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Welcome to a "Geovisual Analytics Educational Web site"

Nu också på Svenska!  Swedish Web site: http://ncva.itn.liu.se/?l=sv

 

National Center for Visual Analytics (NCVA) is a Swedish national educational and research resource for Geovisual Analytics established in 2007 with financial support from the Swedish Knowledge Foundation's Visualization Program, VINNOVA (Swedish government agency), Vetenskapsrådet (Swedish Research Council), Unilever Research, Statistics Sweden, OECD, European Commission, Eurostat, SMHI, Norrköping Kommun and others. Professor Mikael Jern is the director.

Our research focuses on geovisual analytics methods and applications for spatio-temporal data which demonstrate the usefulness of these techniques, storytelling, geographic and information visualization, spatial cognition, quantitative data analysis e.g., (geo-)statistics/data science. We are particular interested in how these techniques can support knowledge construction and insight from large statistical data.

 

Our software used by Eurostat http://ec.europa.eu/eurostat/cache/RCI/#?vis=nuts2.labourmarket&lang=en

 

 

 

 

 

Introducing Latest version of Statistics eXplorer

Statistics eXplorer http://ncva.itn.liu.se/explorer for education and research

Statistics eXplorer integrates common visualization methods to make sense of statistical data, uncover patterns of interests, gain insight, tell-a-story and finally communicate knowledge. eXplorer is developed based on a component architecture and includes a wide range of visualization techniques integrated in multiple linked views, map, bubble plot, bar chart, parallel coordinates Plot, Distribution Plot and many more, with sophisticated interaction techniques and interactive features supporting data exploration and analysis. eXplorer also supports integrated storytelling with a snapshot mechanism for capturing discoveries made during the exploratory data analysis process which can be used for sharing gained knowledge. The picture above are from World eXplorer.

 

The Human Development Index (HDI) available as a variable in World eXplorer (see figure)

HDI is a composite statistic of life expectancy, education, and per capita income indicators, which are used to rank countries into four tiers of human development. A country scores higher HDI when the lifespan is higher, the education level is higher, the GDP per capita is higher, the fertility rate is lower, and the inflation rate is lower. HDI was developed by the United Nations as a metric to assess the social and economic development levels of countries. Four principal areas of examination are used to rank countries: mean years of schooling, expected years of schooling, life expectancy at birth and gross national income per capita. This index makes it possible to follow changes in development levels over time and to compare the development levels of different countries.

The HDI was established to place emphasis on individuals, more precisely on their opportunities to realize satisfying work and lives. Evaluating a country's potential for individual human development provides a supplementary metric for evaluating a country's level of development besides considering standard economic growth statistics, such as gross domestic product (GDP). This index can also be used to examine the various policy choices of nations; if, for example, two countries have approximately the same gross national income (GNI) per capita, then it can help to evaluate why they produce widely disparate human development outcomes. One goal of the proponents of the HDI is to stimulate public policy debate.

The HDI variable is available in our World eXplorer. See data table from the colour legend.

See also interactive Vislet:

http://ncvademo-mobile.blogspot.se/2016/04/world-databank-1960-2014-ageing.html

 

 

 

 

 

Europe eXplorer for countries, NUTS2 and NUTS3 regions

"ageing population 65+ in Europe"

http://ncva.itn.liu.se/explorer/europe-explorer?l=en  (europe eXplorer Flash application))

More on this web site :

 https://mitweb.itn.liu.se/geovis/eXplorer/euro  

 

 

 

New Geovis Portal available:

You are invited to use our NEW Geovis Portal for publishing your own Vislets. Read more about this at:

https://mitweb.itn.liu.se/geovis/portal/# 

Use this guest login:  email and password for login

email: visenorrkoping@gmail.com
pass: vise2016

 

 

World eXplorer Vislets (in HTML5) also viewed interactively on your Mobile Device

Figure: World eXplorer is here used on a Samsung Mobile 6 device.

