A Survey of Visualizations

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In my first term in HuCo I was assigned to present the concept of Visualization in class. I made a survey looking for definition, usage and examples. I put all to gather in this keynotes. Now it is available here. Enjoy.

See more here: http://luciano.fluxo.art.br/?p=87

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  • Pictures taken in New york\nRED - Tourists\nBLUE - Residents\n\nUser can have their own conclusion\n
  • Cross-reference in bible\n
  • Survey of text visualization techniques\nAndrey A. Puretskiy, Gregory L. Shutt and Michael W. Berry\n\nWordle\nhttp://www.wordle.net/\n
  • Survey of text visualization techniques\nAndrey A. Puretskiy, Gregory L. Shutt and Michael W. Berry\n\nWordle\nhttp://www.wordle.net/\n
  • The software creates a series of color-coded bars (by author), each corresponding to a single version or revision of the document. Same-color segments on adjacent bars are connected, creating a three-dimensional visual effect that provides the user with information on the way the document was altered over time by multiple authors\n\nDarwin\nhttp://benfry.com/traces/\n
  • The visualization provided by TextArc consists of two levels. First, the original text is available around the periphery of the visualization area. Second, an interconnected graph of terms is provided in the middle of the visualization area. The two areas are interconnected, meaning that the user is able to select any particular term in the middle area and quickly see its context in the full text that is displayed along the periphery.\n\nTextArc\nhttp://www.textarc.org/\n
  • Has been used to support the extraction and tracking of scenarios and plots from news articles defining the VAST 2007 Contest (Scholtz et al. 2007).\n\nIn providing news stories, blog entries, background information, and limited multimedia materials (small maps and data tables), the contest organizers challenged the participants to investigate a major law enforcement/counter-terrorism scenario, form a hypothesis, and collect supporting evidence.\n\nText mining could greatly benefit from the design of more intuitive visualizations that expose or verify potential scenarios of human activity.\n\nFeatureLens allows the user to explore frequently occurring terms or patterns in a collection of documents.\nConnections between these frequent terms and the dates at which they appear in the set of documents can quickly be visualized and investigated.\n
  • Narrative Visualization: Telling Stories with Data\nEdward Segel and Jeffrey Heer\n
  • Narrative Visualization: Telling Stories with Data\nEdward Segel and Jeffrey Heer\n
  • Narrative Visualization: Telling Stories with Data\nEdward Segel and Jeffrey Heer\n
  • Narrative Visualization: Telling Stories with Data\nEdward Segel and Jeffrey Heer\n
  • Visual structuring refers to mechanisms that communicate the overall structure of the narrative to the viewer and allow him to identify his position within the larger organization of the visualization.\nThese design strategies help orient the viewer early on (establishing shot, checklist, consistent visual platform) and allow the\nviewer to track his progress through the visualization (progress bar, timeline slider).\n\nHighlighting refers to visual mechanisms that help direct the viewer’s attention to particular elements in the display.\nThis can be achieved through the use of color, motion, framing, size, audio, and more, which augment the salience of an element relative to its surroundings. Many of these strategies are also used in film, art, and comics.\n\nTransition guidance concerns techniques for moving withinor between visual scenes without disorienting the viewer.\nA common technique from film is continuity editing, though other strategies (e.g., animated transitions, object continuity, camera motion) also exist.\n
