PA214 Visualization II / Lecture #1 Bára Kozlíková, Katka Furmanová, Vítek Rusňák, Honza Byška Introduction HCILAB :•. visitlab What to expect? • Successor of PV251 - Visualization course • We are expecting that you know the basic principles of visualizations © • Visualization II more focused on research in visualizations What to expect? • Lectures about diverse research fields and topics in visualization Medical visualization, molecular visualization, visual data science, AI explainability, visualization & machine learning, user studies,... • Many (invited) speakers • TUWien Wolftech Broadcast Solutions AS, Bergen • MU What is expected from you? • To attend and enjoy © • Attend seminars Select a topic of interest (from the given list) and work on your project for the whole semester You can work individually or in groups Each seminar, there will be a task for you and homework Each task will be "awarded" by points. Based on these, you will get the final grade for the course. Topic for today... • Why is visualization important • Why is research in visualizations exciting httDs://princeton[ibrarv.org/event/data-visualization-with-iavascript-part-3/ Motivation • TED talk of David McCandless: Introduction to Data Visualization • https://[ibguides.lib.fit.edu/c.php?g=863116&p=6188479 • Hans Rosling: GapMinder • https://www.voutube.com/watch?v=ibkSRLYSoio&[ist=PLXLYorBS4uI9-lC6SVa[v-10710nrOvN9 Three main fields in visualization • Scientific visualization (SciVis) • Information visualization (InfoVis) • Visual analytics (VAST = Visual Analytics Science and Technology) Scientific Visualization • Producing graphics representations of scientific phenomena • Graphic representation is used for understanding, interpretation. It may guide the direction of the research in the corresponding field. 8 Scientific Visualization - Areas • Many fields: • Medical visualization • Molecular visualization • Flow visualization • Volumetric visualization Scientific Visualization Pipeline Produce Input Data Analyze, Filter, Reformat Apply Sei Vis Techniques Map to Geometry Render, Postprocess View Results What is the core topic... • The focus of the pipeline is the application of SciVis techniques to create a renderable geometric model of the data 11 Data Representation in SciVis • The studied phenomenon is usually modelled by measurements at a discrete set of points in space • Representational samples of the underlying mathematical function governing that phenomenon • Mesh or topology associated with the data • Explicit or implicit definition of points 12 SciVis Techniques • Spatial phenomena • Scalar data - slice planes, isosurfaces, glyphs, volumes • Vector data - hedgehog, streaklines, ribbons SciVis Software Packages Tool Produce Input Data Analyze. Fi Her, Reformat Apply Sei Vis Techniques Map to Geometry Render Postprocess View Results Experiments, Simulations Y Custom code X X X X X X X MAT LAB X Y X X X X IDL X Y X X X X VTK X Y X X X Para view X Y X X X OpenGL Y X Open Scene Graph Y X Maya Y X Photoshop Y X Gimp Y X Imageimagick Y X Premier Y X Journals, web browsers, Projectors Y http://www±u.edu/tech/support/research/training-co 14 Other Resources • Anders Ynnerman: OpenSpace - Visualizing the Universe • https://vimeo.com/169967499 • Anders Ynnerman et al.: Interactive visualization of 3D scanned mummies at public venues • https://dl.acm.org/doi/10.1145/2950040 Information Visualization • Main focus on representing data in an easily understandable way, supported by intuitive interaction • The most common uses of InfoVis are: • Presentation • Explorative analysis • Confirmation analysis 16 Presentation 17 51 Explorative Analysis Confirmation Analysis Other Resources • https://informationisbeautifui.net/ • https://informationisbeautifui.net/visuaiizations/what-makes-a-good-data-visualization/ • Jeffrey Heer: https://www.voutube.com/watch?v=hsfWtPH2kDg • Ben Shneiderman: https://www.voutube.com/watch?v=XlEPxT9EP5c VAST • Analytical reasoning supported by interactive visual interfaces • Designing advanced visual interfaces Visual Data Exploration User Interaction Automated Data Analysis Feedback loop https://www.visual-analvtics.eu/faq/ 21 VAST Scope Information Analytics Interactio Geospatial Analytics Cognitive and Perceptual Science Scientific Analytics Scope of Visual Analytics Presentation, production, and dissemination Statistical Analytics Data Management & Knowledge Representation Knowledge Discovery https://visual-analvtics.eu/2009/12/visual-analytics-scope-and-chaUenges/ 22 Examples Altitude 1?.oro km ui 11.9329' lon/9228' tlev reomelers https://www.researchgate.net/figure/Visuai-anaivtics-in-action-Visuai-support-for-the-simulation-of-climate-models figl 277007765 23 Examples SAS" Visual Analytics - Report Viewer 0» | t J H Telecommunications - Customer's Service Choote * D*«(s)__ [3 Monday. Stpt*mb»r 7, 2015 □ Tu*ie*y, Stpttmbtr S. 20» Q W«dft*id*r. Stpttmbtr 9.2015 □ Tftvrjday. S«pt*m0*f 10, 2015 [7] Fndjy. S*pC*ml*r 11. 2015 □ Saturday, Wpttmbvr 12. 2015 □ Sunday. Sapttmbtr 15. 2015 ■>oos* a Time o( Day □ 12-J*m □ 4-7»m □ ••llam □ 12 -3pm □ 4.7pm □ I - 11pm How much traffic is served over which network? ■V 03 : C:< How much traffic is served over which network during each hour of the day? UMTSISGI 0 S 6 7 « t 10 l| 12 IS 1« 15 1« 17 II 1» 20 21 22 Cell Tower Traffic and Throughput (Large circles use more data, blue circles are faster) ® [■ml • - G "4r https://www.softwareadvice.com/bi/sas-visuai-anaivtics-profiie/ 24 373673 Other Resources • Tamara Munzner: https://www.voutube.com/watcri ?v=xUbhRu2f8e4 25 Where to publish the visualization research outcomes... • International conferences: IEEE VIS, EG EuroVis, IEEE PacificVis,... • Smaller specialized venues: EG VCBM • Journals: IEEE TVCG, Computer Graphics Forum,... What are the possible paper types... http://ieeevis.org/ Area 1: Theoretical & Empirical This area focuses on theoretical and empirical research topics that aim to establish the foundation of VIS as a scientific subject Theoretical & Empirical ■ Area 4: Representations & Interaction This area focuses on the design of visual representations and interaction techniques for different types of data, users, and visualization tasks. Representations & Interaction. Area 2: Applications This area encompasses all forms of application-focused research. Applications ■ Area 5: Data Transformations This area focuses on the algorithms and techniques that transform data from one form to another to enable effective and efficient visuaL mapping as required by the intended visuaL representations. Data Transformations Area 3: Systems & Rendering This area focuses on the themes of buiLding systems, algorithms for rendering, and alternate input and output modalities. Systems & Rendering - Area 6: Analytics & Decisions This area focuses on the design and optimization of integrated workflows for visual data anaLysis, knowledge discovery, decision support, machine learning, and other data intelligence tasks. Analytics & Decisions —> We hope you'll like the course... • Questions and requests: *furmanova(cDmaiL muni.cz, * rusnak(g)ics. muni.cz. * jan.bvska(q)gmai[.com. * koziikova(cDfi.m uni.cz