Key Takeaways from the Data Visualization Society’s Outlier 2021 Conference

Data Visualization

The Data Visualization Society’s (DVS) first conference Outlier 2021 took place on 4th, 5th, and 7th February 2021. It was organized as an online conference, joined by about 1000 participants from their computer screens all over the world. 41 main talks, about 20min each, were presented, as well as dozens of smaller sessions.

Talks were distributed within a large time window, suitable (or not) for people in different time zones. I was only able to participate in full on sunday the 7th. But due to the presentations being prerecorded, and made available as videos immediately after each talk, I was able to see every talk.

To profit the most from this event, and process it in a structured way for myself, I shortly summarized the key takeaways from the talks. These summaries are listed below. The talks I found most interesting are summarized in more detail than the others. Unfortunately the very short summaries do not do justice to these also great talks. So, I encourage you to also see these video in full if their topics interests you.

To process the content in retrospect, it also made sense for me to regroup the talks into categories. Categories that emmerged are: general methodology, tools, history, data art and experimental case studies, and case studies. My interest mainly lay in the methodological talks, followed by presentations of tools. The talks on data visualization history and data art provided some lighter content in between. The enormous breadth of case studies greatly contributed to the diverse and international atmosphere of this event. The talks that I most recommend watching in full are marked with an asterisk* below.

The full list of talks is also available as a youtube playlist. The list contains a few additional talks not mentioned below on organizational issues of the Data Visualization Society as well as several 5-minute short so-called lighting talks.

Data Visualization General Methodology

How to Get Your Organization to Value Data Visualization – And You! (Steve Wexler)* (watch video)

Steve Wexler demonstrated how to convince people of the power of data visualization in company environments were people are still working with raw numbers in spreadsheets. By showing examples and asking questions people can experience for themselves that data visualizations allow to find answers much faster than tables. Dashboards can be made more attractive for people if they can see their own relative position in the data. Needless discussions about chart types and color choices can be avoided by having experiments at hand demonstrating your point, such as estimating the relative sizes of bubbles/circles versus bars.

Soft Landing, Firm Impact: Practical Tips on How to Give and Receive Meaningful Data Visualization Feedback (Candra McRae)* (watch video)

Candra McRae gave practical tips on how to give and receive feedback. When giving feedback one should be self-aware of one’s tone, body language, and biases. Personal opions should be voiced in the form of „I“ and „me“. It is better to give feedback in a one-on-one setting than in a group. One should first seek to understand why things were done in a certain way. The given feedback should be clear and honest but also kind. Dataviz experts‘ (Tufte, Few) stances should not be used in a discussion. When receiving feedback one shouldn’t shut down and be argumentative. One should ask engaging open questions. It is also important to act upon the given feedback.

Side Projects (Jan Willem Tulp)* (watch video)

Jan Willem Tulp elaborated what makes good side projects in data visualization. Such projects serve to learn something and to show something. For data visualization designers starting out, such projects usually serve to fill the portfolio. But they also make sense for seasoned professionals, because they can lead to paid projects. Side projects provide the opportunity to fully do you own thing, with your ideas, creativity, and skills. It is recommended to keep a notebook/spreadsheet of ideas and interesting datasets. Good side projects are relevant and original. Relevance can be achieved by using a well-known dataset, treating a current event, and by allowing people to find themselves in the data. Originality can be achieved by collecting one’s own data, redesigning an existing visualization, trying a new visualization concept, visualizing uncommon questions, and by creating engaging design people spend more time with. Mr. Tulp then discussed how his own and other people’s side projects meet the criteria of relevance and originality.

My Statistic Enemy, or Why Difficulties Make Better Data Visualization (Julie Brunet)* (watch video)

Julie Brunet explained how she cooperates with people with different skillsets. The basic idea is to manage that which you don’t know. People in the data visualization community have very different backgrounds. There is a temptation to try to learn to do everything by oneself. But a better approach is to cooperate with people that have the skills that one lacks for a project. People can thus alternately take the lead for different parts of a project.

Personal comment: The slides of this presentation were probably the most beautiful of the conference.

Data Viz, the UnEmpathetic Art (Mushon Zer-Aviv)* (watch video)

Mushon Zer-Aviv discussed how empathy can be achieved in data visualizations. Humans easily empathize with individuals but not with masses. Research has shown that people are willing to donate more than double the amount to save an individual (identifiable life) than to save the many (statistical lives). Even when the statistics are just shown aside the individual fates, the donations go down. This is called statistical numbing. Daniel Kahneman wrote about two systems of thinking. System 1 is fast, automatic, and involuntary, system 2 is slow, effortful and deliberating. Often system 2 rationalizes in retrospect, what system 1 has perceived. Empathy can be located in system 1. Or, speaking in data visualization terms, it can be called a preattentive attribute that focuses our attention. A good approach to reaching empathy with data visualization is thus to start with the individual fate and then zoom out to the bigger picture. But it is not enough to simply rouse people, there must also be a specific call to action. Not just the status-quo should be shown, but also the better situation that could be.

Personal comment: Especially in the Covid crisis, where statistical data represents thousands of deaths, this is a very pressing topic. Many great examples of empathic and unempathetic data visualizations have emerged in this context.

3 Languages, 3 Aesthetics, 1 Graphic: A Case Study of Visualization in a Multicultural Environment (Nilangika Fernando)* (watch video)

Nilangika Fernando explained how she takes three different cultural aesthetics in Sri Lanka into account when designing data visualizations. The official languages of Sri Lanka are English, Sinhala, and Tamil. When she published data visualizations from an English context, translated into Sinhala, they would get little traction in Sinhala media. Looking at newspaper frontpages she noticed that each language and culture has it’s own look and feel. Newspaper try to make their frontpage as attractive as possible to the given audience, so they can be used to determine wether an audience has a different design aesthetic. These specific aesthetics could also be seen in online-memes of the different cultures. To analyze an aesthetic one should look at the layout, color, font, images, and narrative. Icons need to match the cultural context. For instance, a savings box in the form of a pig would not be understood in Sri Lanka, or even be considered offensive. Also, the hair and eye color of icons should be appropriate. Then she explained how to bridge this visual gap. She creates the infographic in the language of the primary audience, and then translate them into the others. She works with collaborators who are based in the different cultures. Finally she explained how data visualization can be presented in a non-data culture. She advised to use serve infographics in small doses, give a finished product that is attractive to publish, and to use storytelling.

Mind Games: The Psychology Behind Designing Beautiful, Effective and Impactful Data Viz (Amy Alberts)* (watch video)

Amy Alberts talked about results of user research at Tableau. Using eye trackers she analyzed how people perceive dashboards. Such eye tracking studies are in themselves data visualizations because the results are shown and analyzed as gazeplots, heatmaps, and gaze opacity maps. Given 10 seconds people focused their attention especially on big numbers, high color contrast, pictures of humans, and maps. People also tended to read the dashboards starting in the upper left corner moving right and down. When the viewing duration was increased, the viewing patterns remained largely the same. But when a specific task was given when viewing a dashboard, the patterns fell apart. So humans are on the one side dumb monkeys, looking with little actual intent, but on the other side also very intelligent in navigating systems to reach a goal. These result are in line with UX research. The mentioned attention-getters can be used purposefully for designing dashboards, notably taking up corporate design elements. Priming can be also be used to focus attention, by saying or writing something related to what you want people to focus on before showing the dashboard.

Are Your Data Visualizations Excluding People? (Larene Le Gassick, Sarah Fossheim, Frank Elavsky) (watch video)

Larene Le Gassick, Sarah Fossheim and Frank Elavsky explained how data visualizations can be made more accesible to people with vision impairment and blind people. They argued how everyone, also people with good vision, profit from more accessible data visualizations.

Iron Quest: Lessons from the Community (Sarah Bartlett) (watch video)

Sarah Bartlett gave tips on how to succeed in the Tableau Ironviz challenge. She recommends to visualize what one loves, build own datasets, use an exploratory or declarative approach, and provide context to the shown data.

Data Designer: A Self Portrait (Valentina d‘Efilippo) (watch video)

Valentina d’Efilippo gave tips on working as a data designer she wishes she had known when she started out herself. She recommends to see design as a problem-solving mindset, not box oneself in and embrace the chaos, tap into other’s brains to create empathy, learn to say no, feed one’s brain with creative things, raise one’s own personal voice, and listed to one’s gut.

Labels Matter (Gaelan Smith) (watch video)

Gaelan Smith discussed how labels and categories used in data gathering can include and exclude people. He explained how adding categories can make room for diversity.

Beyond Word Clouds: Visualizing the Linguistic Patterns of Political Speeches (Riva Quiroga) (watch video)

Riva Quiroga presented her analysis of presidential speeches in Chile. Among other analyses, she showed how the punctuation of speeches with many exclamation marks indicate authoritarian presidencies.

Using Zipf‘s Law to Help Understand COVID-19 (Howard Wainer) (watch video)

Howard Wainer showed how Zip’s Law can be used for outlier detection. Many natural processes follow a distribution where the frequency of occurence of an observation is inversely proportional to its rank (according to frequency of occurrence). When a process follows this distribution, outliers can easily be detected that deviate from it.

An Odd Couple’s Journey Towards SciArt: Design Meets Science and Vice-Versa (Greta Carrete Vega, Estefania Casal) (watch video)

Greta Carrete Vega and Estefania Casal discussed how they work together as a scientist and designer. Among other things they showed a model by Min Basadur on roles required in creative problem solving: the generator, the conceptualizer, the optimizer, and the implementer. Casal, the designer, likes to generate ideas and concepts. Vega, the scientist, likes to get things done practically. Thus, they complement each other as collaborators.