  • Visual structuring refers to mechanisms that communicate the overall structure of the narrative to the viewer and allow him to identify his position within the larger organization of the visualization.\nThese design strategies help orient the viewer early on (establishing shot, checklist, consistent visual platform) and allow the\nviewer to track his progress through the visualization (progress bar, timeline slider).\n\nHighlighting refers to visual mechanisms that help direct the viewer’s attention to particular elements in the display.\nThis can be achieved through the use of color, motion, framing, size, audio, and more, which augment the salience of an element relative to its surroundings. Many of these strategies are also used in film, art, and comics.\n\nTransition guidance concerns techniques for moving withinor between visual scenes without disorienting the viewer.\nA common technique from film is continuity editing, though other strategies (e.g., animated transitions, object continuity, camera motion) also exist.\n
  • Visual structuring refers to mechanisms that communicate the overall structure of the narrative to the viewer and allow him to identify his position within the larger organization of the visualization.\nThese design strategies help orient the viewer early on (establishing shot, checklist, consistent visual platform) and allow the\nviewer to track his progress through the visualization (progress bar, timeline slider).\n\nHighlighting refers to visual mechanisms that help direct the viewer’s attention to particular elements in the display.\nThis can be achieved through the use of color, motion, framing, size, audio, and more, which augment the salience of an element relative to its surroundings. Many of these strategies are also used in film, art, and comics.\n\nTransition guidance concerns techniques for moving withinor between visual scenes without disorienting the viewer.\nA common technique from film is continuity editing, though other strategies (e.g., animated transitions, object continuity, camera motion) also exist.\n
  • Visual structuring refers to mechanisms that communicate the overall structure of the narrative to the viewer and allow him to identify his position within the larger organization of the visualization.\nThese design strategies help orient the viewer early on (establishing shot, checklist, consistent visual platform) and allow the\nviewer to track his progress through the visualization (progress bar, timeline slider).\n\nHighlighting refers to visual mechanisms that help direct the viewer’s attention to particular elements in the display.\nThis can be achieved through the use of color, motion, framing, size, audio, and more, which augment the salience of an element relative to its surroundings. Many of these strategies are also used in film, art, and comics.\n\nTransition guidance concerns techniques for moving withinor between visual scenes without disorienting the viewer.\nA common technique from film is continuity editing, though other strategies (e.g., animated transitions, object continuity, camera motion) also exist.\n
  • Ordering refers to the ways of arranging the path viewers take through the visualization.\nSometimes this path is prescribed by the author (linear), sometimes there is no path suggested at all (random access), and other times the user must select a path among multiple alternatives (user-directed).\n\nInteractivity refers to the different ways a user can manipulate the visualization (filtering, selecting, searching, navigating),\nand also how the user learns those methods (explicit instruction, tacit tutorial, initial configuration).\n\nMessaging refers to the ways a visualization communicates observations and commentary to the viewer.\nThis might be achieved through short text fields (labels, captions, headlines, annotations) or more substantial descriptions (articles, introductions, summaries).\n\n
  • Ordering refers to the ways of arranging the path viewers take through the visualization.\nSometimes this path is prescribed by the author (linear), sometimes there is no path suggested at all (random access), and other times the user must select a path among multiple alternatives (user-directed).\n\nInteractivity refers to the different ways a user can manipulate the visualization (filtering, selecting, searching, navigating),\nand also how the user learns those methods (explicit instruction, tacit tutorial, initial configuration).\n\nMessaging refers to the ways a visualization communicates observations and commentary to the viewer.\nThis might be achieved through short text fields (labels, captions, headlines, annotations) or more substantial descriptions (articles, introductions, summaries).\n\n
