What is he best known for?
The fields of study he is best known for:
- Software
- Artificial intelligence
- Programming language
Visualization, Data visualization, Geovisualization, Graphics and Human–computer interaction are his primary areas of study.
His Visualization research includes elements of Cartography, Information overload and Data science.
His biological study spans a wide range of topics, including Agile software development and User interface.
His work carried out in the field of Data visualization brings together such families of science as Statistical graphics, Information visualization and Rendering.
His Geovisualization research is multidisciplinary, incorporating perspectives in Visual analytics, Representation and Geographic information system.
His Graphics study which covers Spatial analysis that intersects with Transient, Graphical user interface and Scripting language.
His most cited work include:
- Space, time and visual analytics (297 citations)
- Interactive Visual Exploration of a Large Spatio-temporal Dataset: Reflections on a Geovisualization Mashup. (181 citations)
- Exploring spatial data representation with dynamic graphics (165 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Visualization, Data science, Geovisualization, Human–computer interaction and Data visualization.
Jason Dykes works mostly in the field of Visualization, limiting it down to topics relating to Graphics and, in certain cases, Scale.
His study looks at the intersection of Data science and topics like Visual analytics with Analytics.
His work in Geovisualization addresses subjects such as Geographic information system, which are connected to disciplines such as Information retrieval.
His Human–computer interaction study incorporates themes from Interactive visualization, Space, Spatial analysis and Computer graphics.
His Data visualization study frequently draws connections to other fields, such as Multimedia.
He most often published in these fields:
- Visualization (45.56%)
- Data science (36.09%)
- Geovisualization (26.04%)
What were the highlights of his more recent work (between 2014-2021)?
- Visualization (45.56%)
- Data science (36.09%)
- Human–computer interaction (19.53%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Visualization, Data science, Human–computer interaction, Data visualization and Data mining.
His Visualization study frequently links to related topics such as Engineering design process.
His studies in Data science integrate themes in fields like Domain and Reflection.
His study on Human–computer interaction also encompasses disciplines like
- Relation and related Scale, Interactivity, Analytics and Graphics,
- Task which intersects with area such as Scope and Knowledge management.
Jason Dykes has researched Data visualization in several fields, including Reflexivity, Engineering ethics and Social constructionism.
His research in Data mining is mostly focused on Geovisualization.
Between 2014 and 2021, his most popular works were:
- Visual analysis of pressure in football (37 citations)
- Criteria for Rigor in Visualization Design Study (34 citations)
- Visualizing Multiple Variables Across Scale and Geography (32 citations)
In his most recent research, the most cited papers focused on:
- Software
- Artificial intelligence
- Programming language
Jason Dykes spends much of his time researching Visualization, Data visualization, Data mining, Geovisualization and Variable.
His Visualization study combines topics in areas such as Data science, Domain, Human–computer interaction and Engineering design process.
His Data visualization research integrates issues from Reflexivity, Engineering ethics and Social constructionism.
His study in Data mining is interdisciplinary in nature, drawing from both Spatial analysis, Set and Feature selection.
His Geovisualization study integrates concerns from other disciplines, such as Geospatial analysis and Choropleth map.
His research in Variable intersects with topics in Simulated annealing, Scale, Theoretical computer science, Multivariate analysis and Multivariate statistics.
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