The workshop was mainly led by Ali Rebaie, a Senior School of Data fellow, and Bahia Halawi, a data scientist at Data Aurora, along with the data community team assistants; Zayna Ayyad, Noor Latif and Hsein Kassab. The aim of the workshop was to give the students an introduction to the world of open data and data journalism, in particular, through tutorials on open source tools and methods used in this field. Moreover, we wanted to put students on track regarding the use of data.

On the first day, the students were introduced to data journalism, from a theoretical approach, in particular, the data pipeline which outlined the different phases in any data visualization project: find, get, verify, clean, analyze and present. After that, students were being technically involved in scraping and cleaning data using tools such as open refine and Tabula.

Day two was all about mapping, from mapping best practices to mapping formats and shapes. Students were first exposed to different types of maps and design styles that served the purpose of each map. Moreover, best mappings techniques and visualizations were emphasized to explain their relative serving purpose. Eventually, participants became able to differentiate between the dot maps and the choropleth maps as well as many others. Then they used twitter data that contained geolocations to contrast varying tweeting zones by placing these tweets at their origins on cartodb. Similarly, they created other maps using QGIS and Tilemill. The mapping exercises were really fun and students were very happy to create their own maps without a single line of code.

On the third day, Bahia gave a lecture on network analysis, some important mathematical notions needed for working with graphs as well as possible uses and case studies related to this field. Meanwhile, Ali was unveiling different open data portals to provide the students with more resources and data sets. After these topics were emphasized, a technical demonstration on the use of network analysis tool to analyze two topics was performed. Students were analyzing climate change and later, the AUB media group on Facebook was also analyzed and we had its graph drawn. It was very cool to find out that one of the top influencers in that network was among the students taking the training. Students were also taught to do the same analysis for their own friends’ lists. Facebook data was being collected and the visualizations were being drawn in a network visualization tool.

After completing the interactive types of visualizations, the fourth day was about static ones, mainly, infographics. Each student had the chance to extract the information needed for an interesting topic to transform it into a visual piece.  Bahia was working around with students, teaching them how to refine the data so that it becomes simple and short, thus usable for building the infographic design. Later, Yousif, a senior creative designer at Data Aurora, trained the students on the use of Photoshop and illustrator, two of the tools commonly used by infographic designers. At the end of the session, each student submitted a well done infographic of which some are posted below.

After the workshop Zayna had small talks with the students to get their feedback and here she quoted some of their opinions:

“It should be a full course, the performance and content was good but at some point, some data journalism tools need to be more mature and user-friendly to reduce the time needed to create a story,” said Jad Melki, Director of media studies program at AUB, “it was great overall.”

“It’s really good but the technical parts need a lot of time. We learned about new apps. Mapping, definitely I will try to learn more about it,” said Carla Sertin, a media student.

“It was great we got introduced to new stuff. Mapping, I loved it and found it very useful for me,” said Ellen Francis, civil engineering student. “The workshop was a motivation for me to work more on this,” she added, “it would work as a one semester long course.”

Azza El Masri, a media student, is interested in doing MA in data journalism. “I like it I expected it to be a bit harder, I would prefer more advanced stuff in scraping,” she added.

Just like we have seen in Nigeria, NGOs and activist seem not familiar with data pipelines or what we refer to as the data management processes, likewise basic tools that can be used in analyzing data. Unlike Nigeria, the transparency and accountability [T&A] movement in Ghana is coordinated under the STARGHANA project. Thus creating an ecosystem of groups working in the T&A component of the Open Data movement. “Two years ago, I was part of a team that initiated the SMS reporting on service delivery in the health sector, however, I am not sure how much the system is working anymore” explained Joseph Senyo, National Director of Programmes, Community and Family Aid Foundation

Participants at the Open Data event in Accra Ghana

While going through finding data, it was interesting to know that Nigeria has more datasets available online than Ghana, as most of the participants couldn’t figure out where to find the budget data of the country, although some mentioned the ministry of finance, but surprisingly we couldn’t get budget data from this website. Nevertheless, the country national statistics online portal is a one – stop shop for datasets in the country, and only one of the participants knew this existed. Analyzing using Microsoft Excel, and Google Spreadsheets was an eye – opener for participants, as most of them requested to know how this can be applicable in their various works.