Creative problem solving profile according to Min Basadur (Source: Greta Carrete Vega, Estefania Casal: Outlier 21 presentation)

Data Viz for Non-Profit (Guillermina Sutter Schneider, Luis Ahumada) (watch video)

Guillermina Sutter Schneider and Luis Ahumada explained how non-profit organizations can work with data visualization. They recommend to develop a style guide for an organization in order to give the created charts an uniform and recognizable look.

Data Visualization Tools

Going Beyond Matplotlib and Seaborn: A Survey of Python Data Visualization Tools (Stephanie Kirmer)* (watch video)

Stephanie Kirmer provided an overview of six Python data visualization libraries. She included the older standard libraries Mathplotlib (2003) and Seaborn (2012), and the newer libraries Bokeh (2012), Altair (2016), Plotnine (2017), and Plotly (2013). The target criteria she wanted libraries to meet are an easy learning curve, consistent grammar, flexibility, beautiful output, and interactivity. She tested each library with a set of standard charts, and then discussed how the target criteria were met. She advises against using the older libraries. In conclusion she showed for which individual target criterion which of the four newer libraries should be used. For an easy learning curve: Plotnine or Altair. For consistent grammar: Plotnine or Altair. For flexibility: Plotnine or Bokeh, For beautiful images: Altair or Bokeh. For interactivity: Plotly or Bokeh. Generally, Altair is only suitable for small datasets.

Srengths of different Python graphics libraries (Source: Stephanie Kirmer: Outlier 21 presentation)

Navigating the Wide World of Data Visualization Libraries (for the Web) (Krist Wongsuphasawat)* (watch video)

Krist Wongsuphasawat explained a framework for choosing data visualization libraries for the web, mainly Javascript libraries. He located libraries within a two-dimensional design space. The x-axis is the level of abstraction from 1 to 5. The y-axis are different categories of API design. Level of abstraction 1 is graphics libraries working on a low level. P5.js, Three.js, and Two.js fall into this category. Level 2 is low-level building blocks. D3, visx, cola, dagre, and others belong into this category. Level 3 is visualization grammars. Vega-lite, Chart Parts, Muze, and G2 are part of this category. Level 4 are high-level building block. Echarts, Highcharts, Plotly, Victory, React-Vis, and Semiotic belong into this category. Level 5 are chart templates. Chart.js and Nivo are part of this category. The other dimension, API design, consists of the categories JSON, JSON with callback, plain Javascript, and framework specific. He then showed how the different libraries are located within this dimension. He then explained how to choose a library. It should allow you to create what you need (custom, rare, or common data visualizations) within the time you have. Familiarity with a specific library plays a role here. Technical aspects that can be considered are performance, the used tech stack, and project lifespan (maintenance of the library in the long term).

Note: Krist Wongsuphasawat has also published a corresponding Nightingale article.

Design Space of data visualization libraries (Source: Krist Wongsuphasawat: Outlier 21 presentation)

ggplot Wizardy: My Favorite Tricks and Secrets for Beautiful Plots in R (Cédric Scherer)* (watch video)

Cédric Scherer explained how he creates print-ready charts entirely programmed in R with the ggplot2 library and extensions. He refined his R skills mainly within the weekly TidyTuesday challenge. The R community shares extension packages for a big variety of graphs and extra functionalities. He then demonstrated the capabilities of the extension packages he regularly uses in his work. The package ggtext provides improved text rendering. The package ggforce provides annotations. The package ggdist is useful for visualizing distributions and uncertainty. Then he showed several tips for improving charts within the ggplot2 library by changing default parameters. Plot-titles and plot-captions can be aligned with the outer margins. The legend can be placed at the top of the chart. The legend formatting can be improved. The axis labels can be placed closer to the axes. The clipping of elements that protrude beyond the borders of the chart, such as long labels, can be shut off. The outer margin between chart and border of the image can be enlarged. An image can be added to the plot to make it more illustrative. Finally he showed how the patchwork package can be used to combine and arrange several plots.

Data Visualization History

Otto and Gerd in the Chauvet Caves (Nigel Holmes)* (watch video)

Nigel Holmes explained how basic principles of information design can be traced back to early cave art. The earliest figurative cave art known to date is in Sulawesi from 45 500 years ago. Abstract marks from 70-100 000 years ago have been found in the Blombos cave. Such drawings might have been made by homo sapiens or other early homonids. Many of the known pictures of cave art are reproduced drawings, not actual photos of the art itself. Jumping forward to modern times, in the 1920s Otto Neurath and Gerd Arntz developed the Isotype graphic language to display statistical information. Neurath urged the artists to find the essence of the depicted object. Objects are shown in profile, from the side as a silhouette, omitting surface details. At first, icons were cut out from black cardboard, later they were printed as linocuts to obtain this simple appearance. A basic mechanism that is used in Isotype is to combine two icons into one. For instance, a waiter can be represented as a person with a coffee cup. The same principles of depicting the essential outline in sideview, and combining basic element into icons can be found in cave art. With combined elements, rhinos are shown wooly and with their summer coat. Thus it is valid to say that cave painter were the first information designers. “They were counting, recording, explaining, storytelling, while showing only the essentials.” Today the same principles can be found in roadsigns showing animal silhouettes, signs in airports, and emojis.

Florence Nightingale Is a Design Hero (RJ Andrews) (watch video)

RJ Andrews talked about the data visualization work of Florence Nightingale. Her charts were meant to be easily understandable and convince the army leadership of improving the medical care of soldiers. She worked together with several collaborators from different institutions.

Spotting Minard on the Corner Three (Senthil Natarajan) (watch video)

Senthil Natarajan demonstrated how he creates basketball data visualizations based on the styles of famous historic charts.

Data Art and Experimental Case Studies

3D Geo Dataviz: From Insight to Data Art (Craig Taylor)* (watch video)

Craig Taylor showed spectacular 3D visualizations of traffic data he develops at the company Ito. These cinematic visualizations serve to gather insight and for use as marketing material. He presented the project transit in motion which showed the change of patterns in public bus mobility during a Covid lockdown. He presented several possibilities of representing the data, some of which were quite experimental and artistic. Then he presented the project Europe’s quiet skies which shows the reduction of airplane flights in the Europe during the Covid crisis. In the Q&A session Craig Taylor explained that he uses QGIS and ESRI ArcMap for data preparation and visualizes the data using Houdini, Cinema 4D, and the Octane rendering engine.

Personal comment: This talk demonstrated the controversy around 3D data visualization and use of animations very well. On the one hand beautiful, spectacular images. On the other hand a way of presenting data that make it hard to derive deeper analytical insight.

Loud Numbers: Telling Stories with Data and Music (Miriam Quick, Duncan Geere) (watch video)

Miriam Quick and Duncan Geere gave an introduction to data sonification, which is the transformation of data into sounds. They also introduced their upcoming podcast Loud Numbers.

Data Through Design: Creating a Data Art Exhibition (Sara Eichner) (watch video)

Sara Eichner talked about the the Data Through Design exhibition taking place in New York. The exhibition shows data art based on New York open data. She discussed the challenges of exhibting data art in the corona crisis.

Using Data in a Fine Art Practice (Wilma Woolf) (watch video)

Wilma Wolf presented her physical data art and the processes and philosophy behind it. Her work focuses on women’s rights. It is important to her that high ethical standards are met during each manufacturing step of the art piece. She aims at the „death of the artist“, meaning that the final works stands for itself, without her as an artist being visible.

Step and Repeat: Visualizing Human Motion (Emma Margarite Erenst) (watch video)

Emma Margarita Erenst presented her physical data art works, mainly pieces of clothing, that deal with human motion and dance.

Coding with Fire: Cooking with Data (Ian Johnson, EJ Fox) (watch video)

Ian Johnson and EJ Fox talked about their streaming format where they do live coding of Javascript in observable notebooks.

Data Visualization Case Studies

A Viral Map (Karim Douieb)* (watch video)

Karim Douieb showed how he developed an animated visualization of the results of the U.S. presidential election of 2016. This animation went viral on social media. The animation visualizes the fact that land doesn’t vote, people do, by transitioning each state area to a bubble proportional to the population of the state. He presented a detailed walkthrough of how he developed this animation in Javascript, using the Observable working environment and the D3 library. He used a D3 force layout to distribute the bubbles, and Flubber for the animated transitions. He published his result as a looping gif on social media. The attention that his work received when posted by others exceeded that of his own posting. He noted that a watermark should be added, to avoid one’s work being shared widely without attribution.

Mapping the Covid19 Research Landscape: The Power of Data Viz over Black Boxes (Caroline Goulard)* (watch video)

Caroline Goulard presented a tool for visualizing scientific papers about Covid. There currently exist more than 50 000 publications on this topic. This make it very difficult for researchers to find the relevant ones. “Dark knowledge” is a big problem. 50 % of publication on Covid are not cited, 6 % are not in English. The currently available tools such as Pubmed, Scopus, and Google Scholar only display search results as paginated lists. It is not transparent how these ranked lists were generated. Also the user needs to precisely specify what he is looking for. Caroline Goulard proposes spatial mapping as part of the solution. This helps get a mental representation of the data, helps interaction, and helps memorization. They developed two approaches. The first approach is a citations network graph, implemented via a force-directed graph. The second approach is a dimensions reduction map. Here publications that have similar keywords are located closer together in two-dimensional space. This replicates walking through a library and looking into the nearby shelves. This second approach was favored by interviewed users. Clusters of publications were created using hierarchical clustering. Each cluster was assigned a color. In the interface colors can also be assigned to years of publication, fields of study, and keywords. The interface also allows to look at the detailed metadata of each publication. In user testing it was found that people mainly use search functionalities, and then look at the map for confirmation. Users found using the tool a “disturbing experience”. So a sexy interface will not guarantee, that a tool will actually be used next time, instead of the standard tools. In the Q&A section Caroline Goulard explained that the application was programmed with WebGL and the HDBSCAN library.

