mobile data collection and d viz presentation
TRANSCRIPT
Mobile Data Collection and Data Visualization tools
Myo Min OoChalk & Slatewww.chalkandslate.co [email protected]
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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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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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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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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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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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ODK Build
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ODK Collect8
ODK Aggregate9
Data Cleaning
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
Data Visualization
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Four Main Things
Get the data
Clean the data
Draw out dimensions, correlation and facts
Visualize it
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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 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/
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What does your data say?
Trends
Correlations
Geographics
Facts and Figures
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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
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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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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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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