Spatio-temporal semantics based on ＂object views＂ or ＂event views＂ has few abilities to represent and model the continuity and gradual oceanic phenomena or objects, which seriously limits the specific marine appli...Spatio-temporal semantics based on ＂object views＂ or ＂event views＂ has few abilities to represent and model the continuity and gradual oceanic phenomena or objects, which seriously limits the specific marine applications and knowledge discovery and data mining, so this paper proposes a hierarchical abstraction semantics with ＂marine spatio-temporal process-life span phases-evolution sequences--state units＂ and process objects included by level with ＂marine process objects--phase objects--sequence object---state objects＂ with the oceanic process characteristics into the marine process semantics. In addition, this paper designs the storage and representation of marine process objects using the backus normal forms （BNF） and abstract data type （ADT）. Base on E1 Nifio Southern Oscilation （ENSO） index and Chinese rain gauging station data, this paper also gives a case of study. The spatio-temporal analysis between ENSO process and Chinese rainfall anomalies shows that the marine spatio-temporal semantics not only can illustrate the spatial distribution of Chinese rainfall anomalies in different time scales at ENSO process, life span phases and state units, but also analyze the dynamic changes of Chinese rainfall anomalies in different life span phases or state units within ENSO evolution.展开更多
Hierarchical abstraction is a scalable strategy to deal with large networks.Existing visualization methods have allowed to aggregate the network nodes into hierarchies based on the node attributes or network topology,...Hierarchical abstraction is a scalable strategy to deal with large networks.Existing visualization methods have allowed to aggregate the network nodes into hierarchies based on the node attributes or network topology,each of which has its own advantage.Very few previous system has the capability to enjoy the best of both worlds.This paper presents OnionGraph,an integrated framework for the exploratory visual analysis of heterogeneous multivariate networks.OnionGraph allows nodes to be aggregated based on either node attributes,topology,or a hierarchical combination of both.These aggregations can be split,merged and filtered under the focus+context interaction model,or automatically traversed by the information-theoretic navigation method.Node aggregations that contain subsets of nodes are displayed by the onion metaphor,indicating the level and details of the abstraction.We have evaluated the OnionGraph tool in three real-world cases.Performance experiments demonstrate that on a commodity desktop,our method can scale to million-node networks while preserving the interactivity for analysis.展开更多
基金The National Basic Research Program of China under contract No.2009CB723903the National Natural Science Foundation of China under contract Nos 40901194 and 40801162+2 种基金the Director Foundation of CEODECASunder contract No.Y2ZZ06101B
文摘Spatio-temporal semantics based on ＂object views＂ or ＂event views＂ has few abilities to represent and model the continuity and gradual oceanic phenomena or objects, which seriously limits the specific marine applications and knowledge discovery and data mining, so this paper proposes a hierarchical abstraction semantics with ＂marine spatio-temporal process-life span phases-evolution sequences--state units＂ and process objects included by level with ＂marine process objects--phase objects--sequence object---state objects＂ with the oceanic process characteristics into the marine process semantics. In addition, this paper designs the storage and representation of marine process objects using the backus normal forms （BNF） and abstract data type （ADT）. Base on E1 Nifio Southern Oscilation （ENSO） index and Chinese rain gauging station data, this paper also gives a case of study. The spatio-temporal analysis between ENSO process and Chinese rainfall anomalies shows that the marine spatio-temporal semantics not only can illustrate the spatial distribution of Chinese rainfall anomalies in different time scales at ENSO process, life span phases and state units, but also analyze the dynamic changes of Chinese rainfall anomalies in different life span phases or state units within ENSO evolution.
文摘Hierarchical abstraction is a scalable strategy to deal with large networks.Existing visualization methods have allowed to aggregate the network nodes into hierarchies based on the node attributes or network topology,each of which has its own advantage.Very few previous system has the capability to enjoy the best of both worlds.This paper presents OnionGraph,an integrated framework for the exploratory visual analysis of heterogeneous multivariate networks.OnionGraph allows nodes to be aggregated based on either node attributes,topology,or a hierarchical combination of both.These aggregations can be split,merged and filtered under the focus+context interaction model,or automatically traversed by the information-theoretic navigation method.Node aggregations that contain subsets of nodes are displayed by the onion metaphor,indicating the level and details of the abstraction.We have evaluated the OnionGraph tool in three real-world cases.Performance experiments demonstrate that on a commodity desktop,our method can scale to million-node networks while preserving the interactivity for analysis.
