Traffic with Radial Traffic Analyzer"], pages 123-128. IEEE Symposium on Visual Analytics Science and Technology 2006.

== Evaluation References ==
A formal user study is pending as per April 2007. However, previous evaluations have been conducted, e.g.:

*[Komlodi, et. al., 2005] Komlodi, A.; Rheingans, P.; Ayachit, U.; Goodall, J.R.; Joshi, A.; [http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1566119 "A User-centered Look at Glyph-based Security Visualization"], Visualization for Computer Security, IEEE Workshops on Publication Date: 26 Oct. 2005 On page(s): 3- 3

*[Stasko, et. al., 2000] Stasko, J.; Zhang, E.; [http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=885091 "Focus+context display and navigation techniques for enhancing radial, space-filling hierarchy visualizations"], Information Visualization, 2000. InfoVis 2000. IEEE Symposium on Publication Date: 2000 On page(s): 57-65

[[Category:Techniques]]
[[Category:Hierarchical Data]]

Talk:Stardinates

2007-07-23T00:30:46Z

Markus: spam

== Other category? ==

IMHO this page fits better into the "Techniques" category... ([[User:Iwolf]])

Category:Persons

2007-07-22T04:40:13Z

Markus: Reverted edit of DkeAkh, changed back to last version by Iwolf

[[Category:Top level]]

Talk:Stardinates

2007-07-22T04:39:04Z

Markus: Reverted edit of AanI8q, changed back to last version by Iwolf

== Other category? ==

IMHO this page fits better into the "Techniques" category... ([[User:Iwolf]])

Cone Trees

2007-07-20T09:30:12Z

Markus: Reverted edit of PsuPyq, changed back to last version by Iwolf

== Authors ==
*[[Robertson%2C_George|George Robertson]] 
*[[Mackinlay%2C_Jock_D.|Jock D. Mackinlay]] 
*[[Card%2C_Stuart|Stuart Card]] 

== Short description ==
{{Quotation|The task of managing and accessing large information spaces is a problem in large scale cognition. Emerging technologies for 3D visualization and interactive animation offer potential solutions to this problem, especially when the structure of the information can be visualized. We describe one of these Information Visualization techniques, called the Cone Tree, which is used for visualizing hierarchical information structures. The hierarchy is presented in 3D to maximize effective use of available screen space and enable visualization of the whole structure. Interactive animation is used to shift some of the user's cognitive load to the human perceptual system.| [George Robertson et al., 1991]}}

== Suitable Datatypes ==
Suitable Datatypes for this information visualization technique are hierarchical information structures. 

== Figures ==
Each tree node is the apex of a cone. The children of each node are drawn around the base of its associated cone. 
[[Image:cone1.GIF|200px]]
[[Image:cone2.GIF|200px]] 

== Examples and use cases ==
 
'''Layout of a simple Cone Tree''' [Robertson et al., 1991] 
[[Image:conetree.jpg|300px]] 

'''[http://www.sims.berkeley.edu/~hearst/papers/cac-sigir97/sigir97.html Cat-a-Cone: An Interactive Interface for Specifying Searches and Viewing Retrieval Results using a Large Category Hierarchy]''' [Hearst and Karadi, 1997] 

{{Quotation|The Cat-a-Cone is a novel user interface that integrates search and browsing of very large category hierarchies with their associated text collections. One key insight is the separation of the representation of category labels from documents, which allows the display of multiple categories per document. Another key component is the display of multiple selected categories simultaneously, complete with their hierarchical context. Shown are the results of a search on category labels Mastectomy and Radiation Therapy in conjunction with the text word "lumpectomy" on a breast cancer subset of the MEDLINE collection. A ConeTree displays category labels and a WebBook shows retrieval results. The lefthand page shows the title and the category labels associated with the document. The righthand page shows the abstract associated with the document. | [Hearst and Karadi, 1997]}} 
[[Image:catacone.jpg|300px]] 

'''[http://portal.acm.org/ft_gateway.cfm?id=223759&type=pdf&coll=GUIDE&dl=GUIDE&CFID=69627115&CFTOKEN=87748242 Lyberworld]''' [Hemmje, 1994] 
LyberWorld is a 3D visualization user interface supporting fulltext retrieval. 
[[Image:lybertree.gif|300px]] 