Start the Vislet in your mobile device at:

 

 

 

 

 

 

 

 

 

http://ncvademo-mobile.blogspot.se/2016/04/world-databank-1960-2014-ageing.html

or start  http://ncva.itn.liu.se/explorer/world-explorer?l=en in your mobile web viewer and scroll down to the first interactive picture (World eXplorer Vislet integrated into the web site). Start navigating and select indicators.

 

 

Geovisual Analytics and Knowledge Visualization - Concept, Idea and Implementation

The large and ever-increasing amounts of multidimensional, multi-source, time-varying digital information represent a major challenge. The need to analyze and make decisions based on these information streams, often in time-critical situations, demands integrated, automatic and sophisticated interactive tools that aid the user to manage, process visualize and interact with large information spaces. This approach has been encapsulated in the idea of Geovisual Analytics - "defined as the science of analytical reasoning facilitated by interactive visual interfaces, creative visualization and storytelling". NCVA provides interactive geovisual analytics tools:

• Analytical reasoning facilitated by interactive visual interfaces – e.g. dynamic time-linked views;
• Exploring and analyzing large spatial-temporal and multidimensional data;
• Discern trends or patterns - derive insight and Communicate discovery  and knowledge effectively through Storytelling;
• NCVA is moving Geovisual Analytics Research into Practice through tools like Statistics eXplorer and Publisher;

Knowledge visualization is regarded as an independent scientific discipline and the relevance of applying storytelling towards its scientific goals is still relatively unexplored. Therefore, the emerging popularity of visual storytelling presents several interesting challenges. Our overall objective is to promote within education and research Geovisual Analytics in particular but also its relation to knowledge visualization. To this end we must make sure that education is not left behind in this rapid evolution and can keep up with the international development. In various applied research projects, geovisual analytics techniques have been developed and used to build prototype visualization applications (eg. Statistics eXplorer) that can be used to educate academia with demonstration and educational tools.

"Our mission is to use knowledge visualization to educate researchers and students in geovisual analytics and storytelling, discuss problems and possible approaches to solving them, and define appropriate directions for further research"

 

"Enable you to easily create and share interactive statistics news through our eXplorer Publishing tools"

 

 

Figure: Statistics eXplorer comprises several research topics including information visualization, geographical visualization, perceptual science and Storytelling - see below.

 

 

 

 

 

 

 

 

 

 

 

Interactive Statistical Visualization with integrated Storytelling

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Introducing Latest version of Statistics eXplorer

 

Statistics eXplorer versions now available at these new locations:

World eXplorer: https://mitweb.itn.liu.se/geovis/eXplorer/world/  (countries)

Sweden eXplorer: https://mitweb.itn.liu.se/geovis/eXplorer/swe/#story=0   (counties and municipalities)

Europe eXplorer: https://mitweb.itn.liu.se/geovis/eXplorer/euro   (countries, NUTS2 and NUTS3 regions)

MDim eXplorer: https://mitweb.itn.liu.se/geovis/eXplorer/mDim/#story=0  (any spreadsheet data)

Statistics eXplorer embraces a collection of recognized information visualization web compliant methods applied to perform with statistical data including data manipulations and data access methods. Statistics are easily accessed through distinctive and highly interactive visualization.

Statistics visualization of socio-economic information at national or detailed territorial level can provide clear insight on regional differences and performance within a country and comparison of different areas across countries. Statistics eXplorer enables users to explore simultaneously spatial, temporal and multivariate data (both numeric and categorical) from multiple perspectives, to discover interesting relationships, to share their incremental discoveries with colleagues and finally to communicate selected relevant knowledge to other users. Statistics eXplorer is composed of Geovisual Analytics Visualization components facilitating a broad collection of dynamic visualization methods developed and integrated for use with the Adobe Flash and Flex development platform. NCVA provides access to:World eXplorer, Europe eXplorer, Sweden eXplorer and the more general (no map) Mdim eXplorer.  You can load your own data (EXCEL data etc.), analyse, gain insight and create your own stories to be shared - see figure below.