  • Ordering refers to the ways of arranging the path viewers take through the visualization.\nSometimes this path is prescribed by the author (linear), sometimes there is no path suggested at all (random access), and other times the user must select a path among multiple alternatives (user-directed).\n\nInteractivity refers to the different ways a user can manipulate the visualization (filtering, selecting, searching, navigating),\nand also how the user learns those methods (explicit instruction, tacit tutorial, initial configuration).\n\nMessaging refers to the ways a visualization communicates observations and commentary to the viewer.\nThis might be achieved through short text fields (labels, captions, headlines, annotations) or more substantial descriptions (articles, introductions, summaries).\n\n
  • Ordering refers to the ways of arranging the path viewers take through the visualization.\nSometimes this path is prescribed by the author (linear), sometimes there is no path suggested at all (random access), and other times the user must select a path among multiple alternatives (user-directed).\n\nInteractivity refers to the different ways a user can manipulate the visualization (filtering, selecting, searching, navigating),\nand also how the user learns those methods (explicit instruction, tacit tutorial, initial configuration).\n\nMessaging refers to the ways a visualization communicates observations and commentary to the viewer.\nThis might be achieved through short text fields (labels, captions, headlines, annotations) or more substantial descriptions (articles, introductions, summaries).\n\n
  • which prioritize the author-driven approach\nPrice of weedhttp://www.priceofweed.com/\n
  • which prioritize the author-driven approach\nPrice of weedhttp://www.priceofweed.com/\n
  • which prioritize the author-driven approach\nPrice of weedhttp://www.priceofweed.com/\n
  • Reader-driven is prioritized\n\nFive Major North Korean Prison Camps\nhttp://www.washingtonpost.com/wp-srv/special/world/north-korean-prison-camps-2009/?ad=inw\n
  • Reader-driven is prioritized\n\nFive Major North Korean Prison Camps\nhttp://www.washingtonpost.com/wp-srv/special/world/north-korean-prison-camps-2009/?ad=inw\n
  • that promotes a dialogue between the two approaches\n\nBudget Forecasts\nhttp://www.nytimes.com/interactive/2010/02/02/us/politics/20100201-budget-porcupine-graphic.html\n\nGapMindhttp://www.gapminder.org\n
  • that promotes a dialogue between the two approaches\n\nBudget Forecasts\nhttp://www.nytimes.com/interactive/2010/02/02/us/politics/20100201-budget-porcupine-graphic.html\n\nGapMindhttp://www.gapminder.org\n
  • that promotes a dialogue between the two approaches\n\nBudget Forecasts\nhttp://www.nytimes.com/interactive/2010/02/02/us/politics/20100201-budget-porcupine-graphic.html\n\nGapMindhttp://www.gapminder.org\n
  • that promotes a dialogue between the two approaches\n\nBudget Forecasts\nhttp://www.nytimes.com/interactive/2010/02/02/us/politics/20100201-budget-porcupine-graphic.html\n\nGapMindhttp://www.gapminder.org\n
  • that promotes a dialogue between the two approaches\n\nBudget Forecasts\nhttp://www.nytimes.com/interactive/2010/02/02/us/politics/20100201-budget-porcupine-graphic.html\n\nGapMindhttp://www.gapminder.org\n
  • Guide - Visualization can be too complicate or too big... so users need some tutorial or guide\n
  • NYT - Pushing Visualization in journalism\n
  • Dark = Facebook\nYellow = non facebok\n
  • Dark = Facebook\nYellow = non facebok\n
  • Many eye - Democratize visualization\n
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  • A Survey of Visualizations

    1. 1. VISUALIZATION
    2. 2. VISUALIZATIONBY LUCIANO FRIZZERA
    3. 3. ? WHAT IS VISUALIZATION ? 100 96 75 70 50 58 55 53 43 25 26 17 0 2007 2008 2009 2010
    4. 4. ? WHAT IS VISUALIZATION ?• VISUALIZATION IS THE VISUAL REPRESENTATION OF DATA. 100 96 75 70 50 58 55 53 43 25 26 17 0 2007 2008 2009 2010
    5. 5. ? WHAT IS VISUALIZATION ?• CAN BE ANY KIND OF DATA: WORDS IN A TEXT, DEMOGRAPHICS OF SOME COUNTRY, ECONOMICS, FOOD, TIME, SOUND.... WHATEVER YOU WANT.
    6. 6. ? WHAT IS VISUALIZATION ?• CAN BE ANY KIND OF DATA: WORDS IN A TEXT, DEMOGRAPHICS OF SOME COUNTRY, ECONOMICS, FOOD, TIME, SOUND.... WHATEVER YOU WANT. • IT IS USED IN A VARY WIDE FIELD: ECONOMY, STATISTIC, BUSINESS, CARTOGRAPHY, ENGINEERING, BIOLOGY, JOURNALISM, ETC.