While it was important to drive this conversation forward, outside the training sessions, the participants were already thinking about a 3 –day event that could bring together government, NGOs and other activist in the coming year. But, our trip to Accra would not have been complete without taking some time at the iSpace (it was a women in technology day, and we had ladies) and the LaBadi Beach – it is known that trainings can also be complemented with ice breakers on the beach – and same we did, and fortunately for us – it was the reggae night.

Getting instant feedbacks from participants

“We would have like to have more days of training, as the little minutes I spent was quite educative, especially the use of analysis tools, thus making me to know how important data is to my various monitoring and evaluation work” said Mensah Ileom of Inspire Africa. Actually, I have seen more NGO participants looking towards how data gathering can also help them in monitoring and evaluation, aside using it for advocacy, and monitoring service delivery.

Sunday, August 31st, DataMeet worked with an Economic Times Journalist Jayadevan PK with support from School of Data, to design an intro to data journalism workshop. For a while now there has been quite a bit of interest and discussion of data journalism in India. Currently there are a few courses and events around promoting data journalism, we thought there was definitely room to start to build a few modules on working with data for storytelling. Given that we have not done too many of these we decided to do an introduction and leave it limited to a few people.

You can see the agenda with notes here and the resources we shared on the data journalism resource wiki page, as well as refer to the data catalog that DataMeet has been putting together.

Thanks to Knolby Media for hosting us and for School of Data for the support. Thank you to Vikras Mishra for volunteering and taking notes, pictures, and video.

We had four story tellers with us, from various backgrounds. We spent the morning doing introduction and what was their experience with data, what their definition of data journalism is and why they wanted to take this workshop. Then we had them put up some expectations so we can gauge what the afternoon should focus on.

We then had Jaya go through the context of data journalism in terms of the world scale and the new digital journalism era.

Then we spent some time going over examples of good data journalism and bad.

After we went through resources people can use to get data. We touched upon the legal issues around using data and copyright issues. Then we discussed accuracy and how to properly attribute sources.

Then we demonstrated a few tools

Tableau
CartoDB
Scraping tools
– Scraper wiki
– IMACROS
MapBox
QGIS

Visualization Roadmap
The participants thought understanding how to visualize would be helpful.  So we went through a sort of visualization roadmap.  Then went through stories they were working on to see how we would create a visualization and also how to examine the data and come up with a data strategy for each story.

Then showed some more tools to address the suggestions from the exercise.
– BHUVAN
– Timelines
– Odyssey
– Fusion Tables
– BUMP

Feedback session

People wanted another day to let the lessons be absorbed and some more time to actually have hands on time with the tools.  Also even at the intro level it is important to make people come prepared with stories, so they have something to apply the ideas to.

To say we learned a lot is an understatement. We will definitely be planning more intro workshops and hopefully more advanced workshops in the future, we hope to continue to learn what people think is important and will keep track and see what kinds of stories come out of these learning session.

Data visualization is awesome! However, it conveys its goal when it tells a story. This weekend, Mandela’s death dominated the Twitter world and hashtags mentioning Mandela were trending worldwide. I decided to design a map that would show how people around the world tweeted the death of Nelson Mandela. First, I started collecting tweets associated with #RIPNelsonMandela using ScraperWiki. I collected approximately 250,000 tweets during the death day of Mandela. You can check this great recipe at school of data blog on how to extract and refine tweets.

After the step above, I refined the collected tweets and uploaded the data into CartoDB. It is one of my favorite open source mapping tools and I will make sure to write a CartoDB tutorial in future posts. I used the Bubble or proportional symbol map which is usually better for displaying raw data. Different areas had different tweeting rates and this reflected how different countries reacted. Countries like South Africa, UK, Spain, and Indonesia had higher tweeting rates. The diameter of the circles represents the number of retweets. With respect to colors, the darker they appeared, the higher the intensity of tweets is.