How Do We Translate Cultural Experiences Into Data Stories? (Mick Yang, Isabella Chua) (watch video)

Mick Yang and Isabella Chua explained how they develop data stories at the Kontinentalist, a Singapore-based data journalism agency. The agency focuses on data stories dealing with asian culture. They advocate to have the courage to be niche and local in the data stories one tells.

Narrating a Nation Through Numbers – India in Pixels (Ashris Choudhury) (watch video)

Ashrin Choudhury presented his work on visualizing data on India for an Indian audience. He asks for feedback from several colleagues of diverse ethnical and regional backgrounds, in order to avoid cultural pitfalls.

Data Points Are People Too (Bronwen Robertson, Saja Hathman, Joachaim Mangalima, Zdenek Hynek) (watch video)

Bronwen Robertson, Saja Hathman, Joachaim Mangalima and Zdenek Hynek talked about their participation in different gloabal Data4change projects. They discussed how the covid crisis has impacted their work.

#BlackInDataWeek: Connecting and Celebrating Black People in Data Fields (Rith Agbakoba, Jarrett C. Hurms, Simone Webb) (watch video)

Rith Agbakoba, Jarrett C. Hurms, and Simone Webb presented initatives for black people working in data fields. They talked about the activities of BlackTides and BlackInData.

Visualizing the History of Mass Incarceration (Sarah Fawson) (watch video)

Sarah Fawson presented the results of her master’s thesis in which she visualized the history of mass incarceration in the USA. Her work shows that black men are disproportionately often imprisoned.

Visualizing Transgender Day of Remembrance: Lessons in Bearing Witness through Making Losses Visible and Visceral (Kelsey Campbell, Cathryn Ploehn) (watch video)

Kelsey Campbell and Cathryn Ploehn showed ongoing work where they visualize transgender people’s murderings.

Visualization of Violence in Colombia (Gustavo Ojeda) (watch video)

Gustavo Ojeda showed the data visualizations he is creating on violence in the Columbian society. Many people in Columbia do not have electricty and internet connection may be slow. He showed how data visualizations can be implemented technically to lower the amout of data transfered.

Are We Fine with Global warming? The Role of Nuclear Power & Low Carbon Energy (Harim Jung) (watch video)

Harim Jung discussed a dashboard where she showed CO2 emissions and electricity generation mix (renewable, fossil, nuclear) of different countries. Separating countries into four strata according to gross domestric product (GDP) shows that the countries with a high GDP emit a large share of global CO2.

Using DataViz to Re-sensitive the World to Animals (Karol Orzechowski) (watch video)

Karol Ozechowski demonstrated how he uses data visualizations to advocate for animals rights at Faunalytics. He identified three main problems in this field: problems of scale, problems of strategy, and problems of data opacity.

Shaping Data Viz through Student Newsrooms (Raeedah Wahid, Jessica Li) (watch video)

Raeedah Wahid and Jessica Li talked about their work at the university student newspaper Columbia Daily Specator. They explain how their newspaper built up data visualization expertise in the last years.

Becoming a Data Driven Learner (Aminah Aliu) (watch video)

Aminah Aliu showed how she determined the best time of day for her to study as a highschool student. She timed the durations she needed to solve problems of the card game Set at different times of day. Thus she could show that she performed better in the morning.

At the conference Jason Forrest and Mary Aviles announced that Nightingale, the online publication of the Data Visualization Society, will also appear as a printed magazine.

Thanks to DVS Events Director Mollie Pettit and the rest of the volunteering organization team for this event: Duncan Geere, Evelina Judeikyte, Gabrielle Merite, Lloyd Richards, Maxene Graze, Marília Ferreira da Cunha, Frederic Fery, Céline Genest, Katy Liang,Jennifer Li, Bill Tran, Yi Ning Wong Isabella Chua, Akshit Aggarwal, Nöelle Rakotondravony, Naomi Smulders

Blog article history

22.02.2021 First version published. Additional talk summaries added in the following days and weeks.

21.03.2021: Added links to the now public youtube videos.

Phänologischer Kalender 2021

Data Visualization, Design

Für das Jahr 2021 habe ich wieder einen Kalender gestaltet. Der Kalender basiert auf dem Prinzip der phänologischen Jahreszeiten. Die zehn phänologischen Jahreszeiten werden aufgrund von Entwicklungsstadien von sogenannten Zeigerplanzen im Jahreszyklus definiert (mehr Infos siehe unten). Pro phänologischer Jahreszeit hat der Kalender ein Blatt, auf dem die zugehörigen Informationen zu Zeigerpflanzen und deren Entwicklungsstadien stehen, sowie ein impressionistisches Gemälde, das eine Landschaft zu dieser Jahrezeit zeigt.

Der Kalender beinhaltet die gesetzlichen Feiertage aller deutschen Bundesländer sowie die wichtigsten Festtage. Die bundeweit geltenden gesetzlichen Feiertage sind in rot markiert.

Der Kalender kann hier zum freien Ausdrucken für private Zwecke heruntergeladen werden:

Hier eine Übersicht zu den 11 Kalenderblättern:

Phänologischer Kalender 2021 Übersicht

Hier als Vorschau beispielhaft die Seite für den Erstfrühling:

Illustriert ist der Kalender mit impressionistischen Gemälden von Camille Pissarro (4x), Claude Monet (2x), Eward Willis Redfield, Pál Szinyei Merse, Isaak Iljitsch Lewitan, Olga Wisinger-Florian und Vilhelms Purvītis. Ich musste lange suchen, um für jede phänologische Jahreszeit ein passendes Bild zu finden. Camille Pissarro ist mehrmals vertreten, da seine zahlreichen Gemälde von Bäumen sich besonders gut im Jahreszyklus einordnen lassen. Bei manchen Gemälden ist es jedoch diskutabel, ob sie hier zur passenden phänologischen Jahreszeit gezeigt werden, oder nicht eine vorher oder nacher stehen sollten.

Der verwendete Font ist Jost von indestructible type. Es ist eine sehr gelungene freie open source Futura Variante, mit zahlreichen Schriftschnitten. Einziger Kritikpunkt aus meiner Sicht ist das nicht-geometrische kleine „a“.

Der Kalender wurde mit der open source Desktop Publishing Software Scribus erstellt.

Hier noch der erklärende Text zum Kalender, der sich auch im Kalenderdokument auf der zweiten Seite befindet:

Was ist ein phänologischer Kalender?

Im allgemeinen Sprachgebrauch wird das Jahr in die vier Jahreszeiten Frühling, Sommer, Herbst und Winter unterteilt. Einen deutlich differenzierteren Blick auf die Jahreszeiten erlaubt die Phänologie, also die Beobachtung der jährlichen Wachstumszyklen von Pflanzen. Frühling, Sommer und Herbst werden hier jeweils in drei Unterjahreszeiten unterteilt. Die zehn phänologischen Jahreszeiten lauten: Vorfrühling, Erstfrühling, Vollfrühling, Frühsommer, Hochsommer, Spätsommer, Frühherbst, Vollherbst, Spätherbst und Winter. Dieser Kalender hat je ein Kalenderblatt für jede dieser Jahreszeiten, wobei der Winter zweimal auftritt.

Definiert werden diese Jahreszeiten anhand der Entwicklungsstadien von sogenannten Zeigerpflanzen. Entwicklungsstadien, die dabei betrachtet werden, sind:

  • Beginn der Blattentfaltung
  • Beginn der Blüte
  • Erste reife Früchte
  • Beginn der Blattverfärbung
  • Beginn des Blattfalls
  • (Ende des Blattfalls (alle Blätter sind abgefallen))

Das Kalenderblatt für eine phänologische Jahreszeit zeigt jeweils die relevanten Entwicklungsstadien und Zeigerpflanzen. Diejenige Zeigerpflanze, die in Deutschland üblicherweise zur Definition der jeweiligen phänologischen Jahreszeit verwendet wird, ist in rot markiert.

Der Beginn der phänologischen Jahreszeiten ist von Region zu Region und von Jahr zu Jahr unterschiedlich. Der Kalender ist so konzipiert, dass idealerweise beim Beobachten der nächsten Jahreszeit zum nächsten Kalenderblatt weitergeblättert wird. Alternativ kann tendenziell etwas früh umgeblättert werden, sobald sich der erste Tag auf dem jeweiligen Kalenderblatt ereignet. Hier wird das Umblättern durch einen Pfeil am Ende der jeweiligen Woche angezeigt. Oder es kann tendenziell etwas spät umgeblättert werden, indem ab dem 1. März jeweils zum Monatsanfang umgeblättert wird.

Illustriert werden die jeweiligen Jahreszeiten mit impressionistischen Gemälden. Impressionistische Maler haben ihre Gemälde bevorzugt en plein air, also unter freiem Himmel in der Natur gemalt. So entstanden unmittelbare Landschaftsbilder zu verschiedenen Zeiten im Jahr. Bei Gestaltung dieses Kalenders war es nicht einfach, zu jeder phänologischen Jahreszeit ein passendes Bild zu finden. Viele phänologischen Erscheinungen, wie z.B. die allerersten Blüten im Erstfrühling, sind offenbar zu kleinteilig um ein gutes Motiv für impressionistische Farbflächenmalerei zu ergeben. Bei einigen Bildern ist es eine Interpretationsfrage in welcher phänologischen Jahreszeit sie gemalt wurden. Zeigt z.B. das Bild, das für den Erstfrühling gewählt wurde, Kirschblüten oder doch Apfelblüten? Wenn Sie selber zum Ergebnis gelangen, dass ein Bild zur falschen phänologischen Jahreszeit gezeigt wird, dann hat dieser Kalender seinen Zweck erfüllt.

