You are browsing the archive for Joachim Mangilima.

Mobile data collection

- December 16, 2014 in Skillhare, Tech


This blog post is based on the School of Data skillshare I hosted on mobile data collection. Thanks to everyone who took part in it!


Of recent, mobile has become an increasingly popular method of data collection. This is achieved through having an application or electronic form on a mobile device such as a smartphone or a tablet. These devices offer innovative ways to gather data regardless of time and location of the respondent.

The benefits of mobile data collection are obvious, such as quicker response times and the possibility to reach previously hard-to-reach target groups. In this blog post I share some of the tools that I have been using and developing applications on top of for the past five years.

  1.       Open Data Kit

Open Data Kit (ODK) is a free and open-source set of tools which help researchers author, field, and manage mobile data collection solutions. ODK provides an out-of-the-box solution for users to:

  • Build a data collection form or survey ;
  • Collect the data on a mobile device and send it to a server; and
  • Aggregate the collected data on a server and extract it in useful formats.

ODK allows data collection using mobile devices and data submission to an online server, even without an Internet connection or mobile carrier service at the time of data collection.

 

Screen Shot 2014-12-15 at 20.15.30

ODK, which uses the Android platform, supports a wide variety of questions in the electronic forms such as text, number, location, audio, video, image and barcodes.

  1.      Commcare

Commcare is an open-source mobile platform designed for data collection, client management, decision support, and behavior change communication. Commcare consists of two main technology components: Commcare Mobile and CommCareHQ.

The mobile application is used by client-facing community health workers/enumerator in visits as a data collection and educational tool and includes optional audio, image, and audio, GPS locations and video prompts. Users access the application-building platform through the website CommCareHQ  which is operated on a cloud-based server.

Screen Shot 2014-12-15 at 20.20.30

Commcare supports J2ME feature phones, Android phones, and Android tablets and can capture photos and GPS readings, Commcare supports multi-languages and non-roman character scripts as well as the integration of multimedia (image, audio, and video).

CommCare mobile versions allow applications to run offline and collected data can be transmitted to CommCareHQ when wireless (GPRS) or Internet (WI-FI) connectivity becomes available.

  1.      GEOODK

GeoODK provides a way to collect and store geo-referenced information, along with a suite of tools to visualize, analyze and manipulate ground data for specific needs. It enables an understanding of the data for decision-making, research, business, disaster management, agriculture and more.

It is based on the Open Data Kit (ODK), but has been extended with offline/online mapping functionalities, the ability to have custom map layer, as well as new spatial widgets, for collecting point, polygon and GPS tracing functionality.

Screen Shot 2014-12-15 at 20.21.48

This one blog post cannot cover each and every tool for mobile data collection, but some other tools that can be used to accomplish  mobile data collection each of which having their own unique features includes OpenXData and Episurveyor.

Why Use Mobile Technology in Collecting Data

There are several advantages as to why mobile technology should be used in collecting data some of which include,

  •         harder skipping questions,
  •         immediate (real time) access to the data from the server, which also makes data aggregation and analysis to become very rapid,
  •         Minimizes workforce and hence reduces cost of data collection by cutting out data entry personnel.
  •         Data Security is enhanced through data encryption
  •         Collect unlimited data types such as audio, video, barcodes, GPS locations
  •         Increase productivity by skipping data entry middle man

·         Save cost related to printing, storage and management of documents associated with paper based data collection.

Flattr this!

Education Data Dive in Tanzania

- November 10, 2014 in Data Expeditions, Events

We recently had a round of training in Dar es Salaam to continue growing momentum and capacity around open data in Tanzania, which is part of a bigger commitment by the Tanzanian government to the Open Government Partnership (OGP), a global initiative that aims at promoting transparency, empower citizens, fight corruption and encourage use of new technologies to improve governance. In Tanzania this commitment covers three main sectors: education, health and water.

“Open Data Training: Education Data Dive” workshop was held on 6-10 October 2014, in Dar Es Salaam, with representatives from Ministry of Education and Vocational Training (MoEVT), Prime Minister’s Office- Regional Administration and Local Government, National Examination Council of Tanzania (NECTA), E-Government Agency (EGA), National Bureau of Statistics (NBS) and National Council of Technical Education (NACTE), Tanzania Education Authority and other institutions.

Group photo for training in Dar es Salaam

Group photo for training in Dar es Salaam

This was my first time co-facilitating a workshop of this kind as a School of Data Fellow in Tanzania. And it was a fantastic opportunity for me to sharpen my facilitation skills and also to learn from other facilitators, including the main facilitator and a more experienced among us all, Michael Bauer from the School of Data. It was a wonderful thing seeing all these government agencies responsible for education, in one room, learning and sharing from one another, which even by their own admission is very rare situation. When we were preparing for this workshop we knew that there is an existing expertise and knowledge about specific education datasets, but the challenge is mainly in letting other agencies know this so that they can be able to collaborate between themselves. It was fitting then that we had several datasets from some of the agencies that we used during our workshop to bring participants to a common understanding of open data concepts, teach and practice data wrangling skills and clean and join key datasets that some of them were already familiar with.

We started the workshop by focusing on developing a common understanding of open data and data management with concepts such as improving usability of already available public data providing better metadata and improving data workflows, to open licensing of data. Then we proceeded to introduction of various tools for data cleaning, analysis and visualization, including Open Refine, QGIS, Fusion Tables and Pivot Tables. This was the first time that most of the participants were using these tools, and they were excited to see how these tools opened up a world of possibilities that they did not know that existed with the datasets that they are working with often. An example was clearly illustrated by one participant from the PMO-RALG who was glad to have discovered Pivot Tables, as most of the tasks that he is working on most datasets would be simplified a lot using Pivot Tables skills. These practical hands on sessions were met with enthusiasm by all participants, and despite dedicating two full days, they were still up to spending more time cleaning, merging, analyzing and visualizing their datasets using these tools.

Brainstorming during the workshop

Brainstorming during the workshop

One major discussion that resonated throughout the workshop and how these agencies through working together might be able to come up with solutions about this , was the lack of unique codes that can be used to identify schools by different education stakeholders when dealing with education datasets containing schools. Most participants were of the agreement that merging data sets and coming up with analysis and visualizations during the workshop, would have been much easier, if we had unique codes used by every agency whose data sets were used during the workshop.

The latter part of the workshop was mainly spent, collecting feedback about the workshop and jointly plan the way forward for the implementation of what participants learned in their daily workflows. The follow up plan was drafted in which we will have a bi–weekly sessions with some of the participants to work together to implement what they learned during the workshop and also to revise various techniques about the tools learned and to dive deep into techniques we could not cover during the workshop.

Post-it notes from the workshop

Post-it notes from the workshops

The highlight for me of this workshop was the informal discussions that participants were having during breaks in which most of them were of the agreement that Open Data initiatives need not be seen as a foreign based concept imposed on Tanzania, but rather Tanzanians themselves need to see the benefits and take ownership of this concept.

Flattr this!