mobile data collection and d viz presentation

Mobile Data Collection and Data Visualization tools

Myo Min OoChalk & Slatewww.chalkandslate.co info@chalkandslate.co

1

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

2

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

3

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

4

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

5

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.

6

ODK Build

7

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

12

Four Main Things

Get the data

Clean the data

Draw out dimensions, correlation and facts

Visualize it

13

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 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

What does your data say?

Trends

Correlations

Geographics

Facts and Figures

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

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/ )

18

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

19

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

20

Thank You21

myominoo@tutanota.demmorakhine22@gmail.com