Modernist Design Chairs: the Design Lineage of the IKEA Poäng

Data Visualization, Design

Recently I bought myself an IKEA Poäng as a comfortable armchair for reading. I’m quite fond of the chair. For the low price one gets a pretty classy looking piece of furniture.

In the Bauhaus year 2019 I had already learned a lot about modernist furniture design. Researching a bit more about the construction of the Poäng, with its cantilever construction made of bent laminated wood, it fascinated me that the chair could be linked to some of the most renowned designers and chair designs of the modernist epoch. Names that thus appear in the Poäng’s ancestry are:

The IKE Poäng is thus a good point of depart for discussing some basics about modernist chair design.

Just after finishing this infographic, I coincidently stumbled into a chair design exhibition in the Lippisches Landesmuseum Detmold. It was great to see all the iconic chairs named in the infographic there. The most renowned museum for chair and furniture design in Germany is the Vitra Design Museum in Weil am Rhein, which I also visited some years ago. The museum also has a great digital catalogue available. There even is a museum dedicated solely to cantilever chairs, the Tecta Kragstuhlmuseum in Lauenförde, which I hope to visit some day.

IKEA is known to sell variants of famous design classics. A variant of Alvar Aalto’s stool 60 is also available in the form of IKEAS stool Frosta. At the time of this writing, in August 2020, IKEA does not sell this model anymore, but similar stools are also available from other manufactuctures. They work beautifully as side tables for the IKEA armchair.

Below now the infographic showing the design linage of the IKEA Poäng armchair. The infographic can also be downloaded here as an A3 sized pdf for better viewing or printing.

Modernist Design Chairs: the Design Lineage of the IKEA Poäng

In the following, I want to add a few notes on the making of this graphic. Initally I started with a free flowing layout (see photo below on the left) but noticed that the large amounts of text, taking up more space than the pictures, would need careful planning. The basic idea was to use a modular grid with each picture corresponding to one and each text to two adjectent grid modules. Some puzzling was required to find a balanced arrangement (see photo below on the right). The content turned out to fit into a grid of 5 x 7 modules.

Sketches for planning the layout of the modernist design chair infographic

Paper cutouts were quite useful for testing different arrangements. The photo below shows the final layout I ended up using.

The screenshot below shows how layout ended up in Scribus. The baseline grid provides the underlying structure. Strictly following the modular grid structure looked quite clunky and cramped in many parts, so captions and text were indented. This lead to the forming of text columns that give structure to the infographic.

Modular grid and baseline grid used for layouting the modernist design chair infographic

Another interesting detail was the scaling of photos. These were gathered from different sources and thus had different dimensions. I wanted to display them correctly to scale. For correctly sizing them, I thus looked up or estimated their seat height and used this as a reference length.

Scaling of modernist design chair photos by use of their seat height

Visualizing Spatiotemporal Data with all Critical Mass Essen 2019 bicycle tours

Data Visualization

Geodata with timestamps can be beautifully visualized as animated maps. My main tool of choice for creating such maps up to now has been QGIS with the Time Manager plugin (examples see here, here, and here). Some time ago I came across another promising free and open source tool for creating such animations: The tool was developed by Uber to visualize and analyze mobility data. It is based on WebGL, a Javascript API for running interactive 2D and 3D applications in a browser. The tool is web hosted but all data remains within the local browser. No registration is required to use the web tool.

The most noticeable about is its cool futuristic mapping style. Below is a typical example map shown on the website:

The aspects that contribute to the futuristic appearance are:

  • The use of dark mode, i.e. a black or dark background on which bright content is displayed. (White/light backgrounds and satellite images are also available.)
  • The use of transparency and overlay effects which make the map content appear to emit light and glow on the dark background.
  • The display of 3-dimensional maps, with or without a height dimension, even in cases where a 2-dimensional display would be sufficient.

All these elements can be reconfigured, if a less showy appearance is desired.

The tool is quite easy and intuitive to use. It is still worthwhile to read through the entire user guide to be aware of all available functionalities. The main field of application for the tool seems to be the dynamic visualization of large spatiotemporal data and visual cluster/density analysis.

Point data can be directly visualized as Point or Icon layers. Origin destination data can be visualized as Arc or Line layers. Trajectories can be visualized as a Trip layer in a specific data format. GeoJSON files can be included as Polygon layers. Point data can be spatially aggregated/binned as Grid, S2 (a special kind of grid), Hexbin, and H3 (a special kind of hexbin) layers. The clustering of data points can be shown as Clusters or Heatmaps.

Data can be imported in CSV or GeoJSON formats with Web Mercator (EPSG:3857 – WGS8) coordinates. Own Mapbox styles can be integrated as backgrounds. Maps can be exported as images or as a standalone interactive HTML files. It is not possible to directly export videos. A separate screen recording software I necessary to record a video.

I tested the capabilities of with a dataset of all critical mass Essen bicycle tours of 2019. This data I logged personally as a participant of these tours. At critical mass events, large numbers of cyclists meet and drive through a city. This serves to raise awareness for cycling as a means of transportation. I have already used such logged tours several times to test different GIS animation technologies.

Here the final resulting animated maps:

Animated maps are fun to look at and to create, but are not always the best way of providing analytical insight. For pure analytical purposes they should be accompanied by static maps, and diagrams showing aggregated values (histograms, sums etc.). I discussed the advantages of animated vs. static maps in a previous blog post here.

Here a discussion of the main patterns that can be seen in these animated maps, and some additional contextual information:

The first animated map in the video shows all 12 tour itineraries. Tours start at 19:15 at the central Willy-Brandt-Platz in Essen and usually end there at about 21:00. Two tours ended at other locations were parties then took place.

The second animation shows the tours as moving dots. The dots are sized according to the number of participants. The number of participants in the months January to December were: 26, 82, 77, 66, 78, 160, 63, 51, 85, 84, 65, 15. These numbers were counted at the beginning of tours. Many particpants do not cycle along for the entire 2 hours. Most cyclists join the tour regularly, with a few infrequent and first-time cyclist joining every month. In cold and rainy weather (here: June, August, December) the number of participants significantly drops. In summer more casual cyclists and children join the tour. The tours that venture furthest away from the city center seem to be ones with a medium number of seasoned participants in decent weather.

The third, fourth, and fifth animation show the density of logged points in different variants. A high density of points was logged for the inner city ring. A trip down the Rüttenscheider Straße to the south is part of most tours. There are lots of restaurants and bars along this street which gives the tour lots of public exposure.

The sixth animation shows the logged speed. Overall speeds tend to be lower in the inner city area. In the outskirts speeds are higher with stops clearly visible at intersections. The slower overall speeds when cycling in the city also contributes to the higher density of logged points seen in the previous animations

The seventh animation shows the logged altitude. A clear south-north slope can be seen with the highest point of about 240 meter above sea level measured in the south, and the lowest point of 85 above seal level in the north. This isn’t much slope compared to other cities, but still makes cycling too exhausting for some inhabitants.

Here a few more notes on the technical details of creating these animations:

The used CSV file contains about 11 000 lines and has a size of 870 kB. The application runs smoothly with a file of this size.

The drawing order/layering on the map seems to be determined by the order in which the points appear in the dataset. So I reordered the raw data according to the timestamp, to make later logged points appear above earlier ones.

A filter needs to be defined for a field with timestamps to enable the time control. This is one of the few things I did not find self-explanatory. The timeline then runs from the earliest to the latest point in time appearing in the data.

I wanted the entire dataset to be successively added to the map, starting with an empty map at the earliest point in time. (In the QGIS Time Manager this is a standard feature called „aggregate features“.) A workaround to achieve this in is to add a dummy point to the dataset at a much earlier point in time, about the duration of the entire datasets time interval previously, and then adjust the time window to include the entire time interval of the dataset. As this sounds much more complicated than it is, here a screenshot with the resulting time control in the lower right:

Extracting a video in decent quality from the web interface proved to be more difficult than expected. After much tinkering here is the settings I ended up using:

On my small laptop monitor I reduced the scaling from 150 % (recommended default) to 100 % with a screen resolution of 1920 x 1080 px.

I adjusted the scaling in the browser (using Crtl +, Ctr ) and adjusted the zoom level of the web map to display an appropriate map section. There is no clear map window in the web interface that could be selected for screen recording.

I used CamStudio (a free open source screen recording software) to record the animation running in The default unsatisfying codec I replace by the Xvid codec. I set the quality to 70 %, capture frames every 20 milliseconds, playback rate 50 frames/second. I used a fixed region in CamStudio of 1280 x 780 px with no fixed corner. Selecting the region to record manually before every screen capture unfortunately lead to small deviations between recordings. I set the animation to 0,2x speed, to get a good quality screen recording.

Using Shotcut (a free open source video editing software), I cut the video files, sped them up by a factor of 4, and added the captions. The recording at slow speed and speeding up in postprocessing was the most crucial point in extracting a good quality video.

So, how does compare to QGIS with the Time Manager Plugin? seems to be a great tool for ad hoc temporal geodata visualization and visual density analysis. Creating a pretty visualization with the tool is surprisingly simple and fast. It is difficult though to break out of the given visual framework. So, for a visualization that requires the customization of many map elements, I would still prefer QGIS with its full mapping capabilities. The QGIS Time Manager exports frames with time information but no legend. can show both time and legend on the web interface, but these are not suitably formatted for a screen capture. In my case extracting usable videos from the web interface proved to be quite challenging. This should be less tricky when using more powerful hardware.

Designing Information Graphics for Different Audiences

Aesthetics, Data Visualization, Design

Information graphics should be designed for the target group they address. This is common good practice for any graphic design. The series of infographics shown below provide the rare opportunity to see the same informational content designed for four different target audiences: the age groups of preschool children, school children, teenagers, and adults.