    7. 7. VISUALIZATION OF YESTERDAY• FOR A LONG TIME WE USE FINANÇAS Tabela 37 - Evolução do ICMS, FPM, ISS e IPTU em Valores constantes VISUALIZATION TO ICMS 2004 2005 2006 2007 2008 2009 28.089.692,67 32.521.843,47 37.225.189,04 40.735.983,77 44.789.853,51 44.762.831,13 51.207.919,18 2010 SUPPORT FPM 27.533.785,28 33.858.948,82 35.392.219,67 38.029.637,46 43.883.960,59 39.621.209,66 36.145.758,26 pação dos Municípios (IPM) de Cariacica devido às novas empresas ISS 14.033.032,15 18.877.408,85 23.363.805,43 29.491.960,56 34.867.702,20 34.695.445,21 38.446.424,15 geradoras de ICMS que se instalaram no município nos últimos anos. IPTU 3.103.499,59 3.073.168,72 3.554.633,54 4.160.290,63 4.107.445,86 4.545.419,78 6.848.492,49 STORYTELLING. Em 2009 Cariacica se configura como o município do ES com menor receita per capita, conforme pode ser observado na tabela 38. Porém, com os dados sobre população divulgados pelo Censo 2010 e consi- Fonte: Balanços Municipais - Resumo Geral da Receita - Anexo 2. Gráfico 18 - Evolução do ICMS, FPM, ISS e IPTU em Valores constantes derando a receita total do município prevista para 2011, a receita per capita de Cariacica passa a se configurar em torno de R$ 1.000,00. Mesmo com a menor capacidade de atendimento à população dentre• BASICALLY IT WAS todos os municípios do Espírito Santo, visto que a receita per capita é a menor do Estado, Cariacica entre 2005 e 2009 foi o quarto mu- nicípio do Espírito Santo que mais investiu no período, na ordem de STATIC CHARTS TO aproximadamente R$ 213 milhões. Além disso, o município ainda consegue figurar entre os cem que mais investem no Brasil, de acordo com dados da Revista Multicidades. Na REPRESENT edição de 2010, Cariacica aparece como 71º munícipio do Brasil em total de investimentos. Esse crescimento significa um salto pisitivo em direção à consolidação de uma cidade com mais equipamentos so- FINANCIAL AND cials e com mais infraestrutura, tais como ruas pavimentadas, escolas, unidades de saúde, entre outros. Os recursos destinados aos investimentos cresceram de 2004 a 2010 STATISTIC DATA quase que de forma sucessiva, já que nos anos de 2009 e 2010, devido principalmente à crise econômica mundial, os investimentos em geral diminuíram, não sendo diferente em Cariacica. No entanto, apesar do ON REPORTS. decréscimo dos últimos dois anos, o investimento em 2010 ainda foi 265% maior do que o de 2004. Fonte: Balanços Municipais - Resumo Geral da Receita - Anexo 2. Obs: Valores constantes com base em 2010, corrigidos pelo IPCA. Elaboração: SEMGE/PMC 100 C a r i a c i c a e m d a d o s | 2 0 1 1
    8. 8. VISUALIZATION OF YESTERDAY• NEWSPAPERS USE AS AN INFOGRAPHIC.• STARTING TO MERGE IMAGE AND DATA TOGETHER
    9. 9. VISUALIZATION OF TODAY • NOW, WE ARE USING TEXT MINING AND CRUNCHING HUGE DATABASE TO CREATE VISUALIZATION.
    10. 10. VISUALIZATION OF TODAY • NOW, WE ARE USING TEXT MINING AND CRUNCHING HUGE DATABASE TO CREATE VISUALIZATION.
    11. 11. VISUALIZATION OF TODAY • NOW, WE ARE USING TEXT MINING AND CRUNCHING HUGE DATABASE TO CREATE VISUALIZATION.
    12. 12. VISUALIZATION OF TODAY • NOW, WE ARE USING TEXT MINING AND CRUNCHING HUGE DATABASE TO CREATE VISUALIZATION. • COMBINE COMPUTER SCIENCE, STATISTIC, ARTS DESIGN AND STORYTELLING.
    13. 13. VISUALIZATION OF TODAY • NOW, WE ARE USING TEXT MINING AND CRUNCHING HUGE DATABASE TO CREATE VISUALIZATION. • COMBINE COMPUTER SCIENCE, STATISTIC, ARTS DESIGN AND STORYTELLING. • CREATING DIFFERENT CONTEXTS.
