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National Center for Visual AnalyticsNCVA Logo

Welcome to the "Geovisual Analytics Educational Web site"

Swedish Web site: http://ncva.itn.liu.se/?l=sv

mikael pionjär

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 (KK-Stiftelsen) Visualization Program and VINNOVA (the Swedish government agency that administers state funding for research and development). Financial support for two industrial PhD students was also provided by Unilever Research Port Sunlight and SMHI (Swedish Meteorological and Hydrological Institute).

NCVA - Concept and Idea

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".

The overall objective of NCVA is to promote within education and research Geovisual Analytics in particular but also the more general Visual Analytics. 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 innovative Geovisual Analytics techniques have been developed and used to build prototype visualization applications that educate academia with demonstrating and educational tools.


"Our mission is 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"

geovisual analytics

Figure: Geovisual Analytics comprises several research topics including information visualization, geographical visualization, perceptual science and storytelling etc. Geovisual Analytics.png - These methods are all implemented and available in our Statistical eXplorer applications.



Interactive Statistical Visualization with integrated Storytelling

Statistics eXplorer, developed by NCVA in collaboration with its spin-off company NComVA, is a collection of web compliant applications that enables the statistics visualization of socio-economic information at national or detailed territorial level providing 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 eXplorerEurope eXplorerSverige eXplorer and the more general Mdim eXplorer.  You can load your own data (EXCEL etc.), analyse, gain insight and create your own stories to be shared - see figure below.

World eXplorer

FigureThree linked and coordinated views covering the following visualization methods (choropleth map representing the indicator "age group 65+" , the extended scatter plot shows four indicators "age group young 0-14" (Y-axis), "age group 65+ (Y-axis), "age group 65+" (colour) and dot size is related to the indicator "total population". The fish eye bar chart uses a focus&context method to highlight about 20 countries (bars in focus) representing countries with highest rate elderly people in 2014 while the remaining 270 countries (context) are displayed as thin bars. The bars are coloured according to the active colour legend ("age group 65+") and applied in all three views. Three conuntries (Japan, Sweden and Niger) are highlighted in each of the tree views. The Story in the right panel represents our Storytelling method and controls how eXplorer will be initiated including selected visualization methods, colour legend, selected countries, time step, etc. 

Read about World eXplorer http://ncva.itn.liu.se/explorer/world-explorer    World eXplorer is loaded with national data in EXCEL format (see figure above) or access latest statistics data directly from the integrated World Databank.

Use MDim eXplorer with any table data (NO geographical reference) http://ncva.itn.liu.se/explorer/mdim-explorer

Read more about data formats at: http://ncva.itn.liu.se/explorer 


storytelling loopFigure:                  analytical storytelling loop  Statisticians with diverse backgrounds and expertise participate in a creative discovery processes that transform statistical data into knowledge. Our Storytelling tools integrate this geovisual analytics process using collaboration. This knowledge exchange process develops a shared understanding with colleagues and, after consensus has been reached, the story can 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. 


Statistical eXplorer Visualizations

FigureThe Statistical  eXplorer visualizations facilitate information and geographical visualization methods (e.g., choropleth maps, bar charts and histograms, table lens, parallel coordinates plots “profile plots”, scatter or "bubble" plots, scatter matrices, time graphs, treemap, and pie graphs but also flow maps - all methods applied and customized for statistics data. They also show hidden data or trends. The distribution plot 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.



Fisheye Lens technique in bar charts enhances large statistical data

World IndicatorsHere is an example of an important visual technique that has evolved from Information Visualization: the Fisheye Lens technique that magnify 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 below with the following world indicators.

Fish eye bar chart











Figure: Interactive Fisheye Bar Chart at: http://ncvademo.blogspot.se/2015/03/the-world-databank-indicators.html

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



Parallel Coordinate Plot applied to statistical data

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.

World PCP explanation


Statistical eXplorer introduces to the statistical community the PCP method originating from Information Visualization research. PCP is a proven visualization technique for identifying trends and cluster in many scientific environments and has now also been adopted, evaluated (OECD and its many users) and appreciated by many in the statistical community. Our PCP enables visual representation of large spatial-temporal multivariate data and hence is becoming an important mechanism in Statistics Analytics.

A special advantage of the NCVA 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. 


  OECD Regional eXplorer - A successful collaboration with OECD since 2008


'I have always believed that the very best results in dynamic visualization - the truly breakthrough innovations - are the results of cross-disciplinary collaboration. The NCVA OECD joined project brings together 'right brain' statisticians with the 'left brain' visualization designers. The interactions are incredible!'