Figure: Europe eXplorer with NUTS2 regions showing ageing (65+) population in Europe.  Two coordinated and linked views choropleth map, and scatter plot. The elderly population have increased fast in Italian regions Toscana and Liguria and represents more than 25% of total population. On the other extreme, in Inner London the elderly population represented less than 10%. In 2015, 35% of the elderly population lived in only 10% of European regions. In Germany the concentration of the elderly population is higher in the old East Germany region such as Dresden. In Poland, Belgium, the Slovak Republic and Hungary the share of the elderly population is much lower. The younger population age 0-14 is represented in the bubble plot on the Y-axis vs. age 65+ on the X-axis and gives an indication of poor coordination between a young generation and retired populations.  See further an interactive picture below or use:

http://ncvademo-mobile.blogspot.se/2016/06/vislet-europe-nuts2-regions-ageing.html

 

Read more about Statistics eXplorer at: http://ncva.itn.liu.se/explorer 

 

Storytelling integrated in Statistics eXplorer

 

Figure: A Story with snapshots and metadata is created in a Story Editor – The Story is saved and can be shared with colleagues to reach consensus – A Story can be distributed and imported again into eXplorer. Users with diverse backgrounds and expertise participate can participate in a creative discovery processes that transform statistical data into knowledge. After consensus has been reached, the story can be shared through publishing. A snapshot mechanism (see below) helps the author of a story to highlight data views of particular interest, and subsequently guide others to important visual discoveries. The story can then be placed in the public domain to be shared. The snapshot mechanism helps the author of a story to highlight data views of particular interest, and subsequently guide others to important visual discoveries. The final Story (xml format) can then be imported by others with interest in the selected topic. 

 

Publisher for sharing interactive pictures Vislets

Statistics Publisher is our server tool that imports the story produced with Statistical eXplorer. The user selects a layout and visualization tools and then generates the HTML5 code that represents the Vislet.  This code is then manually copied and embedded by the user into a web page. The Vislet can be opened in any user’s Web browser and dynamically communicate the story. 

 

New Geovis Portal available:

You are invited to use our NEW Geovis Portal for publishing your own Vislets. Read more about this at:

https://mitweb.itn.liu.se/geovis/portal/# 

Use this guest login:  email and password for login

email: visenorrkoping@gmail.com
pass: vise2016

 

Statistics eXplorer integrated visualization methods

Statistics  eXplorer integrates highly interactive information and geographical visualization methods including choropleth maps, bar charts and histograms, table lens, parallel coordinates plots or “profile plots”, scatter or "bubble" plots, scatter matrices, time graphs, treemap, and pie graphs but also flow maps - all methods applied and customized to support large statistical data. They also show hidden data or trends. The distribution plot, (see below) was developed in collaboration with OECD and presents evidence-based facts on regions allowing comparison of regions within countries. Interactive features that support a spatial analytical reasoning process are applied, such as tooltips, brushing, highlight, visual inquiry and conditioned statistics filter mechanisms that help detect outliers.

 

  

Learn more about Europe eXplorer

 

Figure:Europe eXplorer supports three levels of statistical maps - European Countries and 289 NUTS2 regions and 1391 NUTS3 regions. The same variable "ageing population 65+" is here illustrated using the same class limits (12,14,16,19,20%). The visual result differs dramatically when you use NUTS2 regions instead of countries. We see no ageing problems in Spain when using the average value for countries but when NUTS2 regions are visualised, we see that north west Spain has an ageing population. The same for Germany (East) and Italy (North). Learn more about how to use Europe eXplorer loaded with the latest European regional statistics:

http://ncva.itn.liu.se/explorer/europe-explorer?l=en

or start Europe eXplorer direct: https://mitweb.itn.liu.se/geovis/eXplorer/euro/#story=0

Below the applied NUTS2 regional data in an EXCEL data sheet

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Interactive Vislet: Produced with Europe eXplorer for NUTS2 regions and loaded with the latest statistics for 2015 "age group 65+" applied into a map coordinated with scatter plot and bar chart. Three regions Liguria, Stockholm and Inner London are highlighted. This EXCEL file can be dowloaded:  http://ncva.itn.liu.se/resources/data/1.678695/EUNUTS2IndicatorsEXCELData2015.xlsx

 

Read more below about publishing this interactive Vislet within our Storytelling concept and Europe eXplorer. 

