This is a brief introduction, tools and tips for mobile data collection and data visualization.

1. Mobile Data Collection and
Data Visualization tools
Myo Min Oo
Chalk & Slate
www.chalkandslate.co
info@chalkandslate.co
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2. Advantages of Mobile in data
collection
▹ Time efficient – skip the secondary data entry step
▹ Faster transmission
▹ Accuracy of Data (Less text errors)
▹ Richer data (Pictures, GPS, BarCode, Audio, Video, etc…)
▹ Easier to analyze
▹ almost ready to visualize
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3. Challenges for Mobile Data
Collection
▹Initial trainings for surveyors
▹Connection Problems
▹Provision of Mobile Devices
▹OS Version Compatibility
▹Resolution of System Problems
▹Font Compatibility (Especially Myanmar Fonts) Both front end and back
end
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4. Tools for Data Collection
▹Google Forms (200000 Cells Limit)
▹Survey Monkey (Only 100 records for free version, $299 for unlimited)
▹Formhub (Free)
▹Open Data Kit ( Free)
▹Kobo Tool box (Free)
▹Collect
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5. Why we used ODK?
▹It’s free no matter how large your data set is (Other free tools have limits)
▹The forms can be created using powerful form design tools like Formhub,
XLS2XForm, Vellum, or Kobo, or PurcForms
▹Data can be exported not only to (.xls) (.csv) files but also to files like
(.kml) or shape files
▹Can operate offline
▹Can record audio, video, geographic codes, barcodes,
▹It’s Open Source
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6. Components of ODK
▹Build - ODK Build enables users to generate forms using a drag-and-drop
▹Collect - ODK Collect smartphone application
▹Aggregate - ODK Aggregate provides a ready to deploy online repository to
store, view and export collected data.
▹Form Uploader - ODK Form Uploader easily upload a blank form and its
media files to ODK Aggregate.
▹Briefcase - ODK Briefcase is the best way to transfer data from Collect and
Aggregate.
▹Validate - ODK Validate ensures that you have a OpenRosa compliant form
-- one that will also work with all the ODK tools.
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7. ODK Build
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8. ODK Collect
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9. ODK Aggregate
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10. Data Cleaning

11. 11 Data Cleansing Tools …..
 Data Wrangler (http://vis.stanford.edu/wrangler/) (From Stanford
University)
 Open Refine (Google Refine)
(https://code.google.com/archive/p/google-refine/) (From Google)
 R Programming (https://www.r-project.org ) from R Core Team
 Tableau Public (https://public.tableau.com/s/ )
 Microsoft Excel from Microsoft

12. Data
Visualization
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13. Four Main Things
 Get the data
 Clean the data
 Draw out dimensions, correlation and
facts
 Visualize it
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14. 14 Get the data: 3 Types of Data
 Data that you have collected
 Other elses’ data that you want to highlight (Eg: Open
Data)
 Search Engine and Social Media Data

15. 15 Data Sources
• http://ckan.org/
• http://www.theguardian.com/data
• http://www.google.com/publicdata/
• http://data.worldbank.org/
• http://datahub.io/
• www.themimu.info/

16. 16
What does your data
say?
 Trends
 Correlations
 Geographics
 Facts and Figures

17. 17
Before handling the
infographics………..
 What message do u want to give to your audience?
 What kind of people are they?
 Align your context with your goals and audience
 Structure your story

18. Data Visualization Tools
▸ Tableau Public (https://public.tableau.com/s/ )
▸ R Programming (https://www.r-project.org )
▸ D3.js ( https://d3js.org/ )
▸ Infogram ( https://infogr.am/ )
▸ PikToChart ( http://piktochart.com/ )
▸ Info Active ( https://infoactive.co/ )
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19. Infogr.am
Pros
▹Able to upload data set or live data
▹Strong Chart Tool
▹Good Features in free trail
▹Templates are very easy to customize
Cons
▹ Doesn’t allow to download in free version
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20. PikToChart
Pros
▹Able to upload data set or live data
▹A lot of graphic contents
▹Tons of Good Features in free trail
▹Templates are very easy to customize
Cons
▹ Chart tool is not that strong
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21. Thank You
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myominoo@tutanota.de
mmorakhine22@gmail.com