Difference between revisions of "Tasks Taxonomy for Graphs"
Jump to navigation
Jump to search
| Line 1: | Line 1: | ||
== Low-Level Tasks == | == 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 == | == Graph Task Taxonomy == | ||
| Line 8: | Line 49: | ||
== High-Level Tasks == | == High-Level Tasks == | ||
| + | |||
| + | == 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. | ||
Revision as of 10:56, 16 October 2006
Low-Level Tasks
From [Amar et al. 2005] and [Lee et al 2006].
- General Tasks
| 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
| Task | Description |
| Find Adjacent Nodes | Given a node, find its adjacent nodes. |
Graph Task Taxonomy
Topology-based Tasks
Attribute-based Tasks
Browsing Tasks
Overview Tasks
High-Level Tasks
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.