WORKSHOP B5 Data visualization techniques

1. WORKSHOP B5Data visualization techniques

4. WHAT IS VISUALIZATION? • More than GIS… • …MORE THAN YOU THINK.

5. EXAMPLES

6. WHY VISUALIZE • Get it “at-a-glance” • Normalizes / Focuses • Translates • Enhances Quality • Accelerate Learning • “Discovery” • Scenarios of Future • “Enjoy Your Data”

7. WHERE DOES IT FIT? • BUSINESS CASE • DATA STRATEGY • SAMPLING FRAME • RECRUITMENT • DATA COLLECTION • DATA QUALITY • DATA ANALYSIS • DISSEMINATION & PRESERVATION

8. BUSINESS CASE • DATA STRATEGY • SAMPLING FRAME • RECRUITMENT • DATA COLLECTION • DATA QUALITY • DATA ANALYSIS • DISSEMINATION & PRESERVATION • BUSINESS CASE • Who’s the audience • What’s the problem • What’s been done • ETHICS • NORMALIZATION • HARMONISATION

9. BUSINESS CASE • DATA STRATEGY • SAMPLING FRAME • RECRUITMENT • DATA COLLECTION • DATA QUALITY • DATA ANALYSIS • DISSEMINATION & PRESERVATION • RECRUITMENT • Show how they fit in survey • Increase Response Rates • INTRODUCE BIAS • GUIDELINES • Participant Training

10. BUSINESS CASE • DATA STRATEGY • SAMPLING FRAME • RECRUITMENT • DATA COLLECTION • DATA QUALITY • DATA ANALYSIS • DISSEMINATION & PRESERVATION • DATA QUALITY • Real Time • Post Processing • Cleaning • Inference • Imputation • Understanding Quality • Transparency

11. WATCH OUT FOR: • Time Consumption • Ethics / Misrepresentation • Visual Overload • Introduction of “bias” • Privacy • Superficiality • (dazzle vs. inform)

12. RESEARCH NEEDS • “Stable” Funding For: • Reliable Base-Data Resources • Operating budget for “maintenance & preservation” • How Visualization can Improve “Response Rates” • Engaging “Hard-to-Reach” groups • Identifying & Quantifying • Value-added by using visualization • New Risks (i.e. biases) • Privacy Thresholds • Impacts of visualizing

13. RESEARCH NEEDS • Framing • In context of traditional surveys • In Stated Preference & Other Surveys • Developing Templates (tools) & Guidelines • Harmonized, High-Quality Data Bases • Education & Training • Computer Science MEETS Transportation • SYNTHESIS (what’s out there) • Teach the Possibilities • Define the skills needed to develop/utilize Visualization

14. BUSINESS CASE • Who’s the audience • What’s the problem • What’s been done • ETHICS • NORMALIZATION • HARMONIZATION • DATA STRATEGY • Graphic Literature Review • What we know / Don’t know • Knowledge Accelerometer • THOROUGHNESS • VISUAL OVERLOAD • APPROPRIATENESS • GUIDELINES • EST. SAMPLING FRAME • Review “official’ data • Ensure geospatial compatibility • Encourage “mix-mode” surveys • FUNDING to get spatial data up-to-date • DEVELOP VIS. TEMPLATES • DATA COLLECTION • Monitoring Progress • - Monitoring Quality • Monitoring Process & Workforce • Reduce Respondent Burden • INTRODUCE BIAS • IMPROVE QUALITY • IMPROVE CATI PROCESS • DATA QUALITY • Real Time • Post Processing • Cleaning • Inference • Imputation • Understanding Quality • Transparency • RECRUITMENT • Show how they fit in survey • Increase Response Rates • INTRODUCE BIAS • GUIDELINES • Participant Training • DISSEMINATION & PRESERVATION • Sustainability • “Get To The Knowledge” • PRIVACY (Show / Keep) • TOOLS & GUIDELINES • DATA ANALYSIS • Extract Patterns • Data Fusion • Identify Relationships • Does not compensate for “POOR ANALYSIS” • POSSIBILITIES FOR INNOVATION • MISREPRESENTATION • - FUNDING FOR TEMPLATES