'''A file-system displayed as cone-tree'''
 [[Image:cones.gif|300px]] 

== Evaluation ==

* [[Cockburn%2C_Andrew|Andrew Cockburn]] 
* [[McKenzie%2C_Bruce|Bruce McKenzie]] 

== References ==
* [Robertson et al., 1991] [[Robertson%2C_George|George Robertson]], [[Mackinlay%2C_Jock_D.|Jock D. Mackinlay]], [[Card%2C_Stuart|Stuart Card]]. Cone Trees: Animated 3D Visualizations of Hierarchical Information. In ''Proceedings of the ACM CHI 91 Human Factors in Computing Systems Conference'', pages 189-- 194, April 28 - June 5, 1991, New Orleans, Louisiana, June 1991. Association for Computing Machinery 

== Evaluation References ==
* [Cockburn and McKenzie, 2000] Andrew Cockburn and Bruce McKenzie. An Evaluation of Cone Trees. In ''People and Computers XIV: British Computer Society Conference on Human Computer Interaction 2000'', p425--436. Springer-Verlag. 

* [Hearst and Karadi, 1997] Marti A. Hearst and Chandu Karadi. Cat-a-Cone: An Interactive Interface for Specifying Searches and Viewing Retrieval Results using a Large Category Hierarchy. In ''Proceedings of the Twentieth Annual International ACM SIGIR Conference'', pages 246-- 255, Philadelphia, PA, July 1997''
 

* [Hemmje, 1994] Matthias Hemmje, LyberWorld - A 3D Graphical User Interface for Fulltext Retrieval. Created at: May 7-11 1995. Retrieved at: April 13, 2006. [http://delivery.acm.org/10.1145/230000/223759/p417-hemmje.pdf?key1=223759&key2=5327835411&coll=GUIDE&dl=GUIDE&CFID=69627115&CFTOKEN=87748242 http://delivery.acm.org/...]
[[Category:Techniques]]
[[Category:Hierarchical Data]]

CourseVis

2007-07-17T13:40:18Z

Markus:

== Authors ==
*[[Mazza, Riccardo|Riccardo Mazza]]
*[[Dimitrova, Vania|Vania Dimitrova]]

== Short Description ==
{{Quotation|[...] a novel approach of using web log data generated by course management systems (CMS) to help instructors become aware of what is happening in distance learning classes. Specifically, techniques from Information Visualization are used to graphically render complex, multidimensional student tracking data collected by CMS. A system, called CourseVis, illustrates the proposed approach.| [Mazza and Dimitrova, 2004]}}

== Suitable Datatypes ==

This method can be used for tracking data generated by course management systems (CMS). Currently, the only supported CMS is [http://www.webct.com/ WebCT].

== Figures ==
 
'''Social Aspects:'''

This plot is a representation of the students' social activities (i.e. in a discussion board); It allows different views on aspects like date, student or topic. The size of the point describes the intensity and the color the activity a student did (red for start a topic, green for an answer and blue for reading).

[[Image:Sozal_Aspects.jpg|thumb|Social Aspects]]
 
'''Cognitive Aspects:'''

Its a representation for the cognitive level for each student. The representation is shown in a matrix. On the x-axis of the matrix are the students and on the y-axis the concept. The color of the points shows the performance.

[[Image:Coginitive_Aspects.jpg|thumb|Cognitive Aspects]]
 
'''Behavioural Aspects:'''

This graph is a representation of a students overall performance. It shows his/her accesses to the content, the global accesses, the progress with the course, messages at the discussion board and submissions to quizes and assignments.

[[Image:Behavioural_Aspects.jpg|thumb|Behavioural Aspects]]

== Evaluation ==
for [Mazza, 2006] see also [[Evaluating_Information_Visualization_Applications]]

== References ==
[Mazza and Dimitrova, 2004] Mazza, Ricardo; Dimitrova, Vania. [http://doi.acm.org/10.1145/1013367.1013393 Visualising student tracking data to support instructors in web-based distance education.] In ''Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters'', pp. 154-161. 2004.