The Europe eXplorer storytelling mechanism is applied here by the user to: 1) Import regional European statistical data; 2) Explore and make discoveries through trends and patterns and derive insight 3) Visual discoveries are captured into snapshots together with descriptive metadata and hyperlinks  - This gained knowledge is the foundation for 3) creating a Story that can be 4) saved and shared with colleagues and reach consensus. The author gets feedback from colleagues and maybe adopts the story and 5) finally publishes (Publisher) “tell-a-story” to the community using a “Vislet” that is embedded into blogs or Web pages. Try this interactive Vislet (storytelling) above at:

http://ncvademo-mobile.blogspot.com/2016/06/vislet-europe-nuts2-regions-ageing.html

 

This Eurostat

version with European NUTS2 regions was developed using NCVA 

tools

 

 

 

 

 

 

 

Available at: http://epp.eurostat.ec.europa.eu/cache/RSI/

 

 

Three Visual Methods customized for Statistical Data

 

Fisheye Lens technique applied in bar charts enhances large statistical data

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Our interactive "fisheye barchart" is an example of an useful visual technique that has evolved from Information Visualization. The Fisheye Lens technique magnifies the center of the field of view (Focus), with a continuous fall-off in magnification toward the edges (Context). Degree-of-interest is determined by the level of detail to be displayed assigned through user interaction. The Fisheye Lens, here applied to an interactive bar chart developed by NCVA in 2008, represents an interactive data reduction visualization tool for seeing both local detail and global context of a large number of bars simultaneously. Use the interactive Vislet demonstrator produced from our World eXplorer.

 

 

 

 

 

 

 

 

 

 

Figure: Interactive Fisheye Bar Chart at:

 

http://ncvademo-mobile.blogspot.se/2016/11/world-data-in-fish-eye-bar-chart.html

More example of educational information at: http://ncva.itn.liu.se/explorer/learn-more

 

 

Parallel Coordinate Plot applied to statistical data

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The Parallel Coordinate Plot (PCP) is another appealing visualization component introduced and customized by NCVA to the statisticians. Our PCP supports a number of appealing interactive visual analytics methods, for example, to analyze the relationships between indicators and to see a profile for a selected region. Each region (country below) is represented by a string passing through the parallel axes where each axis represents a single indicator, for example, "Population ages 0-14" etc. Differences between highlighted regions can be found by visually comparing the profiles representing them. This has been a highly appreciated method to the statistics community - see figure below highlighting three countries Niger, Qatar and Japan.

 

A special advantage of the our PCP exploration technique is the capability to dynamically make visual inquiries and filter data. Filtering data is a critical step in the process of statistical data analysis. Filter out uninteresting regions; reduce the data set to a smaller, more manageable size. Each indicator axis has a pair of range sliders which define the bottom and top range for the query area. The range of an indicator can be specified by “dragging” the handles on the top and bottom of the corresponding range slider. Regions with values for a selected indicator, that fall outside of the spec­ified range, are filtered out. A combination of range slider movements can be used to dynamically formulate a more complex visual inquiry. These visual conditions and constraints will immediately re­flect the visual contents in all linked views.

Try this Vislet Demo: http://ncvademo-mobile.blogspot.se/2016/07/introduction-to-parallel-coordinate.html and learn more about interacting with a Parallell Coordinate Plot.

More information  at: http://ncva.itn.liu.se/explorer/learn-more?l=en

 

Distribution Plot applied to statistical data developed in collaboration with OECD

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The Distribution Plot is our own method developed in collaboration with OCD and a variation of the box plot visualization method. It is similar to a vertical bar chart but it excels at showing how data items that belong to a cluster are distributed according to an indicator. Each cluster is represented as one row of dots, and these dots are a representation of each data item belonging to this cluster. The mean value is represented as a thin green line for each country. This component is based on the premise that each data item belongs to a cluster. It is a good way to visualize the differences within a cluster; showing the minimum, maximum and mean value as well as the interval of the values in the cluster. Use the menu on the left side to change which indicator to be visualized and use the green scroll bar on the top to "zoom" in on interesting areas. 