These information graphics show instructions for thoroughly washing one’s hands. They are available as stickers to be stuck on mirrors in toilets. They are provided by the German Federal Office of Health Education (Bundeszentrale für Gesundheitliche Aufklärung) for download here, under a creative commons license.

Some of the choices made by the designer(s) can be a matter of debate. In any case the underlying principle is demonstrated very well: Text, fonts, imagery, and colors are chosen to make the information graphic suitable for the given audience.

Based on this principle, how could a corresponding information graphic for the elderly be designed?

Calender 2020: Seasonal flower illustrations by Pierre-Joseph Redouté

Data Visualization, Design

As in the two previous years, I again designed a calender for 2020. The calender shows seasonal flower illustrations by Pierre-Joseph Redouté (1759 –1840), who is considered one of the greatest botanical illustrators of all time.

The calender is freely downloadable as a pdf file and printable (for private use) on standard DIN A4 paper. It is available in three versions:

A good way of hanging the printed pages with standard office equipment is to use a (small white) binder clip (see example picture below). Magnets and pins also work of course. It’s also possible to only print indvidual pages out as they are needed over the year.

Here a preview of all calender pages:

And here an impression of how it looks with a binder clip on the wall:

For those who are interested, here some further background information on the making of this calender. With this design I continue to explore aesthetics I had already taken up in my previous calender designs. For 2018 I had created a calender combining (not very functional) Swiss-inspired typography and Japanese-inspired nature photography. For 2019 I had designed a minimalist functional calender inspired by Bauhaus watches. With the new 2020 design I tried to create a minimalist calender that was both functional and served decorative purposes. It combines Bauhaus/Swiss-inspired typography with natural aesthetics.

Normally I don’t enjoy looking at flowers very much, because in Europe they tend to be presented in the form of lush colorful bouquets and flowerbeds. But I do like it when singular or only few flowers are shown. In this presentation form the beauty does not only lie in the colorful blossoms, but in the entire form of the plant with blossoms, leaves, and stems. This way of presenting flowers can also be seen in the flower arrangements of Japanese Ikebana, and similarly in Japanese Bonsai. Similarly, the botanical illustrations of Pierre-Joseph Redouté show plants in a very lifelike, organically composed way.

For each month an illustration of a flower was selected that (approximately) blooms in that month. I didn’t want to select the „most beautiful“ plants, but those typically seen in gardens, fields, and woods in Germany over the year. Many of Redoutés illustrations are more beautiful than the subset I selected here. I had to make some trade-offs because I could not find all flowers I had on my initial list, especially the rarer fall and winter flowers.

The largest part of illustrations I found via the site The site links to scanned books from where I downloaded the individual pages. Getting the yellowed, faded and spotted images into a clean shape turned out to be more time-consuming than I thought. This making-of article by Nicolas Rougeaux contains some helpful tips on restoring old botanical illustrations. I ended up spending many hours with gimp, making heavy use of the fuzzy select (magic wand) tool, eraser, masking, automatic white correction and further color correction tools. The results are far from perfect but I’m still proud that my restored images look more balanced than what is commonly available on the internet (compare these Redouté images on rawpixel for example).

In the form of small selfmade icons (matching the „o“ in the used font), I added information on lunar and sun phases, which nicely fits the natural and seasonal theme. The font used is the open source font Spartan MB by Matt Bailey. Layouting was done with the open source desktop publishing software Scribus.

What board games teach about designing engaging data visualizations

Data Visualization

An article I wrote about data visualization and board games was published in Nightingale, the journal of the Data Visualization Society.

In the article I summarize my thoughts from a visit to the biggest tradefair for board games in the world, the Spiel (Internationale Spieletage) in Essen. Board game designers are really good at making representations of information and data engaging, fun and easily accessible. Many of the used principles can equally be used for data visualizationa:

  • Using easily readable encodings of data
  • Using overarching plots and metaphors
  • Making the graphic design fit the topic
  • Representing the data in physcial form (data physicalization).

The full article is available here, or click on the picture below: What board games teach us about data visualization.

What defines simple and minimalist design?

Aesthetics, Data Visualization, Design

In my own designs and those of others I admire, I keep gravitating towards the simple and minimalist. From my own experience I can say that such designs are rarely the result of a simple design process. Taking a straightforward approach usually results in a blunt and uninspired design. A lot of time and effort is required to get the details of a simple design just right in order to achieve a balanced, convincing result. Therefore I am always interested in understanding underlying principles of simplicity in design.

Traditional Japanese design I have been admiring for a long time. During this year, marking the centennial of the founding of the Bauhaus, I learned quite a lot new aspects about Bauhaus design (see my long blog article on characteristics of Bauhaus design). The design philosophies of these two movements are in many ways oppositional, with Japanese design favoring the natural and Bauhaus design favoring the technical and constructed. I asked myself: „How can Japanese design and Bauhaus design, which use oppositional design elements, both appear simple and minimalistic?“.

The infographic below answers this question. The minimalist design movements of Japanese design, Scandinavian design, Brutalist architecture, and Bauhaus designer are characterized by their typical use of forms, colors, and textures. This demonstrates that simplicity and minimalism are not tied to any specific design elements. Rather, a simple design results from the limitation to a small coherent set of elements.

Taking a look at the examples shown on my portfolio page, it becomes clear that I followed the approach of achieving a minimalist effect by using a reduced palette of design elements in most of my designs. Many of my previous blog posts can also be reinterpreted as treating specific simple and minimalist design themes:

There is no denying however that there are specific design elements more often associated with simple (graphic) design. Such simple and minimalis clichés that come to mind are:

  • Use of only black, white and gray colors, possibly with a few highlights in red
  • Use of muted brown colors
  • Black and white photography
  • Flat graphics, possibly contourless
  • Use of geometric sans serif fonts

The photo below shows an example that uses such typical design elements to great effect. The shown page is from the book Den Zweiten Weltkrieg verstehen (English edition: World War II: Infographics) illustrated by Nicolas Guillerat, authored by Jean Lopez, Nicolas Aubin, Vincent Bernard, published by dtv in 2019. The infographics are designed in a flat style reminiscent of Isotype, with a muted color palette. The pages are filled very densely with information, so it can be a matter of debate wether this is a good example of simplicity.

Very interesting results come from using elements not typically associated with simplicity. This results is a simple, yet also unusual and interesting composition. This is an approach I have only used sparsely in my work up to now. Examples are the use of bright orange color in this animation of a critical mass bicycle tour, glowing green in this animation on the same topic, and orange color for this animated chart in dot matrix style.

Below are shown two good examples I recently came across. These posters for the SOS Brutalismus exhibition in Bochum (until 24.11.19, very much worth seeing), are printed in black on bright neon orange, yellow, and green (not shown) paper. The posters were designed by Rahlwes.Pietz.

Another example is the book/comic Shakespeare ohne Worte (shakespeare without words) by Frank Flöthmann, published by DuMont in 2016. The illustrations are made up of circle shapes. The color palette is black, white, green, and reflective shimmering gold.

Besides the use of a reduced palette of design elements, the layout of the elements also plays a role. Simplicity in a layout can be achieved by reducing content and leaving more whitespace, using a simple transparent structure, and including a hierachy with three to five layers based on fractal aesthetics. Simplicity by layout is a topic that warrants a further article.

Ligne Claire Graphic Style

Aesthetics, Data Visualization, Design

Currently I’m trying to extend my skillset to also be able to construct basic infographics and illustrations from scratch. One of my preferred graphic styles for clear minimalist infographics and illustrations is the ligne clear („clear line“) style. The style is notably associated with „Adventures of Tintin“ comics by Hergé (Georges Remi).

Doing some research on the topic I found that there are many other artists besides Hergé who produced and still are producing beautiful work in the ligne claire style. I decided to summarize the main findings or my research as an infographic, or rather, a digital poster. You can see the result below (you might have to open the graphic in a new tab to read the small text.)

Ligne Claire Infographic

The copyrights of the images lie with the referenced authors and publishers. The images are shown here for reviewing and educational purposes only.

One main finding of my research was that Hergé owed a lot to his precursors and collaborators. Especially Edgar P. Jacobs played a major role in introducing realistic props and backgrounds in the Tintin series. He went on to work on his own series: Blake and Mortimer. When Edgar P. Jacobs was unable to continue the work on this series, many other renowned ligne claire artists drew individual volumes: Bob de Moor, Ted Benoît, André Juillard, Antoine Aubin and others. Personally I’m quite fond of the artwork Peter van Dongen did for the most recent volumes.

The shown information is mainly based on these sources:

Hergé’s working method can be seen here:

The working method of E. P. Jacobs was quite similar and is shown here:

I constructed the graphic using my preferred open source vector editing software Inkscape. This turned out to not be the best tool for the job. Layouting is a lot more comfortable in Scribus, the usual open-source desktop publishing software of my choice. I had some difficulties coming up with a balanced layout for the content. Finally, I settled on this structure reminiscient of a triptych. The structure makes sense here, grouping everything around the pivotal work of Hergé. The form (together with the vintage paper-colored background) does however undermine my initial intention of drawing attention to other ligne claire artists beyond Hergé and the timelessness of the ligne claire style.

Note: I first created the infographic shown above in October 2019 with Inkscape and then overhauled it in Juli 2021 using Scribus. Several details of the initial typography and layouting bothered me. As the topic of ligne claire style remained relevant to me, I still wanted to shown this piece on my portfoilo page. I notably replaced the font by one with more font weights, did several changes to element alignment, and added the light gradient in the background.