== Evaluation References ==

[Mazza, 2006] Mazza, Ricardo. [http://doi.acm.org/10.1145/1168149.1168155 Evaluating information visualization applications with focus groups: the CourseVis experience.] In ''Proceedings of the 2006 AVI Workshop on Beyond Time and Errors: Novel Evaluation Methods For information Visualization'', pp. 1-6, 2006.

[[Category:Techniques]]

Mazza, Riccardo

2007-07-17T13:36:18Z

Markus: corrected cv url

[[Image:MazzaRiccardo.jpg]]
 
'''University of Lugano '''
Facluty of Communication Sciences 
Facluty of Informatics 

== Academic Grade ==

Ph.D in Communication Sciences, Universita della Sivzzera Italiana/ University of Lugano (Switzerland). Title of the dissertation „Using Information Visualisation to Facilitate Instructors in Web-based Distance Education“ Promoted in June 2004 
 
Graduated in Computer Science, University of Pisa, 1997 
 
Postgraduate specialisation in Information Technologies, Centro Cefriel - Milano, 1997 
 
[http://www.inf.unisi.ch/assistants/mazza/Web_area/Curriculum/curriculum_completo_en.pdf CV]

== Current Employment ==

''Universitá della Svizzera Italiana/ University of Lugano'', faculty of Communication Sciences: PostDoc researcher and teaching assistant 
''Universitá della Svizzera Italiana/ University of Lugano'', faculty of Informatics: PostDoc teaching assistant 
''Telos Internet Solutions SAGL'', founding partner

== Research Interest ==

Information Visualization 
Student modelling and external graphical representations in distance education

== Current Research Projects ==

[http://www.istituti.usilu.net/mazzar/Projects/Peng/index.html PENG - Personalized News Content Programming] 
[http://www.peng-project.org/ Official Peng Project Homepage] 
[http://www.istituti.usilu.net/mazzar/Projects/Viz_ch/index.html Viz.ch] 
[http://www.istituti.usilu.net/mazzar/Projects/PF/index.html The Fundamental Programming Modules]

== List of Publications ==

Because there are so many publications of Riccardo Mazza, you can find the full list [http://www.istituti.usilu.net/mazzar/papers.htm here.] 

== Awards ==

'''2004 - Best Alternate Tracks Paper Award''' 
Riccardo Mazza, Vania Dimitrova. Visualising Student Tracking Data to Support Instructors in
Web-Based Distance Education. In: 13th International World Wide Web Conference (WWW 2004) -
Educational Track. New York May 17-22. 
 
'''1998 - “1st Silicon-Cray Award”''' 
supported by Silicon Graphics Italia & Cray Research. Special mention for the work with title: "Un sistema per il riconoscimento di comandi gestuali". 

== External Links==

[http://www.inf.unisi.ch/assistants/mazza/ Personal Homepage] 
[http://www.unisi.ch/ University of Lugano] 
[http://www.di.unipi.it/ University of Pisa] 
[http://www.cefriel.it/ Centro Cefriel - Milano] 

[[Category:Persons]]

Evaluating Information Visualization Applications

2007-07-17T13:32:48Z

Markus: url internal

[[category: techniques]]

== Author ==

[[Mazza%2C_Riccardo|Riccardo Mazza]]

== Short Description ==

{{Quotation|Evaluation of user-centred tools often makes use of analytic and empirical techniques with the objective to investigate the usability, the functionality, and the effectiveness of an interactive system.| [Dix, Finley, Abowd, Beale, 1998]}} 

There are two different types of "Human Computer Interacion Evaluation Methods": 
*Analytic Methods
*Empiric Methods
**Quantitave Studies
**Qualitative Studies

== CourseVis ==

{{Quotation|[...] a novel approach of using web log data generated by course management systems (CMS) to help instructors become aware of what is happening in distance learning classes. Specifically, techniques from Information Visualization are used to graphically render complex, multidimensional student tracking data collected by CMS. A system, called CourseVis, illustrates the proposed approach.| [Mazza and Dimitrova, 2004]}}

== Figures ==

The following visualizations are used to represent the collected data from ''CourseVis'': 

*'''Access Plot:''' 
 The access plot shows the students' accesses to the course. It is an mixture of a scatterplot and a histogram. 
The scatterplot shows the data of students and of the course while the histogram shows the number of pages of the course accessed by all students on a special date. 

