Keynote at the Urban Mobility Symposium, 11 October 2019, Berlin https://www.citylab-berlin.org/events/mobilitysymposium/

1. Visually analyzing urban mobility
Results and insights from three student research projects
Till Nagel
Hochschule Mannheim
11 October 2019
Urban Mobility Symposium

2. Shanghai Metro Flow cf. city flows Shifted Maps
Liquidata Isoscope-Two Touching Transport
Cab Rides Singapore Road Network Coped

3. • University of Applied Sciences
• computer science, design (+ 7 further faculties)
• 5200 students
Hochschule Mannheim

5. Foundation in information visualization

6. http://infovis-mannheim.de

7. modal
Mannheimer Modell Data Literacy Education

9. • Learn through own research
• Strive to work on a problem methodologically
• Demands autonomy, responsibility, and
curiosity
Research-oriented learning

10. Applied Project: Visualization (WPM_APV)
• With external partners
Do not act as client, but as research partner
and provide questions and ideas
• Trans-faculty course
6+2 (summer ‘17), 3+3 (winter ‘17), 9+1
(summer ‘18), 4+10 (winter ‘18), 6+2 (winter ‘19)

11. Students are able to
• Understand the design space
• Analyze visualization techniques + systems
• Iteratively develop visualization prototypes
Learning outcomes (WPM_APV)

12. Sketching exercises

14. Inspiration and mood boards

15. Literature review

17. Via Velox
Visualizing crowd-sourced cycling trips

18. • GeoNet.MRN (domain experts)
• SAP (creative thinking)
• Universität Mannheim (tracking app)
• Hochschule Mannheim (visualization)
Partners

30. http://infovis-mannheim.de/viavelox

31. WanderVis
Visualizing population movement to and from a city

32. • City of Kaiserslautern (data provider)
• DFKI (data processing)
• Hochschule Mannheim (visualization)
Partners

44. http://infovis-mannheim.de/wandervis

45. PaxMotion
Visualizing boarding/deboarding pax and delays

46. • Rhein-Neckar-Verkehr (data provider)
• Hochschule Mannheim (visualization)
Partners

47. Guest lectures

48. Design thinking workshop

52. Glaskugel-
Nachfragen,
Voraussagen
Am Fahrtziel
ankommen
Stau beim
Ein-/Ausstieg
Betriebs-
störungen
Komfort
Verfügbarkeit
Überfüllung
Auslastung,
Lastspitzen
Sitzplätze
Durchkommen
in der Bahn
Umstiegs-
möglichkeiten
Mehrere Steige
Anschluss-
Anzeige
Barrierefreiheit
Anschluss-
sicherung
Verteilung der
Fahrgäste
Fahrgäste
wollen zuerst
einsteigen
Verspätungen
Ausfälle
Umleitungen
Unfälle
P+R
ausbauen
Gerüche
Sehens-
würdigkeiten

64. Zeitplan & Milestones
Vorträge Aufgaben Milestones
1 15. Mär 18 Einführung
2 20. Mär 18 Flow Maps A1: Recherche ÖPNV-Vis
23. Mär 18 Maps & GeoVis
3 27. Mär 18 Vorstellung RNV A1: Präsentation ÖPNV-Vis Recherche
30. Mär 18 Karfreitag
4 3. Apr 18 Vis Analyse und Taxonomie A2: TaxiVis Analyse
6. Apr 18 NUI: Multitouch & Tangible Interaction Vorbereitung Workshop
5 10. Apr 18 Creative Thinking Workshop Ideation
13. Apr 18 Nachbereitung + Zeitplanung
6 17. Apr 18
20. Apr 18 RNV Daten A3: EDA
7 24. Apr 18 A3: EDA Ergebnisse
27. Apr 18 Sprint 1: Wireframes Zeitplanung & Aufgabenverteilung
8 1. Mai 18 Tag der Arbeit
4. Mai 18 Sprint 2: Technologie Wireframes & Mock-Ups
9 8. Mai 18 (Hackathon)
11. Mai 18 Sprint 3: Prototyp 1 Grundgerüst / Git
10 15. Mai 18 (Konferenz)
18. Mai 18 Sprint 4: Prototyp 2 Prototyp 1
22. Mai 18 Pfingstferien
25. Mai 18 Pfingstferien
11 29. Mai 18
1. Jun 18 Sprint 5: Prototyp 3 Prototyp 2
12 5. Jun 18
8. Jun 18
13 12. Jun 18 Sprint 6: Finaler Prototyp Prototyp 3
15. Jun 18
14 19. Jun 18 Präsentation & Finaler Prototyp
22. Jun 18 Abschlusspräsentation RNV
15 26. Jun 18 frei
27. Jun 18 iExpo
29. Jun 18 Touch-Down

65. Issues: Bugs, Features und Design

69. delayed

70. No station selected central station selected
Daily average Numbers for vehicle at 8:13pm
at central station

71. Average boarding and
deboarding for all vehicles
over 24 hours

72. Daily peak of
passenger volume

75. Summary

76. No data’s perfect

77. I was repeatedly asked about the project
in job interviews. My practical experience
[within this project] also helped me with
data visualization as a working student, at
[work], and in my master's degree.
Pascal Perle

78. Trust students’ capabilities

79. I really liked the complete freedom in
deciding how and what we should implement.
This way you could experiment a little and try
out new things you probably wouldn't have
come up with otherwise.
Dimitry Nagorny

80. EDA and ideation go hand in hand

81. The project was a mixture of an interesting
analytical part, which was data-driven, and
an artistic visual part, which communicated
the meaning of the data to the viewer.
Dustin Noah Young

82. Thank you.
Prof. Dr. Till Nagel
Human Data Interaction Lab, HS Mannheim
@tillnm
t.nagel@hs-mannheim.de