    14. 14. VISUALIZATION OF TODAY • NOW, WE ARE USING TEXT MINING AND CRUNCHING HUGE DATABASE TO CREATE VISUALIZATION. • COMBINE COMPUTER SCIENCE, STATISTIC, ARTS DESIGN AND STORYTELLING. • CREATING DIFFERENT CONTEXTS. • USING INTERACTIVITY TO ENGAGE THE AUDIENCE.
    15. 15. VISUALIZATION OF TODAY • IT IS VERY COMMON TO SEE THINGS THAT WE NEVER SAW BEFORE.
    16. 16. VISUALIZATION OF TODAY
    17. 17. VISUALIZATION OF TODAY
    18. 18. TEXT MINING + VISUALIZATION• COMBINING TEXT MINING WITH VISUALIZATION CAN PROVIDE A BIG PICTURE OF LARGE AMOUNT OF TEXT DATA.
    19. 19. TEXT MINING + VISUALIZATION• COMBINING TEXT MINING WITH VISUALIZATION CAN PROVIDE A BIG PICTURE OF LARGE AMOUNT OF TEXT DATA.• TAG CLOUD • WORDLE • TEXTCROWD
    20. 20. TEXT MINING + VISUALIZATION• COMBINING TEXT MINING WITH VISUALIZATION CAN PROVIDE A BIG PICTURE OF LARGE AMOUNT OF TEXT DATA.• TAG CLOUD • WORDLE • TEXTCROWD
    21. 21. TEXT MINING + VISUALIZATION• AUTHORSHIP AND CHANGE TRACKING
    22. 22. TEXT MINING + VISUALIZATION• DATA EXPLORATION AND THE SEARCH FOR NOVEL PATTERNS
    23. 23. TEXT MINING + VISUALIZATION• VISUAL ANALYTICS
    24. 24. VISUALIZATION AS STORYTELLING• SEGEL AND HEER IDENTIFIED FEATURES AND TECHNIQUES ON VISUALIZATION TO UNDERSTAND HOW IT CAN BE A NEW WAY OF STORY TELLING.
    25. 25. VISUALIZATION AS STORYTELLING• SEGEL AND HEER IDENTIFIED FEATURES AND TECHNIQUES ON VISUALIZATION TO UNDERSTAND HOW IT CAN BE A NEW WAY OF STORY TELLING.• THEY ANALYZED THE STRUCTURED OF 58 VISUALIZATION LOOKING FOR:
    26. 26. VISUALIZATION AS STORYTELLING• SEGEL AND HEER IDENTIFIED FEATURES AND TECHNIQUES ON VISUALIZATION TO UNDERSTAND HOW IT CAN BE A NEW WAY OF STORY TELLING.• THEY ANALYZED THE STRUCTURED OF 58 VISUALIZATION LOOKING FOR: • GENRE
    27. 27. VISUALIZATION AS STORYTELLING• SEGEL AND HEER IDENTIFIED FEATURES AND TECHNIQUES ON VISUALIZATION TO UNDERSTAND HOW IT CAN BE A NEW WAY OF STORY TELLING.• THEY ANALYZED THE STRUCTURED OF 58 VISUALIZATION LOOKING FOR: • GENRE • VISUAL NARRATIVE
    28. 28. VISUALIZATION AS STORYTELLING• SEGEL AND HEER IDENTIFIED FEATURES AND TECHNIQUES ON VISUALIZATION TO UNDERSTAND HOW IT CAN BE A NEW WAY OF STORY TELLING.• THEY ANALYZED THE STRUCTURED OF 58 VISUALIZATION LOOKING FOR: • GENRE • VISUAL NARRATIVE • NARRATIVE STRUCTURE
    29. 29. VISUALIZATION AS STORYTELLING• GENRES
    30. 30. VISUALIZATION AS STORYTELLING • GENRES• VISUAL NARRATIVE IS VISUAL DEVICES THAT ASSIST AND FACILITATE THE NARRATIVE. THEY DIVIDED IN THREE SECTIONS:
    31. 31. VISUALIZATION AS STORYTELLING • GENRES• VISUAL NARRATIVE IS VISUAL DEVICES THAT ASSIST AND FACILITATE THE NARRATIVE. THEY DIVIDED IN THREE SECTIONS: • VISUAL STRUCTURING
    32. 32. VISUALIZATION AS STORYTELLING • GENRES• VISUAL NARRATIVE IS VISUAL DEVICES THAT ASSIST AND FACILITATE THE NARRATIVE. THEY DIVIDED IN THREE SECTIONS: • VISUAL STRUCTURING • HIGHLIGHTING
    33. 33. VISUALIZATION AS STORYTELLING • GENRES• VISUAL NARRATIVE IS VISUAL DEVICES THAT ASSIST AND FACILITATE THE NARRATIVE. THEY DIVIDED IN THREE SECTIONS: • VISUAL STRUCTURING • HIGHLIGHTING • TRANSITION GUIDANCE.