 [[Image:Accessesplot.JPG|center|400px|Access Plot]] 

*'''Discussion Plot:''' 
 This 3D scatterplot is about the disussions of the course. The figure shows time, topics and students. 
The sphere represents a new thread and the number of messages are encoded with the color and size of the sphere. 

 [[Image:Sozal_Aspects.jpg|center|300px|Discussion Plot]] 

*'''Behavioural Graph:''' 
 This graph represents the behaviours of a single student. 
It shows the student's access to the content pages, the global access to the course, a progress with the schedule of the course, messages and the submission of quizzes and assignments. 

 [[Image:Behavioural_Aspects.jpg|center|300px|Behavioural Graph]] 

== Evaluation Types ==

* Focus Group

* Controlled Experiment

* Semi-structured Interview

 {{Quotation|The focus group and the semi-structured interview aimed to assess the usefulness of the graphical representations generated in CourseVis, while the experimental study aimed at verifying the effectiveness and the efficiency of the representations.| [R. Mazza, 2006]}}

== Important Citation ==

{{Quotation| attitudes, feelings and beliefs ... are more likely to be revealed
via the social gathering and the interaction which being in a focus
group entails| [A. Gibbs, 1997]}}
 
{{Quotation| formulate and answer questions [users] didn’t anticipate having
before looking at the visualization| [C. Plaisant, 2004]}}

== References ==

*[[CourseVis|CourseVis]]
*[Mazza and Dimitrova, 2004] Mazza, Ricardo; Dimitrova, Vania. [http://doi.acm.org/10.1145/1013367.1013393 Visualising student tracking data to support instructors in web-based distance education.] In ''Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters'', pp. 154-161. 2004.
*[Mazza, 2006] Mazza, Ricardo. [http://doi.acm.org/10.1145/1168149.1168155 Evaluating information visualization applications with focus groups: the CourseVis experience.] In ''Proceedings of the 2006 AVI Workshop on Beyond Time and Errors: Novel Evaluation Methods For information Visualization'', pp. 1-6, 2006.

Sips, Mike

2007-07-17T13:31:13Z

Markus:

[[Category:Persons]]

[[Image:Mike_Sips.jpg|right|Mike Sips]]

== General Information ==

Stanford University 
Gates Computer Science 3B-362 
353 Serra Mall 
Stanford, CA 94305 

phone: (650) 723-7186 

email: [mailto:mspips@graphics.stanford.edu Mike Sips] 
web: [http://graphics.stanford.edu/~msips/ Mike Sips] 

== Professional Experience ==

'''Stanford University''' 
* Visiting Assistent Professor at [http://graphics.stanford.edu/ Graphics Lab]

'''Max-Planck Center for Visual Computing''' 
* Fellow and Group Leader at [http://www.mpi-inf.mpg.de/mpc/ Max-Planck Center]

'''University of Konstanz''' 
* Research and Teaching Assistent at Databases, [http://infovis.uni-konstanz.de/ Data Mining and Visualization Lab]

'''AT&T Labs Research''' 
* Internship at [http://www.research.att.com/areas/visualization/ Information Visualization Research]

== Research Interests ==

* Analytical Reasing
* Visual Analytics
* Visualization of large databases
* Geo-Analytics

== Papers ==

A list of publications of Mike Sips can be found at [http://www.informatik.uni-trier.de/~ley/db/indices/a-tree/s/Sips:Mike.html DBLP].

