In my first term in Humanities Computing (Huci) master program, I was assigned to present the concept of Visualization in class. I made a survey looking for a definition, usage, and examples. I put all together in this keynote.
See more here: http://luciano.fluxo.art.br/a-survey-in-visualizations/
5. ? 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
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.
7. ? 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.
8. 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
10. VISUALIZATION OF TODAY
• NOW, WE ARE USING TEXT
MINING AND CRUNCHING HUGE
DATABASE TO CREATE
VISUALIZATION.
11. VISUALIZATION OF TODAY
• NOW, WE ARE USING TEXT
MINING AND CRUNCHING HUGE
DATABASE TO CREATE
VISUALIZATION.
12. VISUALIZATION OF TODAY
• NOW, WE ARE USING TEXT
MINING AND CRUNCHING HUGE
DATABASE TO CREATE
VISUALIZATION.
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.
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.
15. 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.
19. TEXT MINING + VISUALIZATION
• COMBINING TEXT MINING WITH VISUALIZATION CAN PROVIDE A BIG
PICTURE OF LARGE AMOUNT OF TEXT DATA.
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. TEXT MINING + VISUALIZATION
• COMBINING TEXT MINING WITH VISUALIZATION CAN PROVIDE A BIG
PICTURE OF LARGE AMOUNT OF TEXT DATA.
• TAG CLOUD
• WORDLE
• TEXTCROWD
22. TEXT MINING + VISUALIZATION
• AUTHORSHIP
AND CHANGE
TRACKING
23. TEXT MINING + VISUALIZATION
• DATA EXPLORATION AND THE SEARCH FOR NOVEL PATTERNS
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.
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:
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
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
29. 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
31. VISUALIZATION AS STORYTELLING
• GENRES
• VISUAL NARRATIVE IS VISUAL DEVICES THAT ASSIST AND FACILITATE
THE NARRATIVE. THEY DIVIDED IN THREE SECTIONS:
32. VISUALIZATION AS STORYTELLING
• GENRES
• VISUAL NARRATIVE IS VISUAL DEVICES THAT ASSIST AND FACILITATE
THE NARRATIVE. THEY DIVIDED IN THREE SECTIONS:
• VISUAL STRUCTURING
33. VISUALIZATION AS STORYTELLING
• GENRES
• VISUAL NARRATIVE IS VISUAL DEVICES THAT ASSIST AND FACILITATE
THE NARRATIVE. THEY DIVIDED IN THREE SECTIONS:
• VISUAL STRUCTURING
• HIGHLIGHTING
34. 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.
36. VISUALIZATION AS STORYTELLING
• NARRATIVE STRUCTURE IS A NON-VISUAL MECHANISMS THAT
ASSIST AND FACILITATE THE NARRATIVE. DIVIDED INTO THREE
SECTIONS:
37. VISUALIZATION AS STORYTELLING
• NARRATIVE STRUCTURE IS A NON-VISUAL MECHANISMS THAT
ASSIST AND FACILITATE THE NARRATIVE. DIVIDED INTO THREE
SECTIONS:
• ORDERING
38. VISUALIZATION AS STORYTELLING
• NARRATIVE STRUCTURE IS A NON-VISUAL MECHANISMS THAT
ASSIST AND FACILITATE THE NARRATIVE. DIVIDED INTO THREE
SECTIONS:
• ORDERING
• INTERACTIVITY
39. VISUALIZATION AS STORYTELLING
• NARRATIVE STRUCTURE IS A NON-VISUAL MECHANISMS THAT
ASSIST AND FACILITATE THE NARRATIVE. DIVIDED INTO THREE
SECTIONS:
• ORDERING
• INTERACTIVITY
• MESSAGING
53. 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
Notes de l'éditeur
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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