Pictograms of people: depicting individuals and groups

Aesthetics, Data Visualization, Design

The infographic below shows a comparison of the pictograms of contemporay artist Julian Opie, and graphic designers Rudolf Modley and Gerd Arntz. While Arntz and Modley depicted members of specific groups (professions, socio-economic groups), Opie uses a very similar design language to depict individuals.

I created this infographic after visiting the exhibition Sculpture 21st: Julian Opie at the Lehmbruck Museum Duisburg. Here’s a photo of the exhibition space from outside the building. The exhibition consisted of several sculptures and an animated LED screen.

Julian Opie is a contemporary british artist. He is best known for portraits in a simplified cartoon-like style. He also produces paintings, sculptures, and animations of walking figures in a pictographic style. The genius of Julian Opie is that he uses a simplified, pictographic design language to portrait individuals with their characteristic features. A large number of his works can be seen on Julian Opies’s website. The walking figures for the graphic was extracted from the painting City Walkers, 2018, a rare example of a work in black and white.

German artist Gerd Arntz designed pictograms for Isotype infographics in the 1920s and 30s. The work was under the direction of Otto Neurath and in collabation with Marie Neurath at the social and economic museum in Vienna. Examples of Arntz’s work can notable be found in the Gerd Arntz Web Archive.

Rudolf Modley had already worked on pictograms with Otto Neurath in the 1920s. When he emmigrated to the USA in the 1930s, he founded Pictural Statistics Incorporated and developed his own Isotype-style pictograms.

Contemporary Designer John Caserta wrote a short tutorial on how to create pictograms in this style from photographs. There is also a selection of resulting pictograms showing contemporary activities available.

In Isotype statistical infographics, pictograms of people usually stand for numbers of people of a specific group. For instance one pictogram of a soldier would stand for 1 million soldiers. The pictograms thus show the clothing and tools characteristic for the depicted profession or socio-economic group. The infographic by Rudolf Modley depicts workers in the agricultural and in other sectors (picture source: wikimedia commons).

Pictograms of people in contemporary signage tend to be even more abstract, depicting even more general groups. For instance athletes of a sport in the olympic pictograms, men and women on toilet signs, or simple humans (walking) on traffic signs.

The Evolution of German Traffic Signs

Aesthetics, Data Visualization, Design

The infographic below shows the evolution of German traffic signs from realistic contour drawing to abstract pictograms. The principle is demonstrated using selected signs. The signs introduced in 1992 are those still in use today.

During bicycle trips in remote areas I often see old traffic signs which to me have a nostalgic look. Especially old signs for foot- and bicyclepaths are often still in place:

Comparing signs of the previous generation to those installed today, two main changes can be identified. The signs have been adapted to changing fashion (men wearing hats etc.) and changing technology (forms of trains, cars, motorcycles etc.). There is also a change in style, with the modern signs looking more abstract and geometric. Doing some research on the topic I found that these trends can be traced back still one generation of signs further, back to those signs first introduced in post-war Germany in the years 1953 – 56. The infographic I prepared illustrates this point.

For company logos it is known that they tend to become more abstract over time. It seems that with every overhaul of a logo, there is a tendency to drop nonessential elements. The logo is thus whittled to perfection over time. Modern design language favors stylized geometric logos over realistic ornamental ones, so there is tendency of designers to make changes in this direction. As an example, both the logomark and logotype of the company Pelikan, a German manufacturer of office equipment, shows such a development. The logomark reached an abstract form quite early, in 1937 (picture Source: Pelikan).

Here another example: the logo of the company Royal Dutch Shell (picture source: here).

In the case of German traffic signs another major influence might have been the pictograms developed by Otl Aicher for the summer olympics in Munich in 1972. These stylized human figures had a big impact on subsequent pictograms showing people. This is especially noticeable when comparing the figure shown in the crosswalk sign of 1992 (see above) to those designed by Otl Aicher in 1972 (picture source:

Though realistic contour drawings are currently seldomly used for functional signs and pictograms they are still in use in other settings. Especially contours of athletes can often be seen, for instance in the Bundesliga logo (German national football league), National Basketball Association (NBA) logo in the USA, and Major League Baseball logo in the USA. The riverway sign/logo below show an assemblance of contours of persons performing different activities.

Signage in Primary Colors: Red, Blue, and Yellow

Aesthetics, Data Visualization, Design

Lately I’ve been studying signs of all types, notably traffic signs. I noticed that German traffic signs use only basic color combinations of a handful of colors. The picture below shows the three most common color combinations. I estimate that about 70 percent of functional signs in Germany use these colors. The shown signs display information about hydrants, and the gas- and water network.

Red shapes and black text are displayed on a white background, black content on a yellow background, and white content on a blue background. The alternative color combinations blue and black, and yellow and white don’t work because of their low contrast. On traffic signs these colors tend to be used for specific purposes, red to indicate danger, yellow for warnings, and blue for neutral indications.

One can only speculate why other high-contrast colors combinations such as green-white, orange-black, and purple-white are seldomly used. My theory is that it is because these three colors were traditionally taught to be the primary colors for subtractive color mixing. The picture below showns the color mixing circle developed by Bauhaus teacher Johannes Itten (picture source: Wikimedia). In todays printing process the colors cyan, magenta, and yellow are used to mix colors.

In art history the three primary colors were also heavily used in De Stijl abstract art which influenced the Bauhaus movement. This painting by Piet Mondrian (Composition with Red, Yellow, Bluea and Black, 1921) demonstrates this (picture source: Wikimedia).

The biggest German tabloid newspaper Bild traditionally had a title page in red, black and white. This highly effective color combination is an absolute classic in graphic design and was already used in egyptian papyrii (headings and quantities written in red) and medieval manuscripts (rubrication). In the last years the newspaper has begun also using yellow-black titles as can be seen in the picture below (Source: Bild ePaper).

Visualizing spatio-temporal data as an animation vs. as static maps: black coal mine shafts in the ruhr region

Data Visualization

The ruhr region (Ruhrgebiet) in Germany was a center of black coal mining and the steel industry. In the last decades all black coal mines and most heavy industry sites have been shut down. Nowadays the low rents in this densely populated urban region attract startups, artists, retaurants, and immigrants. Still, the heritage of coal mining is visible everywhere. So I was keen to do a data visualization dealing with this history.

This project was done in collaboration with Peter Dodenhoff, who supplied me with the data he collected for his mapping project The discussions with Peter helped me to better interprete the historical trends visible in the data visualizations. Peter also wrote an article about this project which you can read here.

The animation below shows the development of black coal mining shafts in the ruhr region from 1800 until 2019. The color of the dots shows the maximal depth of each shaft over its operating time. All maps shown here were designed with QGIS and the Time Manager Plugin.

If you want to read an interpreation of these visible historical trends now, skip right down to the text. I also prepared a set of four maps which show the same data statically. The first map shows the year in which each mine shaft was dug:

The following map shows the year in which the mine shaft was shut down:

The following map shows how long each mine shaft was in operation:

The following map shows the maximal depth of each mine shaft:

The animation and the set of static maps nicely show the big historic epochs of black coal mining in the ruhr region:

  • 1800: Obervation: The animation starts in this year with only very few existing coal mining shafts. Explanation: Since the middle ages coal had already been mined in the small scale in pits and in horizontal tunnels in the Ruhr valley, not shown in the map. Deeper vertical mine shafts became possible when steam engines were used to pump the groundwater out of the shafts. The first such pump was put in operation in 1801 in Bochum by Franz Dinnendahl. Only after that did coal mining in the big scale in vertical shafts really take off.
  • 1800-1930: Observation: Mine shafts are first being mainly dug near Essen, Bochum, and Dortmund. The development then expands further north. Shafts tend to get deeper the further north they are located. Explanation: The axis Duisburg-Mühlheim-Essen-Bochum-Dortmund is the route of the Hellweg, a medieval trade route. Then and now the most populated cities lie along this axis. The need for coal strongly rose after 1800 with the introduction of steam engines in factories and of the steam locomotives for transport (in Germany since 1835). Steel manufacturing requires lots of coal, thus steel factories were built up near coal mines, also leading to higher demand. Coal mines were first dug in the south were coal lies nearer to the surface. Later mines opened further north were the coal lay deeper in the ground. Mines were shut as the coal reserves in the corresponding areas were depleted or mines became economically unviable. (Note: It is interesting that the first world war 1914 – 1918 is not detectable in the data visualization)
  • 1930: Observation: Larger sets of coal mines can be seen to shut down at once, notably south of Dortmund. Explanation: In the world economic crisis beginning in late 1929, several coal mines were shut down.
  • 1930-1960: Observation: Further coal mines are opened. Explanation: There was a high demand for coal before and during the second world war for steel and arms manufacturing. In the postwar „economic miracle“ there was also a high demand.
  • 1960-2018: Observation: Coal mines are quickly shut down. First in the south then in the north. Explanation: The coal crisis in Germany arose in the 1960s because black coal from other countries was cheaper, demand for black coal sunk, and other factors. Technologically older mine shafts in the south were shut down first, then more modern shafts in the north.
  • 2018: Observation: The last coal mine shafts in the ruhr region shut down. Explanation: These belonged to the mine Prosper-Haniel in the north of Bottrop.

This is an example of a project where I designed both an animated map and a series of static maps for a spatio-temporal dataset. After receiving the dataset I first explored the data using quickly prepared static maps. These maps I already discussed with Peter Dodenhoff. The overall historic trends could be seen in these first maps Then I designed the animation. Looking at the animation revealed several patterns on the small scale not so apparent in the static forms. Finally I redesigned the static maps to have them in a presentable form. Having the dynamic and static formats side by side allows a discussion of their benefits:

Animated maps of spatio-temporal data have the following advantages:

  • They provide entertaining content for presentations, websites, and social media. People tend to find dynamic content more interesting than static pictures.
  • Seeing a development in animated time is intuitive, i.e. is easily understood without explanation.
  • Animated maps allow to show more complex spatio-temporal patterns, for instance events of different durations recurring at the same geographic locations.
  • The visualization can usually be displayed in a single frame as a single file.
  • If the video is shown with control panel the user can skip back and forth in time (this is not possible using the simple gif file format). An animated map is a sequence of static maps each of which can be viewed on its own.

