Data Collection, Analysis and Visualization using ODK, SPSS/Stata/R and QGIS

INTRODUCTION

Evidenced based policies for sustainable development and better lives call for better data. Improving the capacity of people involved in data collection, analysis and report writing in ensuring quality data is of significance. Following the changing data environment from use of paper in capturing data to use of digital innovation, there is need to train actors involved in data collection to help them adapt to the upcoming innovations and technologies. Some of the data that are collected through the new technologies include geospatial data, mobile phone, administrative data and citizen-generated data among others. This 10 days course will equip participants with knowledge on research design, designing data collection tools in mobile data collection enabled software, GIS and remote sensing, exporting data
to various data collection software, data analysis and interpretation.

Duration

10 days

Who should attend?

• Policy makers
• Researchers
• NGO and civil society staffs
• Educators
• Private sector representatives
• Civil Society Organizations

Learning Objectives

At the end of training participants will:

• Understand various data collection techniques and data processing methods
• Design data collection tools in google phone/ ODK/CTO/ CSpro (participants’ choice)
• Learn how to use mobile phones in  data collection(Open data Kit/CTO/CSpro)
• Learn how to integrate socio economic data with GPS coordinates
• Learn how to draw maps using ArcGIS among other software
• Learn how to analyze and visualize data with the aid of GIS techniques

Module 1: Statistical Concepts

• Types of data
• Data Structures and types of variables
• Overviews of software used to digitize paper data collection tools (ODK/CTO/)
• Comparative analysis of various software used to digitize paper data collection tools (ODK/CTO)

Module 2: Mobile Data gathering

• Benefits of Mobile Applications
• Data and types of Data
• Introduction to  common mobile based data collection platforms

Module 3: Managing devices

• Challenges of Data Collection
• Data aggregation, storage and dissemination
• Questionnaire Design

Module 4: Getting started in ODK/CTO

• Types of questions
• Data types for each question
• Types of questionnaire or Form logic
• Extended data types geoid, image and multimedia

Survey Authoring and Preparation of mobile phone for data collection

• Survey Authoring
• ODK Collect applications: Installing, Configuring the device (Mobile Phones) and uploading the form into the mobile devices

Module 5: Designing forms and advanced survey authoring

• Introduction to XLS forms syntax
• New data types
• Multiple choice Questions
• Hints and Metadata

Advanced survey Authoring

• Conditional Survey Branching
• Constraining responses
• Skip: Asking Relevant questions
• Grouping questions
• Repeating a set of questions
• Making dynamic calculations

Hosting survey data (Online)

• ODK Aggregate
• Uploading the questionnaire to the server

Module 6: Introduction to concepts of GIS and remote sensing

• Spatial data collection techniques
• Using GPS
• Using GPS utility software for managing and downloading and managing data
• Working with data from different sources

Module7: Attributes manipulation in GIS

• GIS software
• GIS system installation and setup
• GIS Data sources and types
• Using Mobile Phones for GIS data collection(ODK and KoBoToolbox
• Importing GPS data to Quantum GIS

Module 8: Visualizing data

• Understand map layers in GIS
• Composing a GIS layout from GIS layers
• Difference between a map and a layout
• Navigate maps

Module 9: Bringing tabular/spreadsheet data into a GIS (Excel, SPSS, Access )

• Connecting visual map features and tabular data
• Selecting subsets of map features from geo processing
• Finding map features
• Use data sorting records and labeling features to produce information
• Key elements of a map
• Composing a map

Module 10: Data interpretation and report writing

• Different research outputs
• Writing different research outputs from analysed data (case studies, success stories, policy briefs, evidence briefs, journal articles e.t.c)