== Awards ==

* EADS Dornier Research Award 2006
* IEEE Symposium on Information Visualization (InfoVis) 2006, Baltimore, InfoVis Contest Overall Winner (together with Sebastian Kay Belle, Daniela Oelke, Sonja Oettl)

Schneidewind, Jörn

2007-07-17T13:29:47Z

Markus:

[[Category:Persons]]

[[Image:Joerg_Schneidewind.jpg|right|Jörn Schneidewind]]

== General Information ==

Computer Science Institute 
Uni Konstanz Fach D78 
Universitätsstr. 10 
D-78457 Konstanz, Germany 

phone: +49 7531 88-3077 
fax: +49 7531 88-3062 

email: [mailto:schneide@inf.uni-konstanz.de Jörn Schneidewind] 
web: [http://infovis.uni-konstanz.de/members/schneide Jörn Schneidewind Uni Konstanz]

== Curriculum Vitae ==

* 03/2003 - 10/2003: Internship at [http://www.hpl.hp.com/palo_alto/Hewlett Packard Research Labs, Palo Alto, California, US] .
* 11/2002 >: Research assistant, [http://dbvis.fmi.uni-konstanz.de/Database and Visualization Research Group, University of Konstanz].
* 11/2002: Diploma in Informatics at the [http://www.informatik.uni-halle.de/ Department of Mathematics and Computer Science], [http://www.uni-halle.de/ Martin-Luther-University Halle-Wittenberg].

== Teaching ==
'''WS06/07''' [http://infovis.uni-konstanz.de/index.php?region=teach&event=ws06&course=im Informationsmanagement]

'''SS06''' [http://dbvis.inf.uni-konstanz.de/~bustos/sva_ss06/index.php Visual Analytics], [http://dbvis.inf.uni-konstanz.de/lehre/ss06/infovis/index.php Information Visualization I]

'''WS05/06''' [http://dbvis.inf.uni-konstanz.de/~schneide/seminar-ws2005/ Visuelle Datenexploration], [http://dbvis.inf.uni-konstanz.de/~mansmann/ws05/im/index.php Informationsmanagement]

'''SS05''' [http://dbvis.inf.uni-konstanz.de/lehre/ss06/infovis/index.php Information Visualization I]

'''WS04/05''' [http://infovis.uni-konstanz.de/index.php?region=teach&event=ws06&course=im Informationsmanagement]

'''WS03/04''' [http://www.inf.uni-konstanz.de/dbis/teaching/ws0304/computing-systems/computing-systems.html Rechnersysteme]

'''SS04''' [http://dbvis.inf.uni-konstanz.de/~schneide/ss04/dm/index.php Data Mining]

'''SS03''' [http://infovis.uni-konstanz.de/~schneide/sem_ss03/index.html Data Mining und Visualisierung]

'''WS02/03''' [http://infovis.uni-konstanz.de/lehre/ws02/ra Rechnersysteme]

== Research Interests ==

* Data Mining and Knowledge Discovery
* Information Visualization - Visualization of Large Databases (see also PaperFinder Project)
* Similarity Search in Spatial Databases.
* High-Dimensional Indexing

== Selected Publications ==

* [http://infovis.uni-konstanz.de/index.php?lang=de&region=publications&name=schneide&sort=topic#Data%20Mining%20and%20Knowledge%20Discovery Data Mining and Knowledge Discovery]
* [http://infovis.uni-konstanz.de/index.php?lang=de&region=publications&name=schneide&sort=topic#Graphical%20User%20Interfaces%20for%20Databases Graphical User Interfaces for Databases]
* [http://infovis.uni-konstanz.de/index.php?lang=de&region=publications&name=schneide&sort=topic#Information%20Visualization%20-%20Visualization%20of%20Large%20Databases Information Visualization - Visualization of Large Databases]
* [http://infovis.uni-konstanz.de/index.php?lang=de&region=publications&name=schneide&sort=topic#Pattern-%20and%20DataBase%20Management%20Systems Pattern- and DataBase Management Systems]
* [http://infovis.uni-konstanz.de/index.php?lang=de&region=publications&name=schneide&sort=topic#Visual%20Data%20Mining%20of%20Large%20Spatial%20Data%20and%20Cartography Visual Data Mining of Large Spatial Data and Cartography]
 
A list of publications of Jörn Schneidewind can be found at [http://www.informatik.uni-trier.de/~ley/db/indices/a-tree/s/Schneidewind:J=ouml=rn.html DBLP].