 OECD Chief Statistician Enrico Giovannini

From an international perspective, our research builds on collaborating work with OECD since 2008. See Springer paper 2009:  Collaborative Web-Enabled GeoAnalytics Applied to OECD Regional Data


Between 2010-2013, the spin-off company NComVA supplied advanced and innovative statistics geovisual analytics technology to this organization http://stats.oecd.org/OECDregionalstatistics/ and http://rag.oecd.org/. Another important user is the European Commission that have used Statistics eXplorer since 2009 for internal analysis of data from Eurostat. In 2012, Eurostat decided to license the HTML5/JavaScript technology and tools from the spin-off company NComVA.

OECD eXplorer EU TL3Figure: Regional eXplorer "ageing population in regional TL3 Europe" http://stats.oecd.org/OECDregionalstatistics - 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.


oecd factbookFigure: "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/#


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 data from Eurostat.

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.

Eurostat unemployment rates 2014

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


Eurostat Economy NUTS3

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

Other tools and 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

Learn more about the visualization tools used in this NComVA/NCVA dashboard application at:
An oveview of available Eurostat visualization tools:

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



Collaboration with 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/

Statistikatlas SCB

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:



The OECD Flow Map eXplorer Trade Demonstrator

The data which represents a movement from an origin to a destination is defined as flow data. There are many examples of flow data including commutingmigrationtrade and flows of money that have drawn much attention of policy makers, city planners, researchers and ordinary citizens as well. This kind of data is two-dimensional relationship data; thus, it is normally large.

NCVA introduces an interactive Flow Map eXplorer demonstrator based on the large OECD Trade data set that effectively can explore spatio-temporal and multivariate trade statistical flows (Export and Import) data using bidirectional flow arrows where both in-coming (import) and out-going (explort) flows can be clearly shown. This applied research task is based on a collaboration between OECD and NCVA/NComVA.

The OECD Trade Flow Map eXplorer demonstrator provides interactive trade flow visualization of the OECD countries based on two flow types (Import, Export) for more than 4000 commodities, 21 time-steps and more than 200 countries. The flow interaction data table for only one focus point represents more than 1GB. The large trade data is cut into smaller more manageable data files, providing true interactive performance , where each interaction data table represents an origin point (for example, USA below), a combination of a destination points (countries) , selected commodities and all 21 time-steps. The reason of this data management is that normally a user needs to focus on 1-5 selected origins (countries), a few selected commodities but wants to analyse the data of all flow types (compare import and export), for all time-steps (to find pattern over time) and from/to all countries (to find the biggest flows).


OECD Flowmap Trading Export-Import USA

Figure: The OECD Flow Map eXplorer for Trade Data demonstrator with the Origin USA and all countries as Destination showing Total Trade (import, export and Net) for 1988-2008.The map shows flows for the "Top 10 Flows" and the bar chart shows Total "Export", "Import" and "Net" for all countries.


The OECD Trade demonstrator is available at: http://mitweb.itn.liu.se/GAV/flowmaptrade/

Read more about our flow Visualization technology in this research paper: Flow Map - STGIS - Paper.pdf

More about Flowmap eXplorer at: http://ncva.itn.liu.se/explorer/flowmap-explorer


NCVA started Research related to Storytelling already in 1999 called "SmartDoc"SmartDoc

SmartDoc was our first implementation of Storytelling and integrates interactive and collaborative visualization into reports in MS Word format. The normal contents of a report, text and images, are extended with interactive 2D/3D visualization. Data and bookmarks are integrated into the document structure, which make the SmartDoc just as easy to handle as a traditional document. The reader is given a more active role and can interact with the embedded data in order to gain a better understanding of the report’s contents. First publication:

Jern: “Smart Documents with ActiveX 3D Data Visualization Components”, reviewed article in “Digital Media: The Future”, Vince J. A., R. A. Earnshaw (Eds), Springer Verlag March 2000, ISBN 1-85233-246-8.

As social creatures, we love telling stories and sharing them in a good laugh with others. It doesn’t matter how dry or boring the subject inherently is. If someone can tell a good story, others will listen and enjoy it. Analytics visualization experts are challenged to elicit a strong engagement and wonder in our stories stimulating the readers’ curiosity making them want to learn more and convey a deeper meaning.