 

 

 

 

 

 

 

 

 

Partners using eXplorer and underlying technology

 

 

 

Figure: Regional eXplorer, Metropolitan eXplorer and Factbook eXplorer were customized by NCVA for the OECD web site

 

 

Figure: Regional eXplorer "ageing population in regional TL3 Europe"   An emerging and challenging statistical application domain is geovisualization of regional (sub-national) statistics. Higher integration driven by institutional processes and economic globalisation is eroding national borders and creating competition along regional lines in the world market. Sound information at sub-national level and benchmarking of regions across borders, therefore, has increased in importance in the policy agenda of many countries. 

 

 

 

 

Figure: "The Organization for Economic Co-operation and Development (OECD) makes a lot of world indicators available (e.g. world population and birth rate). Much of it goes unnoticed, because most people just see a bunch of numbers. However, the Factbook eXplorer from the OECD, in collaboration with the National Center for Visual Analytics, is a visualization tool that helps you see and explore the data"  http://stats.oecd.org/oecdfactbook/#

 http://rag.oecd.org/interactiveedition/jobs/jobstory1.html

 

Collaboration with Eurostat and European Commission

Another important user of NCVA/NComVA technology is the European Commission that have used Statistics eXplorer since 2009 for internal analysis of Eurostat statistical data.

In 2012, Eurostat also decided to license the HTML5/JavaScript technology and tools from the spin-off company NComVA. The interactive dashboard application below was a joined development by Eurostat and NComVA based on our GAV HTML5/JavaScript visualization technique purchased in 2012 from the spin-off NComVA.

The application analyses regional statistical data for European at both NUTS2 and NUTS3 level, grouped into different statistical domains. Using the interactive map, individual regions can be selected while different visualisation methods allow the comparison and analysis of regional data in a user-friendly analytical way. The animated timeline shows how regions have performed over time.

Figure: Regional Statistics Illustrated here with latest "Unemployment rates" 2014 contains different dashboards, which always feature a choropleth map on the left pane. On the right window, the user can select four different views:

• Distribution plot
• Scatter plot
• Bar chart
• Data table

 

 

 

 

 

 

 

 

 

 

Figure: 3000 NUTS3 regional statistics showing "Purchasing Power". This Eurostat application is available at: http://epp.eurostat.ec.europa.eu/cache/RSI/

Other Eurostat web sites were also created with NComVA/NCVA HTML5 GAV HTML5 tools - See picture and open the web site at: http://ec.europa.eu/eurostat/web/europe-2020-indicators

More about this at: http://ncva.itn.liu.se/great-statistics-visualization/eurostat-statistics-visualization

 

 

Statistics Sweden SCB

NCVA started its collaboration with SCB already in 2004. SCB provided statistical data and professional advice. The first Statistikatlas was installed at SCB in 2010. For more information see:

text http://www.scb.se/statistikatlasen/

 

 

 

 

Figure: Sweden has an ageing population. The average age has increased from 37% in 1968 to 41% in 2014. The amount elderly population 65+ has increased from 13% to 19.6% during the same period. This interactive picture is available at:

http://www.scb.se/Kartor/Statistikatlas_KN_201404/index.html#story=0

 

Figure: Interactive educational statistical material based on the 4Ws concept “What-When-Where-Why”

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure:  Our storytelling mechanism is used by the author to: 1) import regional statistical data; 2) explore and make discoveries through trends and patterns and derive insight - gained knowledge is the foundation for 3) creating a story that can be 4) shared with colleagues and reach consensus and trust. Visual discoveries are captured into snapshots together with descriptive metadata and hyperlinks in relation to the analytics reasoning. The author gets feedback from colleagues, adopts the story and 5) finally publishes “tell-a-story” to the community using a “Vislet” that is embedded in blogs or Web pages. See example of a Vislet embedded into a web site below.