== External links ==

* http://www.uni-konstanz.de/

Schneidewind, Jörn

2007-07-17T13:28:14Z

Markus:

[[Category:Persons]]

[[Image:Joerg_Schneidewind.jpg|right|Jörn Schneidewind]]

== General Information ==

Computer Science Institute 
Uni Konstanz Fach D78 
Universitätsstr. 10 
D-78457 Konstanz, Germany 

phone: +49 7531 88-3077 
fax: +49 7531 88-3062 

email: [mailto:schneide@inf.uni-konstanz.de Jörn Schneidewind] 
web: [http://infovis.uni-konstanz.de/members/schneide Jörn Schneidewind Uni Konstanz]

== Curriculum Vitae ==

* 03/2003 - 10/2003: Internship at [http://www.hpl.hp.com/palo_alto/Hewlett Packard Research Labs, Palo Alto, California, US] .
* 11/2002 >: Research assistant, [http://dbvis.fmi.uni-konstanz.de/Database and Visualization Research Group, University of Konstanz].
* 11/2002: Diploma in Informatics at the [http://www.informatik.uni-halle.de/ Department of Mathematics and Computer Science], [http://www.uni-halle.de/ Martin-Luther-University Halle-Wittenberg].

== Teaching ==
'''WS06/07''' 
* [http://infovis.uni-konstanz.de/index.php?region=teach&event=ws06&course=im Informationsmanagement]

'''SS06''' 
* [http://dbvis.inf.uni-konstanz.de/~bustos/sva_ss06/index.php Visual Analytics]
* [http://dbvis.inf.uni-konstanz.de/lehre/ss06/infovis/index.php Information Visualization I]

'''WS05/06''' 
* [http://dbvis.inf.uni-konstanz.de/~schneide/seminar-ws2005/ Visuelle Datenexploration]
* [http://dbvis.inf.uni-konstanz.de/~mansmann/ws05/im/index.php Informationsmanagement]

'''SS05''' 
* [http://dbvis.inf.uni-konstanz.de/lehre/ss06/infovis/index.php Information Visualization I]

'''WS04/05''' 
* [http://infovis.uni-konstanz.de/index.php?region=teach&event=ws06&course=im Informationsmanagement]

'''WS03/04''' 
* [http://www.inf.uni-konstanz.de/dbis/teaching/ws0304/computing-systems/computing-systems.html Rechnersysteme]

'''SS04''' 
* [http://dbvis.inf.uni-konstanz.de/~schneide/ss04/dm/index.php Data Mining]

'''SS03''' 
* [http://infovis.uni-konstanz.de/~schneide/sem_ss03/index.html Data Mining und Visualisierung]

'''WS02/03''' 
* [http://infovis.uni-konstanz.de/lehre/ws02/ra Rechnersysteme]

== Research Interests ==

* Data Mining and Knowledge Discovery
* Information Visualization - Visualization of Large Databases (see also PaperFinder Project)
* Similarity Search in Spatial Databases.
* High-Dimensional Indexing

== Selected Publications ==

* [http://infovis.uni-konstanz.de/index.php?lang=de&region=publications&name=schneide&sort=topic#Data%20Mining%20and%20Knowledge%20Discovery Data Mining and Knowledge Discovery]
* [http://infovis.uni-konstanz.de/index.php?lang=de&region=publications&name=schneide&sort=topic#Graphical%20User%20Interfaces%20for%20Databases Graphical User Interfaces for Databases]
* [http://infovis.uni-konstanz.de/index.php?lang=de&region=publications&name=schneide&sort=topic#Information%20Visualization%20-%20Visualization%20of%20Large%20Databases Information Visualization - Visualization of Large Databases]
* [http://infovis.uni-konstanz.de/index.php?lang=de&region=publications&name=schneide&sort=topic#Pattern-%20and%20DataBase%20Management%20Systems Pattern- and DataBase Management Systems]
* [http://infovis.uni-konstanz.de/index.php?lang=de&region=publications&name=schneide&sort=topic#Visual%20Data%20Mining%20of%20Large%20Spatial%20Data%20and%20Cartography Visual Data Mining of Large Spatial Data and Cartography]
 
A list of publications of Jörn Schneidewind can be found at [http://www.informatik.uni-trier.de/~ley/db/indices/a-tree/s/Schneidewind:J=ouml=rn.html DBLP].

== External links ==

* http://www.uni-konstanz.de/