    34. 34. VISUALIZATION AS STORYTELLING
    35. 35. VISUALIZATION AS STORYTELLING• NARRATIVE STRUCTURE IS A NON-VISUAL MECHANISMS THAT ASSIST AND FACILITATE THE NARRATIVE. DIVIDED INTO THREE SECTIONS:
    36. 36. VISUALIZATION AS STORYTELLING• NARRATIVE STRUCTURE IS A NON-VISUAL MECHANISMS THAT ASSIST AND FACILITATE THE NARRATIVE. DIVIDED INTO THREE SECTIONS: • ORDERING
    37. 37. VISUALIZATION AS STORYTELLING• NARRATIVE STRUCTURE IS A NON-VISUAL MECHANISMS THAT ASSIST AND FACILITATE THE NARRATIVE. DIVIDED INTO THREE SECTIONS: • ORDERING • INTERACTIVITY
    38. 38. VISUALIZATION AS STORYTELLING• NARRATIVE STRUCTURE IS A NON-VISUAL MECHANISMS THAT ASSIST AND FACILITATE THE NARRATIVE. DIVIDED INTO THREE SECTIONS: • ORDERING • INTERACTIVITY • MESSAGING
    39. 39. VISUALIZATION AS STORYTELLING• SEGEL AND HEER NAMED 3 MODELS OF STORYTELLING USING VISUALIZATIONS:
    40. 40. VISUALIZATION AS STORYTELLING• SEGEL AND HEER NAMED 3 MODELS OF STORYTELLING USING VISUALIZATIONS:• MARTINI GLASS STRUCTURE.
    41. 41. VISUALIZATION AS STORYTELLING• SEGEL AND HEER NAMED 3 MODELS OF STORYTELLING USING VISUALIZATIONS:• MARTINI GLASS STRUCTURE.
    42. 42. VISUALIZATION AS STORYTELLING• SEGEL AND HEER NAMED 3 MODELS OF STORYTELLING USING VISUALIZATIONS:• MARTINI GLASS STRUCTURE.
    43. 43. VISUALIZATION AS STORYTELLING • DRILL-DOWN STORY
    44. 44. VISUALIZATION AS STORYTELLING • DRILL-DOWN STORY
    45. 45. VISUALIZATION AS STORYTELLING • DRILL-DOWN STORY
    46. 46. VISUALIZATION AS STORYTELLING • INTERACTIVE SLIDESHOW
    47. 47. VISUALIZATION AS STORYTELLING • INTERACTIVE SLIDESHOW
    48. 48. VISUALIZATION AS STORYTELLING • INTERACTIVE SLIDESHOW
    49. 49. VISUALIZATION AS STORYTELLING • INTERACTIVE SLIDESHOW
    50. 50. VISUALIZATION AS STORYTELLING • INTERACTIVE SLIDESHOW
    51. 51. VISUALIZATION AS STORYTELLING • INTERACTIVE SLIDESHOW
    52. 52. VISUALIZATION - BE CAREFUL• BIG DATASETS CAN RESULT IN VISUALIZATIONS THAT IS TOO COMPLICATE TO UNDERSTAND. WE HAVE TO THINK OF OUR AUDIENCE.• EXAMPLE OF BAD, BAD, BAD VISUALIZATION

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