 

Embedding interactive visualization in web sites

 

The interactive picture below provides insight into several key statistical indicators covering world countries during 1968-2014.  We suggest that you start reading the storytelling text below the interactive picture and click on the snapshots buttons or the red text (snapshots). The geographical world countries are rather big and loading could take some time. You can reduce the map window to the left to see 100% of the scatter and bar chart. Or go to the Vislet web site:

 

 

Interactive Figure: World eXplorer with 3 time-linked views showing indicators related to countries of the world “ageing population in world” during 1960–2014; map, scatter plot (age 65+ vs. age 0–14) and bar chart; comparing 4 countries Niger,Germany,  Sweden and Japan. Students learn interactively that Japan maintains highest elderly rate, while Niger has the lowest. The students can  interact  and  change  indicators  (many other indicators are available in this story) to  discover  reasons  behind  this  trend  and  gain knowledge. 

More HTML5 Vislets available at http://ncvademo-mobile.blogspot.se

 

Treemap implementation with bubbles and bar chart

A potential Swedish sales management data is stored in EXCEL data and can be imported direct into MDim eXplorer. The data has five categorical data columns (Sales person, Sales Manager, District, Gender and Age group; and four numerical data columns). The sales data is here represented with a treemap and fish eye bar chart. Red colour indicates negative sales results (column H). The treemap is divided into "Districts" (Column C) and the "Sales person name" (Column A) is shown. The size of the rectangles are related to "Total Sales" Column F. The combination of the treemap and bar chart provides a deep insight into this kind of abstract data. More information: http://ncva.itn.liu.se/explorer/mdim-explorer?l=en

 

This treemap visualization shows hierarchies in which the rectangular screen space is divided into several hundreds rectangles. Each rectangle represents a sales person in a hierarchy. The colourful presentations accommodates hundreds of sales management data items in a meaningfully organized display allowing patterns and exceptions to be spotted immediately. Combining a treemap visualization with, for example, fisheye bar chart makes the two linked and coordinated views powerful.

 

The picture below is a "Vislet"   produced in HTML5 analyses the Swedish sales management data above. The Vislet was created as an story example produced with MDIM eXplorer and then inserted into a blog site:

Vislet demo: http://ncvademo-mobile.blogspot.se/2015/02/sales-management.html

 

 

 

 

This colourful presentations accommodates hundreds of sales management data items in a meaningfully organized display allowing patterns and exceptions to be spotted immediately. The size of the rectangle refers to "Total Sales" while the colour attribute represents "Sales result %". 

When the colour and size dimensions are correlated in some way with the tree structure, one can often easily see patterns that would be difficult to spot in other ways, such as if a certain colour is particularly relevant.

 

 

 

 

 

 

 

 

 

Visual Storytelling in Education - VISE Project

Statistics eXplorer is applied in our research project that focuses on learning based on Knowledge Visualization and Geovisual Analytics Statistics in the VISE (Visual Storytelling in Education) research project. VISE supports the use of learning for these focus areas:

• Implementation and evulation of applying of geovisual analytics and knowledge visualization in education;
• Study how visual storytelling methods can improve the student's learning process in development of knowledge and better understanding of statistics data;
• The students’ experiences when employing geovisual analytics for big statistical data in their learning process;
• Introducing a geovisual analytics to teachers with the aim to develop their knowledge about visual storytelling methods;
• Conducting research concerning teachers’ experiences and students learning processes when our visualization tools are used within education;

The visual storytelling process available in “Statistics eXplorer” will be applied to improve the students knowledge and understanding of sophisticated statistical relations. Teachers will be able to, individually and together, develop a dynamic teaching material through storytelling, through the web. Students will be able to, with help of powerful geographical statistics, explore statistical relations on their own. A better understanding of how educators and their students can elicit deeper user understanding and participation by exploiting dynamic web-enabled statistics visualization is of importance. Together with the associated science of perception in learning in relation to the use of multidimensional spatio-temporal statistical data this will contribute to the research fields of Geovisual Analytics as well as educational science.

VISE has received financial support for 2015-2017 from VINNOVA (Swedish government agency) 1 milj Skr, Vetenskapsrådet (Swedish Research Council) 4,5 milj Skr, and Norrköping Kommun 1,6 milj Skr.