Static maps of spatio-temporal data have the following advantages:

  • All data is shown at once and can thus be better compared and analyzed. This only holds if events do not spatially overlap in the chosen visualization. (Visualization formats such as heatmaps also allow to show spatially overlapping events.)
  • Maps can be easily be prepared with standard GIS applications. The simple picture file formats can easily be used in all contexts and printed.

The above lists name more advantages for animated maps than for static ones for visualizing spatio-temporal datasets. In my opinion static maps are especially useful for analytical applications and initial data exploration. The choice of format should be based on the purpose of the visualization (entertaining, presenting vs. analyzing, exploring), the audience (general public vs. visually literate analysts), and nature of the data set (recurring spatially overlapping events vs. one-time spatially dispersed events). The ideal case obviously is to have both formats and to see what patterns can be seen in the different visualizations.

For the sake of transparency I want to add some notes on the underlying data. As already mentioned, the data was collected by Peter Dodenhoff for his project, which shows a spatial map of mine shafts and provides additional information. For some of the mine shafts in this dataset the begin or end year of mining operations is unknown. I could not include these in the animation and also omitted them for the static maps, to get an uniform set of maps. The map below shows these mine shafts in red. The visualisations above show the 1004 mine shafts with time data out of 1168 mine shafts in the inital dataset. There is also bound to be some uncertainty in the data per se. The inital dataset probably does not include every existing mine shaft and a few entries might be incorret. Nevertheless, I am convinced that the visualization and the underlying data reflect the overall historic trends very well.

Creating a 3D flyover video of tour data with Google Earth Pro Desktop

Data Visualization

The free software Google Earth Pro Desktop can be used to create flyover and flythrough videos of real-world 3D cityscapes. Timed data of a tour can be shown within the visualization. In this article I explain how I made such a video.

I realized this project in the context of my monthly mapping of the Critical Mass Essen bicycle tour. At critical mass events large numbers of bicyclist drive through a city as a convoy in a random fashion. This serves to create awareness for cycling as an environmental friendly, healthy, and economic mode of transport.

The window below shows the 2-minute mp4 video I made, embedded via my channel on Youtube.

This is how I created the video. First, I logged the tour with the open source GPSLogger app as a KML and CSV file. The KML track file, containing waypoints and corresponding timestamps, can be directly loaded and visualized in Google Earth. However, I was not happy about the quality of the logged data, which contained lots of jitters. It turned out that KML track files cannot be edited directly in Google Earth, QGIS, or similar programs. So what I ended up doing is loading the CSV file with coordinates and timestamps into QGIS, editing the points and saving the result again as a CSV file. I wrote a Python script that then converted the CSV file into a KML track file.

In Google Earth Pro Desktop I then opened the KML track file (File -> Open). I adjusted the basic visualisation of the track (right click on track -> Properties -> Style, Color), turning the color to blue (for the bluescreen video editing technique see below), widening the line, and reducing the sizes of symbology and labels to 0.0 in order to show only the line.

In order to create a video the KML track must be turned into a Google Earth tour. The parameters for how tours are displayed can be adjusted in Tools -> Options -> Tours. There are several tradeoffs when setting these paramters, so this takes some iterative experimenting. In my case I set the speed to 45 fold real time, in order to have a final video of about 2 minutes. I settled on a camera distance of 800 m. This results in a relaxed viewing speed, while still showing enough ground details. As a camere angle I settled on a somewhat high 30 degrees. This angle still shows off the 3D buildings, while keeping the number of buildings that have to be loaded to an acceptable level (otherwiese I would see glitches due to loading buildings). I set the time between keyframes to 5 seconds. This nicely keeps the track in focus while smoothing out the stops that the track made at red lights.

A tour with the given settings can then be played by selecting the track, and clicking on the play tour icon (connected dots) below the list. Video play controls are then shown. To save the current tour click on the save icon (disk) at the right of the video controls.

With the saved Google tour you can then create a video. Close the video play controls. Go to Tools -> Movie Maker, select your saved tour, and click create video. Here again some iteative experimenting is necessary to get the desired results. I settled on a custom video size of 854 x 280 (corresponds to youtube standard 480p size with 16:9 ratio), 30 frames per second, high quality picture quality, and MP4 file format.

My standard business laptop and medium speed internet connection did not always seem to render the results perfectly. Thus I tweaked the 3D display options in Tools -> Options -> 3D View. I shut of the anisotrope filtering, which plays no role at steep camera angles and set antialiasing to high (option availabe only for OpenGL). I also reduced the texture color to 16 bit because I was going to reduce the image to greyscale anyway (see below).

The recorded MP4 file I then opened in the open source video editing software Shotcut. I added the same file as two layers. The lower layer I colored to red (filter: color correction). For the upper layer I used a chroma key filter (i.e. bluescreen/greescreen). This turned the blue line in the upper layer transparent and let the lower layer shine trought at these points. The rest of the upper layer I then turned monochrome using the saturation, contrast, and brightness filters. The caption in the upper left, I added with the text filter. The resulting video I saved as mp4 and a short extract as the gif file shown above.

In conlusion I would say that Google Earth is a good tool for creating simulated photorealistic drone and aerial videos which can then be further processed. Creating such a video from a KML track file is a matter of minutes, but getting a good result out of the process requires a lot of tweaking of the parameters.

Creating a map panning video with the QGIS 3D map view

Data Visualization

QGIS 3.X includes a 3D map view (View -> New 3D Map View) which was developed by Lutra Consulting. The functionality to create flyover videos is integrated in this view. This can also be used to create panning and zooming videos of conventional maps. In this article I explain how I made such a video.

I realized this project in the context of my monthly mapping of the Critical Mass Essen bicycle tour. At critical mass events large numbers of bicyclist drive through a city as a convoy in a random fashion. This serves to create awareness for cycling as an environmental friendly, healthy, and economic mode of transport.

The window below shows the 2-minute mp4 video I made, embedded via my Youtube-channel.

This is how I created the video. First, I logged the tour with the open source GPSLogger app as a KML file. I loaded the file into QGIS, and and manually removed the worst GPS jitters, to get a smooth curved line representing the tour.

I chose a light orange tone for the line, start and end points, and labels. As a labeling font I used DIN Schablonierschrift, a font that has it’s background in stencil writing often seen on German streets.

Using the QGIS QuickMapServices plugin, I set the Bing Aerial map as a background, which I turned to grayscale in the layer settings. I reduced the brightness and contrast to get a background where the light orange line would be better visible.

The elaborate camera movements needed some structure to be set up. Thus I created a point layer with helping points. I measured the distances between the points using the measure tool, and included the accumulated distance from the first point as an attribute. The time at which each point should be shown is then calculated as timePoint = timeOffset + distancePoint * totalTime/totalDistance.

In the 3D map view a press on the „play“ icon opens the animation/video timeline below the view. The current camera point of view can be added as a keyframe to the animation with a click on the „+“ icon. Thus I could set up the animation keyframes manually quite fast with the previously specified points and times. Enabling „Show camera’s view center“ in the 3D map view settings allows to cleanly focus on given points. The camera can not just be panned and zoomed, but also be tilted and turned but I intentionally did not use these possibilites.

There are a few pitfalls when creating animations in the 3D view. I constantly kept overwriting keyframes. It is necessary to reset the keyframe to <none> after having created a new keyframes, otherwise the keyframe is further being edited through the mouse movements.

I had some problems with panning movements done in rough steps (visible in mp4, not in gifs). In such cases the panning movements were much smoother when I changed the zoom level of a point, ran the animation and then set the zoom level back.

Also there were some glitches visible as tiles were reloaded during panning. It turns out that the settings for map tile resolution, max screen error, and max. ground error have a big impact on how tiles are loaded. In my case adjusting the tile resolution to a large 2048 px resolved all visible tile glitches.

When I was satisfied with the created animation, I recorded the video from the screen using the open source software shareX. With this tool it is possible to cleanly select the 3D view window with a single click and record the video in mp4 format. The recorded video is slightly more choppy then the animation visible in QGIS. In QGIS 3.6 it is apparently also possible to directly export animation frames from the 3D viewer.

As a final step, I used the open source video editing software Shotcut to add the white caption in the upper left into the mp4 file. I also used the program to export the gif extract shown above. The file size was reduced with the online gif optimizer Ezgif.

Critical Mass Essen january 2019 tour

Data Visualization

At critical mass events bicylists meet and drive through a city as a convoy. This creates awareness for cycling as a mode of transport. I logged the january tour and turned the data into an animated map:

Due to rain the tour was shorter than usual, taking about 83 minutes. With a distance of 15,1 km covered the average speed was only about 10,9 km/h. The convoy drives at a leisurely pace and slows down at many traffic lights in the inner city area.

The first kilometer seems a bit short. This was due to circling at the start of the tour and circling in two roundabouts. These movements only become visible when the animation is played at small time intervals. A fast movement can be seen at about 20:07. There the convoy drove downhill through a tunnel. The right/left orientation of the bicycle icon is based on the logged bearing data, i.e. the direction of travel. Some flickers can be seen in this data, especially during stops.

The orthophotography recolored to a monochrome blue makes the city look more densely covered than in the other maps I‘ve seen. This is of course mainly due to the green color being lost, but also due to other factors. I’ve noticed that cemeteries, garden colonies and parks are mostly drawn green in standard maps, while they appear similar to urban fabric in satellite photography. This reminds me of using less processed maps and more raw satellite imagery when plausibility checking geographic data.