A picture is often worth a thousand words, an interactive visualization is worth a thousand pictures but interactive storytelling provides the true difference and that is "understanding" and "knowledge"

A storytelling mechanism assists the author to improve a reader’s visual knowledge. Authors can develop interactive educational material based on the 4Ws concept “What-When-Where-Why”. A story is composed of texts and visual representations together with snapshots, metadata, hyperlinks and references providing answers to the classical 4Ws questions (see figure below): “What” is the data? The data are shown for a given time step - “When”? Moreover time series can be viewed interactively and simultaneously in the in the linked graphs; “Where” is mostly considered in regional comparisons. “Why” is the most important aspect of the story and explained in the metadata text section together with snapshots and hyperlinks that enable users to further analyse aspects related to topics and are helpful tools for both specialised and non-specialised users.



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


World eXplorer Publishing

Figure: Storytelling facilitates three complementary characteristics: explore and gain insight, tell-a-story and publish (Vislet) which finally can be embedded in a web page/blog using the HTML code. 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 1968-2013.  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. 


Interactive Figure: World eXplorer with 3 time-linked views showing indicators related to countries of the world “ageing population in world” during 1960–2013; 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. 

Try also the Mobile HTML5 version http://ncvademo-mobile.blogspot.se/2015/02/worlddatabank1968-2012-mobile.html

NOTE: Some indicators are NOT available for the last years and you might have to move the TIME SLIDER.

More Vislets (using Flash) is available at: http://ncvademo.blogspot.se/


interactive doc












Figure: Try also these two interactive documents from OECD and ISTAT. 

http://noi-italia2013en.istat.it/ and http://rag.oecd.org/


Linked and Coordinated Choropleth and Treemap

This European treemap visualization shows hierarchies in which the rectangular screen space is divided into several hundreds European statistical NUTS2 regions. Each region belongs to a country in the hierarchy. This colourful presentations accommodates thousands of statistical data items in a meaningfully organized display allowing patterns and exceptions to be spotted immediately. The size of the rectangle refers to "Total Population" while the colour attribute represents elderly population in Europe "age group 65+ in %". 

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. We see that Germany has a high rate of eldery people while, for example, Poland has a younger representation 

Try this Dashboard Demonstrator: http://mitweb.itn.liu.se/GAV/dashboard/#story=data/nuts-regions-ageing-population-in-europe-2010.xml&layout=[map,treemap] or this with 3 linked views incl a fish eye bar chart:

http://mitweb.itn.liu.se/GAV/dashboard/#story=data/Ageing Population in the World.xml&layout=[map,(treemap,barchart)]

A special advantage of the treemap is that, by construction, it makes efficient use of screen space by displaying thousands of data items on the screen simultaneously.

treemap EuropeFigure: High resolution: Choropleth Map with small pie charts (age 0-14 vs. 65+) and Treemap visualization showing "Age Group 65+" in Europe for NUTS2 regions". Coloured rectangles in the Treemap represent the ratio of elderly people ("age group 65 and above"). The size of each rectangle in the Treemap represents the "Total Population". 

We know that the EU population is getting progressively older as a result of a significant and continuous increase in life expectancy at birth, combined with low fertility rates and the entry into retirement of the post-World War II baby-boom generation. The linked and coordinated treemap and choropleth map below presents information for the 270 NUTS2 regions in the EU with the highest and lowest shares of elderly persons (aged 65 and above) and their respective populations. A Storytelling panel in the interactive demonstrator gives a textual background and provides some snapshots.

To see the hierarchical structure. You must first set the treemap options as seen on this picture:

Tot Pop

Pop 65+

Group by: Country



In the treemap below - focus is restricted to only  regional Germany. A City Dusseldorf with 5,2 million people is represented by a small geographical area in the map but in the treemap - a larger rectangle represents Dusseldorf based on the size of its population and the darker red colour represents an ageing population of 22%.'

treemap focus Germany



World Data Demonstrator Dashboard using HTML5 Visualization

Below is a World Map Dashboard with three coordinated and linked interactive views map, treemap and parallel coordinates 

World Map DemonstratorThis World Map Dashboard with three linked and coordinated views is available at:  http://mitweb.itn.liu.se/GAV/dashboard/#story=data/Ageing Population in the World.xml&layout=[map,(treemap,pcp)]


Example of NCVA Research Projects 


NCVA applications
Figure: Examples of NCVA  Geovisual Analytics applications produced in collaboration with partners during 2006-2013. 


Collaborative Partners

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 and SMHI  (Swedish Meteorological and Hydrological Institute) Norrköping, and several European universities. Our visualization tools has during 2006-2013 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"



Page manager: mikael.jern@liu.se
Last updated: 2015-11-26