More information about VISE.

Other NCVA Research Projects

 

 

 

 

 

 

 

Collaborative Partners

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NCVA and from 2010 spin-off company NComVA have collaborated with statistical organisations including SCB Statistics Sweden, OECD Paris, Eurostat, Norrköping Kommun, Linkoping Kommun and Göteborg Stad. But also industrial Ericsson Research in Linkoping and financial support for two industrial PhD students was provided by Unilever Research Port Sunlight UK and Swedish SMHI  (Swedish Meteorological and Hydrological Institute) Norrköping, and several European universities. Our visualization tools has during 2006-today helped these organizations to better understand the evolution of applying information visualization and geovisual analytics to multidimensional and multivariate data.

 

 

 

 

VINNOVA: "En forskargrupp på Linköpings universitet har i samarbete med bl.a. OECD, SCB, SKL, Danmark Statistik och Göteborg Stad utvecklat revolutionerande interaktiva "berättande" visuella metoder (storytelling) som enkelt kan publiceras i media som bloggar eller integreras i Web sidor och spridas till miljoner läsare genom bl.a. en annan samarbetspartner engelska tidningen Economist. Istället för en statisk bild så publiceras interaktiva bilder tillsammans med en förklarande text. Läsaren kan också själv interagera med visualiseringen och därmed kanske bättre förstå hur författaren har tänkt. Forskningsprojektet som bl.a. finansierats genom KK-stiftelsens visualiseringsprogram har vid flera utvärderingar demonstrerat en världsledande teknologi"

text

Demonstrators using Statistics eXplorer and "Vislets":

 

SCB Statistikatlas http://www.scb.se/statistikatlasen/

Haldersson Marie (SCB), Andersson Jonas (Göteborg Stad): "The benefits of visualization - how to eXplore a municipality",http://ncva.itn.liu.se/resources/publications/1.542529/ISI2011_Thebenefitsofvisualization-howtoeXploreamunicipality.pdf

Eurostat - Collaboration with Eurostat started in 2012 and spring 2013 this web site was published:

http://epp.eurostat.ec.europa.eu/cache/RSI/

OECD Regional Statistics - Collaboration with OECD started in summer 2008 - The first version of OECD eXplorer was published om the OECD web site and created a lot of attention. This public OECD eXplorer web site has more than 50,000 visitors per month. http://www.oecd.org/gov/regional-policy/regionalstatisticsandindicators.htm

OECD Region-at-a-Glance" interaktive report describes the regional development in the OECD countries.  The interactive report is available at http://rag.oecd.org/

 

Our Litterature about statistics visualization:

• Jern M, Thygesen L, Brezzi M: “A web-enabled Geovisual Analytics tool applied to OECD   Regional Data”, Reviewed Proceedings in Eurographics 2009, Munchen, March 2009 - Web-enabled Geovisual Analytics tools applied to OECD regional data Eugr2009.pdf
• Jern M, Thygesen L, Brezzi M: "Storytelling - How to visualize statistics", Reviewed paper, NTTS 2011 (New Techniques and Technologies for Statistics), international scientific conference on the impact of new technologies on statistical collection, production and dissemination systems, Brussels, February 2011 NTTS 2011 Storytelling - How to visualize statistics.pdf
• Quan Ho, Lundblad P and Jern M, "Geovisual analytics framework integrated with storytelling applied to HTML5", International Conference AGILE 2013 – Leuven, May 14-17, 2013. Geovisual Analytics and Storytelling Applied to Regional Statictics Using HTML5 - Agile Short paper.pdf
• Lundblad P and Jern M. “Visual Storytelling in Education applied to Spatial-temporal Multivariate Statistics Data”. “Expanding the Frontiers of Visual Analytics and Visualization”, Editors Dill J, Earnshaw R, Kasik D, Vince J, Wong P.C. (Eds.), May 2012 Springer 2012, SBN 978-1-4471-2803-8. 

 

Page manager: mikael.jern@liu.se
Last updated: 2017-12-08