The animation was produced in the following workflow. I logged the tour with the GPSLogger app. I used a self-written python script to convert the time sequence of points as a CSV file into a time sequence of lines summarizing the tour up to that point as a geojson file. I set up the tour data in the QGIS Time Manager and exported the frames as PNG images. I loaded the images as layers in Gimp, applied the gif-animation filter for optimization and exported it as an animatedGIF. The GIF file I additionally converted to a MP4 video file using Shotcut.

Some technical details are noteworthy. Especially superimposing the labels and icons in QGIS required some tweaking. I downloaded the bicycle icon as a SVG file from wikimedia commons and constructed a right/left version of it. The logged data contains a bearing field (direction of travel). Using rule-based labeling, for a bearing up to 180 degrees a right-driving bicycle is shown, for larger bearings a left-driving bicycle is shown. QGIS always places labels above icons. This can be worked around by making the icon part of the label by using it as a background image in the label settings. The kilometer markings were set to a low priority and to alway draw to keep them in the background. Dark blue halos were used for all labels to make them better visible. For normal symbols, the outer shadow effect can be used to emulate halos, but for icons used as label backgrounds only the weak shadow functionality is available. Thus I added the icon halos directly into the SVG files using Inkscape.

The orthophotographs I downloaded from the open geodata portal of Nordrhein-Westfalen. The JP2 files (JPEG 2000) can be directly loaded as georeferenced data into QGIS. To get a monochrome image I converted the image to greyscale and colored it blue in the layer settings.


Calender 2019 in Bauhaus-inspired style

Data Visualization, Design

In the last weeks I have been searching for the calender equivalent of a Bauhaus style watch. Such watches, notably those designed by Max Bill*, are functional and free from decorative elements. They have a timeless elegance about them. Available German office calenders, for example this Brunnen calender, lack elegance in the details. In fact the only widely acknowledged calender in a modernist design seems to be this calender designed by Massimo Vignelli in 1966.

Thus I created my own Bauhaus-inspired calender. You can download it here and print it yourself double-sided on standard DIN A4 paper, resulting in a DIN A5 sized calender. The pages are folded in the middle and then reversed and refolded as the months change. With twelve months on three standard sheets of paper this is a minimalist calender that deserves the name. I prepared two versions (in German only):

I experimented with several possibilities of hanging the calender with standard office equipment. I finally settled on using a small (white) foldback clip (see picture). This serves as hanger, binding, and presses the pages together a bit to keep them from fluttering. If you use thick paper (170 g/m² works well) you can also stand it upright as a desktop calender. Other methods also work. You can punch a whole in the middle (be careful when doing this, if the hole is not centered the pages will be badly aligned when you rotate pages) or pass a loop of string under the fold. The pages may then look less fluttery if you fix them with a paper clip or similar means in the lower middle. Pins and magnets also work, of course.

I created the calender using the open source layout program Scribus. I wanted a font that is similar to Paul Renner’s Futura, but runs wider. I ended up using the free fonts Typo Grotesk for lettering and Florence Sans for numerals.

This project nicely demonstrates how minimalist design works. An effortless, natural looking design is often the result of a lot of work on the details. I used an underlying raster here and fine-tuned character spacing, weight, size, and alignment of two different fonts to get the desired result. Also, elegant minmalism and straightforward simplicity are not the same thing. A straightforward simple design would keep all lettering and numerals at the same size and omit the line under the weeks. But when such details are omitted the design loses all depth and sophistication.

*Note: Max Bill studied at the Bauhaus in Dessau 1927 – 1928. The Bauhaus Institution was closed in 1933. Max Bill designed his famous wristwatch designs for Junghans around 1961. So it can be a matter of debate whether these watches should be called „Bauhaus watches“. Earlier watch designs considered to be typical for the Bauhaus such as the Stowa Antea and the Nomos Tangente show similar design characteristics. The Nomos Tangente was designed by Suzy Günther around 1990 based on a watch from the 1930s. Stowa has been producing watches in the look since 1937. The original watchfaces were produced by the company Weber & Baral in Pforzheim, whose founder Arthur Weber played a role in its design. (Where is the connection between Arthur Weber in Pforzheim and the Bauhaus ?)


Critical Mass Essen december tour

Data Visualization

At critical mass events bicylists meet and drive through a city as a convoy. This creates awareness for cycling as a mode of transport. The following animated map shows the Critical Mass tour through Essen in december.

Based on the previous animation for november, I identified some patterns of how such a convoy might typically move. Some of the identified behavioral pattern are again visible in this december tour. A preference for wide main roads can again be seen. Though with the background map showing only building polygons this is not as well visible. Even though there is no prefixed tour, the convoy seems to move in a partially destination-oriented way. The tour to the north-east circled around the Zeche Zollverein site and back. The small loop in the south served to retrieve a bicyle grill from a participant’s garage. The tour ended at a location in the south for an end-of-year get-together. The supposed preference for right hand turns resulting in clockwise loops cannot be observed in the december tour. The two visible loops are both counter-clockwise. Though the legal basis for these events is fairly clear, the tour was held up by ill-informed police officers. The tour continued after some lengthy explantions.

The map also reveals some of the hidden beauties of Essen. The Zeche Zollverein in the north-east is a historic coal mine. It is Essen’s trademark and an Unesco World Heritage site. Large free spaces are visible between the building polygons. Due to the many parks and forests in the city, Essen was the European Green Capital 2017.

The animation was constructed using the open source tools QGIS with the Time Manager plugin, Gimp and the GPSLogger app. The background shows building polygons from Open Streetmap data.

The general wokflow was as follows. I logged the tour at a 5 second interval using the GPSLogger app. I wrote a python script that converted the individual points logged in a CSV file to lines in a geojson file with time as an attribute. This geojson file I opened in QGIS and converted it to a shapefile for use with the Time Manager. I set up the Time Manager with a time interval of 51 seconds. This leads to a nice counting up of seconds in the time display. I added a manually constructed point layer with the labels and associated times when the tour passes those points. The resulting time animation I exported as individual frames in PNG format. These files I loaded as layers in gimp. I applied the gif optimization filter and adjusted the color palette to 255 colors in order to get a clean white background. Finally I exported the animation as a gif.


A dot matrix as an animated data chart

Data Visualization

Dot-matrix displays have a nice retro-futuristic look to them. Here is an animated data chart I made based on this look. The chart shows the result of the federal parliament election in the German federal state of Hessen on the 28.10.2018 and compares them to the previous results of 2013.


(Note: the animation may take a moment to load)

It can clearly be seen that the two parties currently governing in Berlin, CDU and SPD, lost a lot of votes. Large gains can be seen for the Grünen (GRU), an ecological party, and the AfD, a right-wing populist party. After this election chancelor Merkel from the CDU announced that she will not be candidating for another mandate.

Obviously this data chart is more about experimenting with an interesting visual style than about legibility and precision. Party names had to be abbreviated (AND stands for „Andere“ meaning „others“) and values had to be rounded.

I made this animated chart with the open source graphic programs Inkscape and Gimp. First, I constructed the individual frames as vectorgraphics in Inkscape, reusing as many elements as possible. Then I exported them as PNG files. These I loaded as layers into Gimp. I optimized the layers for gif using the animation filter (Filter → Animation → Optimize for gif). This leaves only the differences between individual frames as layers, which makes the final file considerably smaller. Then I tweaked the frame durations to result in a fluid motion. I opted for a linear acceleration and deceleration for the buildup and teardown of bars. This results in a slight „trampoline“ effect with slower motion at the start and end. The appropriate frame durations for this I calculated in a spreadsheet. Finally I exported the animation as a gif from Gimp.

Data sources:

2018 election results for Hessen, preliminary:

2013 election results for Hessen:

Seating order (left to right) in the Hessen parliament before 2018:


Critical Mass Essen: Visualization of the route as an animated map

Data Visualization

At Critical Mass events large numbers of cyclists meet and drive through the city in a random way as a convoy. This serves to create awareness for cycling as a mode of transport.


I logged the route of the november Critical Mass in Essen and turned it into an animated map. The background shows the route network available to cyclists, i.e. the road network including cycling tracks but without footpaths and motorways.


(Note: the animation may take a moment to load.)

Looking at the map shows some interesting behavioral trends that are not immediately apparent when driving in the convoy. There seems to be a preference for wide main roads. The reason is that these are better suited when cycling in large numbers and are better for getting visibily and creating some chaos. An alternation can be seen between cycling to somewhere and cycling in a random fashion. The route to the south and back connects the Essen city center and the southern subcenter in Rüttenscheidt. During random tours there seems to be a preference for right turns resulting in clockwise movements.

For those interested, here some details about how this animation was made. It was constructed using the open source tools QGIS with the Time Manager plugin, Gimp, and the open source GPSLogger app. The background shows Open Streetmap data. Only those roads are displayed that are usable by cyclists i.e. normal roads and cycling tracks, but not foot paths and motorways.

First I logged the tour at a 10 second interval using the app. The resulting CSV file I imported into QGIS. I converted the file format to Geojson which allows editing. I manually corrected the jitters in the logged data which showed some deviations of 10-20 meters. Then I exported the file format to GML because the Time Manager does not seem to support all functions for geojson files. I set up the time animation in the Time Manager Plugin using an interpolation for the points. The glow effect was created with the drawing effect „outer glow“. The trail in the animation was created by registering the points again, setting the end time to cumulative and showing only the glow without the source. The resulting time animation I exported as individual frames. These I loaded as layers in Gimp. I rescaled the image and applied the gif optimization filter. I added the title and finally exported the animation as a gif.