That’s not the whole story! Basically, it is easy to notice that some areas have high tweeting rates such as Indonesia and Spain. After researching about this topic, it was quite interesting to know that Mandela had a unique connection with Spain, one forged during two major sporting events. In 2010, Nelson Mandela was present in the stadium when Spain’s international football team won their first ever World Cup Football trophy as well. Moreover, for Indonesians, Mandela has always been a source of joy and pride, especially as he was fond of batik and often wore it, even in his international appearances.

Nonetheless, it was evident that interesting insights can be explored and such data visualizations can help us show the big picture. It also highlight events and facts that we are not aware of in the traditional context.

Credit: Weronika (Flickr) – Some rights reserved.

Connecting the Dots: Mapping the Bangladesh Garment Industry

This post was written in collaboration with Matt Fullerton.

During the weekend of October 18th-October 20th, a group of volunteers, data-wranglers, geo-coders, and activists teamed up with the International Labor Rights Forum and P2PU for a Data Expedition to investigate the Garment Factories. We set out to connect the dots between Bangladeshi garment producers and the clothes that you purchase from the shelves of the world’s largest retailers.

Open Knowledge Foundation Egypt and Open Knowledge Foundation Brasil ran onsite Data Expeditions on garment factories and coordinated with the global investigation.

In previous endeavors, School of Data had examined the deadly history of incidents in garment factories in Bangladesh and the location of popular retailers’ clothing production facilities. This time around, we worked draw the connections between the retailers that sell our clothes, the factories that make it, the safety agreements they’ve signed, the safety of those buildings, and the workers who occupy them day and night.

The Importance of the Garment Industry In Bangladesh

Bangladesh, as many people are aware, is a major provider of garment manufacturing services and the industry is vital to Bangladesh’s economy, accounting for over 75% of the country’s exports and 17% of the country’s GDP. As in many developing countries, conditions can be harsh with long hours and unsafe working conditions. This project seeks to provide a resource which can then be used to drive accountability for these conditions and improve the lives and livelihood of average garment worker.

What’s Being Done

Many organisations and agreements already seek to promote the garment industry in Bangladesh and to ensure worker health and safety (Bangladesh Garment Manufacturers and Exporters Association (BGMEA), Bangladesh Safety Accord, Alliance for Bangladesh Worker Safety, International Labor Rights Forum (ILRF), Clean Clothes Campaign (CCC), Fair Wear Foundation, The Solidarity Center). Collectively, these groups provide a range of data on Bangladeshi Garment factories: where they are located, safety incidents, and what retailers the factories supply. Our goal focused on connecting suppliers to sellers within the datasets, and geographically plotting the results on an interactive map. Ultimately, we seek to create a usable tool that is filterable on several criteria, specifically on membership to the various organisations and safety agreements which exist, the factory incident history, and the retailers that are being supplied by these factories. Styling of point radii would allow a quick overview of e.g. the number of workers and pop-up information could include additional data from the certification and auditing data including addresses, contact information, website addresses, incidents, and many more.

We made significant progress at the Data Expedition of October 20-21 as we:

• Geocoded the bulk of a list of over 2000 factories from the BGMEA using CartoDB and OpenRefine;
• Made data from the Alliance for Bangladesh Worker Safety available as machine readable data;
• Consolidated the data we have into a central repository;
• And began prototyping some of the data into visual presentations

Keep Moving Forward

We however do not want to stop here. Rather, we see this as simply the beginning of a longer international collaborative project to make it possible for you to find out who created your clothing and under what conditions.

Get involved in the continued investigation of the garment factories by:

• joining this simple project management board on Trello where you can see what’s being done and where you can help out. The board is open to all, so please simply add your self.
• taking on some geocoding. Help us complete geocoding the list of factories, and help us work out an infrastructure for keeping it up to date.
• taking on another data wrangling task such as data cleaning or visualisation over on Trello.
  
• joining the Garment Factory Google Group.