Earlier in the 2017 I attended the UN Data Forum. Outside some oddities out of some of the things discussed at that conference (especially on Data and power dynamics, you can read a paper we wrote in response -> A critical and ecosystem consideration of data for sustainable development in Africa), I got the opportunity to meet John Quinn who is one of the organisers of Data Science Africa. I was pretty much intrigued about the summer school as well as workshops and there and then promised that I would find a way to make it to Tanzania in July for the 2017 version.
The good news, and big thanks, is that through a NRF Knowledge Interchange and Collaboration grant I was able to attend (specifically the workshops). Another thank you to CSIR for also being flexible and encouraging with this part of my work.
My experience presenting at the workshop
I got an opportunity to speak about the work our group does at the CSIR. Specifically our interesting journey with Social Media mining and Public Safety. I enjoyed the conversations leading up to the presentation because this was one of those conferences where one feels "these are my people". The talks prior had already touched on some of the themes I was going to talk about, so it made it easy to cover the work that the wider group is doing carrying on from our past and highlight the thrusts that our PhD, MS and Honours students are doing in the area. I also participated in a panel on social media data later in the day. So in the spirit of the show Review: 5/5 ?.
— Dr Vukosi Marivate (@vukosi) July 20, 2017
My experience learning from the workshops
It was such a breath of fresh air. Seriously. The topics were varied, the experiences shared and more discussion happened later in the day as one tried to get to the bottom of some of the areas discussed. I find it hard to point out my "best" presentations because the topics covered were diverse and seeing Data Scientists talk about their experiences was it's own reward. Quickly, it became clear that this is not just about statistics or machine learning. Our collective work is about working with people to reach goals that change society. This echoed the same sentiments expressed when I visited Data Science for Social Good Europe in June. Just look at these talk titles:
- Using spatial features of human settlement to predict epidemic properties
- Understanding maternal health service utilization
- Machine learning for targeted communication in emergency
- Crowd sourcing ‘Big’ clinical data from small health facilities
- Data Revolution: A fitting Model for Development countries
- Enabling Data Revolution
- How Data Science is solving life-threatening problems in Africa plus the way forward
- Understanding Africa's Wildlife Heritage Through the lens of Genome Data
- Habari Node's Experience creating a Datacenter and Cloud Services Infrastructure
- Mining voter sentiments from Twitter data for the 2016 Uganda Presidential elections
- Algorithmic opportunities in revealing trends of food crisis from news online articles
- Mobile Phone Data for Disasters Management
- KAZNET: Leveraging digital and crowdsourcing technology for livestock market data collection
- Sensing with Farmers; crowdsourced adhoc crop surveillance
- A time series review of forest production and trade trends across the tropical region
- Convolutional Neural Network for Appliance Recognition in Energy Disaggregation
- Images - the all important developing world data format
- Modeling Wireless Sensor Network For Forest Temperature and Relative Humidity Monitoring in Usambara Mountains - A review
- A Weather Forecasting Model for Farmers in Arusha
- Jaguza Livestock App
- Air quality monitoring in Uganda
- Bank At Hause – Factor Xchange
- Monitoring economic indicators in Sub-Saharan Africa
- Price predication for the agricultural commodities.
- Prediction Modelling of Academic Performance, a Data Mining Approach
- Challenges facing data management for community based education and services programs
- Radio mining and rapid-deployment speech technology for humanitarian early warning in Uganda
The workshops should definitely be longer. There is just too much to do in 2 days. For that reason, 6/5?.
If you are thinking of attending Data Science Africa, definitely do!!! 😀
— Dr Vukosi Marivate (@vukosi) July 21, 2017
The other reason I was there
I got an opportunity to talk about the Deep Learning Indaba and our motivations putting together the almost weeklong Machine Learning tutorials/masterclasses in joburg. Luckily I was able to meet 2 participants from this years event and also chat at length to the other researchers about why we would like to collaborate and build on each others strengths. One thing that has become clear through the last 2 years has been how insular South Africa can be and also how disconnected we are. I stand to be corrected, but I was the only South African participant at the workshop. 5/5 ?.
— Dr Vukosi Marivate (@vukosi) July 20, 2017
Black in Artificial Intelligence
A number of us have been working together to increase representation in the field and there has formed a group (co-founded by Timnit Gebru) called "Black in AI". At Data Science Africa, 3 members were in attendance (including myself).
It was a quick trip to Arusha. But, because of using AirBnB I got a unique experience. My AirBnB was owned by the owner of Kitamu Coffee. Long story short, I love coffee and I had a lot of coffee and got a lot of coffee to take home with me 😀